Guidelines for
    Carcinogen
    Risk
    Assessment
    Risk
    Assessment
    Forum
    U.S. Environmental
    Protection
    Agency
    Washington,
    DC
    EPAJ63
    O/P-03/OO
    iF
    March
    2005

    DISCLAIMER
    This
    document
    has been reviewed
    in
    accordance
    with
    U.S.
    Environmental
    Protection
    Agency
    policy and
    approved
    for publication.
    Mention
    of trade
    names
    or
    commercial
    products
    does
    not constitute
    endorsement
    or
    recommendation
    for use.

    CONTENTS
    1.
    iNTRODUCTION
    .
    1-1
    1.1.
    PURPOSE
    AND
    SCOPE
    OF
    THE
    GUIDELiNES
    1-1
    1.2.
    ORGANIZATION
    AND
    APPLICATION
    OF
    THE
    GUIDELiNES
    1-3
    1.2.1.
    Organization
    1-3
    1.2.2.
    Application
    1-5
    1.3.
    KEY
    FEATURES
    OF
    THE
    CANCER
    GUIDELINES
    1-7
    1.3.1.
    Critical
    Analysis
    of
    Available
    Information
    as
    the
    Starting
    Point
    for
    Evaluation
    1-7
    1.3.2.
    Mode
    of
    Action
    1-10
    1.3.3.
    Weight
    of
    Evidence
    Narrative
    1-11
    1.3.4.
    Dose-response
    Assessment
    1-12
    1.3.5.
    Susceptible
    Populations
    and
    Lifestages
    1-13
    1.3.6.
    Evaluating
    Risks
    from
    Childhood
    Exposures
    1-15
    1.3.7.
    Emphasis
    on
    Characterization
    1-21
    2.
    HAZARD
    ASSESSMENT
    2-1
    2.1.
    OVERVIEW
    OF
    HAZARD
    ASSESSMENT
    AND
    CHARACTERIZATION
    ...
    2-1
    2.1.1.
    Analyses
    of
    Data
    2-1
    2.1.2.
    Presentation
    of
    Results
    2-1
    2.2.
    ANALYSIS
    OF
    TUMOR
    DATA
    2-2
    2.2.1.
    Human
    Data
    2-3
    2.2.1.1.
    Assessment
    of
    evidence
    of
    carcinogenicity
    from
    human
    data
    2-4
    2.2.1.2.
    Types
    of
    studies
    2-5
    2.2.1.3.
    Exposure
    issues
    2-6
    2.2.1.4.
    Biological
    markers
    2-7
    2.2.1.5.
    Confounding
    actors
    2-8
    2.2.1.6.
    Statistical
    considerations
    2-9
    2.2.1.6.1.
    Likelihood
    of
    observing
    an
    effect
    2-9
    2.2.1.6.2.
    Sampling
    and
    other
    bias
    issues
    2-10
    2.2.1.6.3.
    Combining
    statistical
    evidence
    across
    studies
    .
    ...
    2-11
    2.2.1.7.
    Evidence
    for
    Causality
    2-11
    2.2.2.
    Animal
    Data
    2-15
    2.2.2.1.
    Long-term
    Carcinogenicity
    Studies
    2-15
    2.2.2.1.1.
    Dosing
    issues
    2-16
    2.2.2.1.2.
    Statistical
    considerations
    2-19
    2.2.2.1.3.
    Concurrent
    and
    historical
    controls
    2-20
    2.2.2.1.4.
    Assessment
    of
    evidence
    of
    carcinogenicity
    from
    long
    term
    animal
    studies
    2-21
    2.2.2.1.5.
    Site
    concordance
    2-22
    2.2.2.2.
    Perinatal
    Carcinogenicity
    Studies
    2-22
    2.2.2.3.
    Other
    Studies
    2-24
    2.2.3.
    Structural
    Analogue
    Data
    2-25
    2.3.
    ANALYSIS
    OF
    OTHER
    KEY
    DATA
    2-25

    2.3.1.
    Physicochemical Properties
    .
    2-25
    2.3.2.
    Structure-Activity
    Relationships
    2-26
    2.3.3.
    Comparative
    Metabolism
    and
    Toxicokinetics
    2-27
    2.3.4.
    Toxicological
    and
    Clinical
    Findings
    2-29
    2.3.5.
    Events
    Relevant
    to Mode
    of Carcinogenic
    Action
    2-30
    2.3.5.1.
    Direct
    DNA-Reactive
    Effects
    2-31
    2.3.5.2.
    Indirect
    DNA
    Effects
    or
    Other
    Effects
    on Genes/Gene
    Expression
    2-32
    2.3.5.3.
    Precursor
    Events
    and Biomarker
    Information
    2-34
    2.3.5.4.
    Judging
    Data
    2-36
    2.4.
    MODE
    OF
    ACTION—GENERAL
    CONSIDERATIONS
    AND
    FRAMEWORK
    FOR
    ANALYSIS
    2-36
    2.4.1.
    General
    Considerations
    2-36
    2.4.2.
    Evaluating a Hypothesized
    Mode
    of Action
    2-40
    2.4.2.1.
    Peer
    Review
    2-40
    2.4.2.2.
    Use of
    the
    Framework
    2-40
    2.4.3. Framework
    for
    Evaluating
    Each
    Hypothesized
    Carcinogenic
    Mode
    of
    Action
    2-41
    2.4.3.1.
    Description
    of the
    Hypothesized
    Mode
    of
    Action
    2-43
    2.4.3.2.
    Discussion
    of the
    Experimental
    Support
    for the
    Hypothesized
    Mode
    of
    Action
    2-44
    2.4.3.3.
    Consideration
    of
    the
    Possibility
    of
    Other
    Modes
    of Action
    . 2-46
    2.4.3.4.
    Conclusions
    About
    the Hypothesized
    Mode
    of
    Action
    2-47
    2.4.4. Evolution
    with
    Experience
    2-49
    2.5.
    WEIGHT
    OF EVIDENCE NARRATIVE
    2-49
    2.6.
    HAZARD
    CHARACTERIZATION
    2-59
    3.
    DOSE-RESPONSE
    ASSESSMENT
    3-1
    3.1.
    ANALYSIS
    OF
    DOSE
    3-3
    3.1.1.
    Standardizing Different
    Experimental
    Dosing
    Regimens
    3-4
    3.1.2.
    Toxicokinetic
    Data
    and
    Modeling
    3-5
    3.1.3.
    Cross-species Scaling
    Procedures
    3-6
    3.1.3.1.
    Oral
    Exposures
    3-6
    3.1.3.2.
    Inhalation
    Exposures
    3-8
    3.1.4.
    Route
    Extrapolation
    3-9
    3.2.
    ANALYSIS
    IN
    THE RANGE
    OF OBSERVATION
    3-11
    3.2.1.
    Epidemiologic
    Studies
    3-11
    3.2.2.
    Toxicodynamic
    (“Biologically
    Based”)
    Modeling
    3-13
    3.2.3.
    Empirical
    Modeling
    (“Curve
    Fitting”)
    3-14
    3.2.4.
    Point
    of Departure
    (POD)
    3-16
    3.2.5.
    Characterizing
    the
    POD:
    The
    POD
    Narrative
    3-18
    3.2.6.
    Relative
    Potency
    Factors
    3-20
    3.3.
    EXTRAPOLATION TO
    LOWER
    DOSES
    3-20
    3.3.1.
    Choosing
    an
    Extrapolation
    Approach
    3-21
    3.3.2.
    Extrapolation
    Using
    a
    Toxicodynamic
    Model
    3-21

    3.3.3.
    Extrapolation
    Using
    a
    Low-dose
    Linear
    Model
    3-23
    3.3.4.
    Nonlinear
    Extrapolation
    to
    Lower
    Doses
    3-23
    3.3.5.
    Comparing
    and
    Combining Multiple
    Extrapolations
    3-24
    3.4.
    EXTRAPOLATION
    TO
    DIFFERENT
    HUMAN
    EXPOSURE
    SCENARIOS
    3-26
    3.5.
    EXTRAPOLATION
    TO
    SUSCEPTIBLE
    POPULATIONS
    AND
    LIFESTAGES
    3-29
    3.6.
    UNCERTAINTY
    3-29
    3.7.
    DOSE-RESPONSE
    CHARACTERIZATION
    3-32
    4.
    EXPOSURE
    ASSESSMENT
    4-i
    4.1.
    DEFINING
    THE
    ASSESSMENT
    QUESTIONS
    4-1
    4.2.
    SELECTING
    OR
    DEVELOPING
    THE
    CONCEPTUAL
    AND
    MATHEMATICAL
    MODELS
    4-3
    4.3.
    COLLECTING
    DATA
    OR SELECTING
    AND
    EVALUATING
    AVAILABLE
    DATA
    4-3
    4.3.1.
    Adjusting
    Unit
    Risks
    for
    Highly
    Exposed
    Populations
    and
    Lifestages
    . 4-4
    4.4. EXPOSURE
    CHARACTERIZATION
    4-5
    5. RISK
    CHARACTERIZATION
    5-1
    5.1.
    PURPOSE
    5-1
    5.2.
    APPLICATION
    5-4
    5.3.
    PRESENTATION
    OF
    THE
    RISK
    CHARACTERIZATION
    SUMMARY
    5-5
    5.4. CONTENT
    OF THE
    RISK
    CHARACTERIZATION
    SUMMARY
    5-6
    APPENDIX:
    MAJOR
    DEFAULT
    OPTIONS
    A-i
    APPENDIX B:
    EPA’s
    GUIDANCE
    FOR
    DATA
    QUALITY
    ASSESSMENT
    B-i
    REFERENCES
    R-l
    LIST
    OF
    FIGURES
    Figure
    1-1.
    Flow
    chart
    for
    early-life
    risk
    assessment
    using
    mode
    of
    action
    framework
    ....
    1-23
    Figure
    3-1.
    Compatibility
    of
    Alternative
    Points
    of
    Departure
    with
    Observed
    and
    Modeled
    Tumor
    Incidences
    3.35
    Figure
    3-2.
    Crossing
    between
    10%
    and
    1% Dose-Response
    Curves
    for Bladder
    Carcinomas
    and
    Liver
    Carcinomas
    Induced
    by
    2-AAF
    3-35

    1.
    INTRODUCTION
    1.1.
    PURPOSE
    AND
    SCOPE
    OF
    THE
    GUIDELINES
    These
    guidelines
    revise
    and
    replace
    the
    U.S.
    Environmental
    Protection
    Agency’s
    (EPA’s,
    or
    the
    Agency’s)
    Guidelines
    for
    Carcinogen
    Risk Assessmen4
    published
    in
    51
    FR
    33992,
    September
    24,
    1986
    (U.S.
    EPA,
    1986a)
    and
    the 1999
    interim
    final
    guidelines
    (U.S. EPA,
    1999a;
    see
    U.S.
    EPA
    2001b).
    They
    provide
    EPA
    staff with
    guidance
    for
    developing
    and using
    risk
    assessments.
    They
    also
    provide
    basic
    information
    to the
    public
    about
    the Agency’s
    risk
    assessment
    methods.
    These
    cancer
    guidelines
    are used
    with
    other
    risk assessment
    guidelines,
    such
    as
    the
    Guidelines
    for
    Mutagenicity
    Risk
    Assessment
    (U.S.
    EPA,
    1986b)
    and the
    Guidelines
    for
    Exposure
    Assessment
    (U.S.
    EPA,
    1 992a).
    Consideration
    of other
    Agency
    guidance
    documents
    is
    also
    important
    in
    assessing
    cancer
    risks
    where procedures
    for
    evaluating
    specific
    target
    organ
    effects
    have
    been developed
    (e.g.,
    assessment
    of
    thyroid
    follicular
    cell tumors,
    U.S. EPA,
    1998a).
    All of EPA’s
    guidelines
    should
    be
    consulted
    when
    conducting
    a risk
    assessment
    in
    order
    to
    ensure
    that information
    from
    studies
    on
    carcinogenesis
    and
    other
    health
    effects
    are
    considered
    together
    in the
    overall
    characterization
    of
    risk.
    This
    is particularly
    true
    in
    the
    case in
    which
    a
    precursor
    effect
    for a tumor
    is
    also
    a precursor
    or
    endpoint
    of
    other health
    effects
    or when
    there
    is
    a concern
    for a
    particular
    susceptible
    life-stage
    for
    which
    the
    Agency
    has
    developed
    guidance,
    for
    example,
    Guidelines
    for Developmental
    Toxicity
    RiskAssessment
    (U.S.
    EPA,
    1991a).
    The
    developmental
    guidelines
    discuss
    hazards
    to children
    that
    may
    result
    from exposures
    during
    preconception and prenatal
    or
    postnatal
    development
    to sexual
    maturity.
    Similar
    guidelines
    exist
    for
    reproductive
    toxicant
    risk
    assessments
    (U.S.
    EPA,
    1 996a)
    and
    for neurotoxicity
    risk
    assessment
    (U.S.
    EPA,
    1
    998b).
    The
    overall
    characterization
    of
    risk is
    conducted
    within
    the
    context
    of
    broader
    policies
    and guidance
    such
    as
    Executive
    Order
    13045,
    “Protection
    of
    Children
    From
    Environmental
    Health
    Risks
    and Safety
    Risks”(
    Executive
    Order
    13045,
    1997)
    which
    is
    the
    primary
    directive
    to federal
    agencies
    and
    departments
    to identifi
    and
    assess environmental
    health
    risks and
    safety
    risks
    that may
    disproportionately
    affect
    children.
    1—1

    The
    cancer
    guidelines
    encourage
    both
    consistency
    in the
    procedures
    that
    support
    scientific
    components
    of
    Agency
    decision
    making
    and
    flexibility
    to
    allow
    incorporation
    of
    innovations and
    contemporaneous
    scientific
    concepts.
    In
    balancing
    these
    goals,
    the
    Agency
    relies
    on
    established
    scientific
    peer
    review
    processes
    (U.S.
    EPA,
    2000a;
    0MB
    2004).
    The
    cancer
    guidelines
    incorporate
    basic
    principles
    and
    science
    policies
    based
    on
    evaluation
    of the
    currently
    available
    information.
    The Agency
    intends
    to revise
    these
    cancer
    guidelines
    when
    substantial
    changes
    are necessary.
    As
    more
    information
    about
    carcinogenesis
    develops,
    the
    need
    may
    arise
    to
    make
    appropriate
    changes
    in
    risk
    assessment
    guidance.
    In
    the
    interim,
    the
    Agency
    intends
    to
    issue
    special
    reports,
    after
    appropriate
    peer
    review,
    to
    supplement
    and
    update
    guidance
    on
    single
    topics
    (e.g.,
    U.S.
    EPA,
    1991b).
    One
    such
    guidance document,
    Supplemental
    Guidance
    for
    Assessing
    Susceptibilityfrom
    Early-Lfe
    Exposure
    to
    Carcinogens
    (“Supplemental
    Guidance”),
    was
    developed
    in
    conjunction
    with
    these
    cancer
    guidelines
    (U.S.
    EPA.,
    2005).
    Because
    both
    the
    methodology
    and
    the data
    in
    the
    Supplemental
    Guidance
    (see Section
    1.3.6)
    are
    expected
    to
    evolve
    more
    rapidly
    than
    the
    issues
    addressed
    in
    these
    cancer
    guidelines,
    the
    two
    were
    developed
    as separate
    documents.
    The Supplemental
    Guidance,
    however,
    as
    well
    as
    any
    other
    relevant
    (including
    subsequent) guidance
    documents,
    should
    be
    considered
    along
    with
    these
    cancer
    guidelines
    as risk
    assessments
    for
    carcinogens
    are
    generated.
    The
    use
    of supplemental
    guidance,
    such
    as
    the
    Supplemental
    Guidance
    for
    Assessing
    Cancer
    Susceptibility
    from
    Early-life
    Exposure
    to
    Carcinogens,
    has
    the
    advantage
    of
    allowing
    the Supplemental
    Guidance
    to be
    modified
    as
    more
    data become available.
    Thus,
    the
    consideration
    of
    new,
    peer-reviewed
    scientific
    understanding and
    data
    in
    an
    assessment
    can
    always
    be
    consistent
    with
    the purposes
    of
    these
    cancer
    guidelines.
    These
    cancer
    guidelines
    are
    intended
    as
    guidance
    only.
    They
    do not
    establish
    any
    substantive “rules”
    under
    the
    Administrative
    Procedure
    Act
    or any
    other
    law
    and have
    no binding
    effect
    on
    EPA
    or any
    regulated
    entity,
    but instead
    represent
    a non-binding
    statement
    of policy.
    EPA
    believes
    that
    the cancer
    guidelines
    represent
    a
    sound
    and
    up-to-date
    approach
    to
    cancer
    risk
    assessment,
    and
    the
    cancer
    guidelines
    enhance
    the
    application
    of
    the
    best available
    science
    in
    EPA’s
    risk
    assessments. However,
    EPA
    cancer
    risk
    assessments
    may
    be
    conducted
    differently
    than
    envisioned in the
    cancer
    guidelines
    for
    many
    reasons,
    including
    (but
    not limited
    to)
    new
    1-2

    information,
    new scientific
    understanding,
    or new
    science
    policy
    judgment.
    The
    science
    of
    risk
    assessment
    continues
    to
    develop
    rapidly,
    and
    specific
    components
    of
    the
    cancer
    guidelines
    may
    become
    outdated
    or may
    otherwise
    require
    modification
    in individual
    settings.
    Use
    of
    the cancer
    guidelines
    in
    future
    risk
    assessments will
    be based
    on
    decisions
    by
    EPA
    that
    the
    approaches
    are
    suitable
    and
    appropriate
    in the
    context
    of those
    particular
    risk
    assessments.
    These
    judgments
    will
    be
    tested
    through
    peer
    review,
    and
    risk
    assessments
    will
    be modified
    to
    use different
    approaches
    if appropriate.
    1.2.
    ORGANIZATION
    AND
    APPLICATION
    OF
    THE
    CANCER
    GUIDELINES
    1.2.1.
    Organization
    Publications
    by
    the Office
    of
    Science
    and
    Technology
    (OSTP,
    1985)
    and
    the National
    Research
    Council
    (NRC)
    (NRC,
    1983,
    1994)
    provide
    information
    and
    general
    principles
    about
    risk
    assessment.
    Risk
    assessment
    uses
    available
    scientific
    information
    on
    the
    properties
    of an
    agent’
    and
    its
    effects
    in
    biological
    systems to
    provide
    an
    evaluation
    of the
    potential
    for
    harm
    as
    a
    consequence
    of
    environmental
    exposure. The
    1983
    and
    1994
    NRC
    documents
    organize
    risk
    assessment
    information
    into
    four
    areas:
    hazard
    identification,
    dose-response
    assessment,
    exposure assessment,
    and risk
    characterization.
    This
    structure
    appears
    in these
    cancer
    guidelines,
    with
    additional
    emphasis
    placed
    on
    characterization
    of
    evidence
    and
    conclusions
    in
    each
    area
    of
    the assessment.
    In
    particular,
    the
    cancer
    guidelines
    adopt
    the
    approach
    of the
    NRC’s
    1994
    report
    in
    adding
    a
    dimension
    of
    characterization
    to the
    hazard
    identification
    step:
    an evaluation
    of the
    conditions under
    which
    its
    expression
    is
    anticipated.
    Risk
    assessment
    questions
    addressed
    in
    these
    cancer
    guidelines
    are
    as follows.
    For
    hazard—Can
    the
    identified
    agent
    present
    a carcinogenic
    hazard
    to
    humans
    and,
    if
    so, under
    what
    circumstances?
    For
    dose
    response—At
    what
    levels
    of
    exposure
    might
    effects
    occur?
    The
    term “agent”
    refers
    generally
    to any
    chemical
    substance,
    mixture,
    or
    physical
    or biological
    entity
    being
    assessed,
    unless
    otherwise
    noted
    (See
    Section
    1.2.2
    for
    a note
    on
    radiation.).
    1-3

    For
    exposure—What
    are
    the
    conditions
    of
    human
    exposure?
    For
    risk—What
    is the
    character
    of the
    risk?
    How
    well
    do
    data
    support
    conclusions
    about
    the
    nature
    and extent
    of the
    risk
    from
    various
    exposures?
    The
    risk
    characterization
    process
    first
    summarizes
    findings
    on
    hazard,
    dose
    response,
    and
    exposure
    characterizations
    and
    then
    develops
    an integrative
    analysis
    of the
    whole
    risk
    case.
    It
    ends
    in the
    writing
    of
    a technical
    risk characterization.
    Other
    documents,
    such
    as
    summaries
    for
    the
    risk
    managers
    and
    the
    public,
    reflecting
    the
    key points
    of the
    risk
    characterization
    are
    usually
    written.
    A
    summary
    for
    managers
    is a
    presentation
    for those
    who
    may
    or
    may
    not be
    familiar
    with
    the scientific details
    of cancer
    assessment.
    It
    also
    provides
    information
    for other
    interested
    readers.
    The
    initial
    steps
    in
    the risk
    characterization
    process
    are
    to make
    building
    blocks
    in
    the
    form
    of
    characterizations
    of the
    assessments
    of hazard,
    dose
    response,
    and
    exposure.
    The
    individual
    assessments
    and
    characterizations
    are then
    integrated
    to
    arrive
    at
    risk
    estimates
    for
    exposure
    scenarios
    of
    interest.
    As part
    of the
    characterization
    process,
    explicit
    evaluations
    are
    made
    of the
    hazard
    and
    risk potential
    for
    susceptible
    lifestages,
    including
    children
    (U.S.
    EPA,
    1995,
    2000b).
    The
    1994
    NRC
    document
    also
    explicitly
    called
    attention
    to the
    role
    of
    the risk
    assessment
    process
    in
    identifying
    scientific
    uncertainties
    that,
    if addressed,
    could
    serve
    to
    reduce
    their
    uncertainty
    in
    future
    iterations
    of
    the
    risk assessment.
    NRC
    recommended
    that
    when
    the
    Agency
    “reports
    estimates
    of risk
    to decisions-makers
    and the
    public,
    it
    should
    present
    not
    only
    point
    estimates
    of
    risk,
    but
    also the
    sources
    and
    magnitudes
    of
    uncertainty
    associated
    with these
    estimates”
    (p.
    15). Thus,
    the identified
    uncertainties
    serve
    as a feedback
    loop
    to
    the
    research
    community
    and
    decisionmakers,
    specifying
    areas
    and
    types
    of
    information
    that
    would
    be
    particularly
    useful.
    There
    are
    several
    reasons
    for individually
    characterizing
    the
    hazard,
    dose
    response,
    and
    exposure
    assessments.
    One
    is that
    they
    are
    often
    done
    by
    different
    people
    than
    those
    who
    do
    the
    integrative
    analyses.
    The
    second
    is that
    there
    is
    very
    often
    a lapse
    of
    time
    between
    the
    conduct
    of
    hazard
    and
    dose-response analyses
    and
    the
    conduct
    of
    exposure
    assessment
    and
    integrative
    1-4

    analysis.
    Thus,
    it
    is important
    to capture
    characterizations
    of assessments
    as
    the
    assessments
    are
    done to avoid
    the
    need
    to
    go
    back and
    reconstruct
    them.
    Finally, frequently
    a single
    hazard
    assessment
    is
    used
    by several
    programs
    for several
    different
    exposure
    scenarios.
    There
    may
    be
    one or several
    documents
    involved.
    “Integrative
    analysis”
    is
    a generic
    term; and many
    documents
    that
    have other titles
    may
    contain
    integrative analyses.
    In
    the
    following
    sections,
    the
    elements
    of these
    characterizations
    are discussed.
    1.2.2.
    Application
    The cancer
    guidelines
    apply within
    the
    framework
    of policies
    provided
    by
    applicable
    EPA statutes
    and
    do
    not alter
    such
    policies.
    The cancer
    guidelines
    cover the assessment
    of
    available
    data. They
    do not
    imply
    that
    one
    kind of data
    or
    another
    is prerequisite
    for regulatory
    action concerning
    any
    agent.
    It is
    important
    that, when
    evaluating
    and
    considering
    the use
    of any data,
    EPA analysts
    incorporate
    the basic standards
    of
    quality,
    as defined
    by the
    EPA
    Information
    Quality
    Guidelines
    (U.S.
    EPA,
    2002a
    see Appendix
    B) and
    other
    Agency guidance
    on
    data
    quality
    such as
    the EPA Quality
    Manual
    for
    Environmental
    Programs
    (U.S.
    EPA,
    2000e),
    as well
    as 0MB
    Guidelines
    for
    Ensuring
    and
    Maximizing
    the
    Quality,
    Utility, and
    Integrity
    of
    Information
    Disseminated
    by
    Federal
    Agencies
    (0MB,
    2002).
    It is very
    important
    that
    all analyses
    consider
    the
    basic
    standards
    of
    quality,
    including
    objectivity,
    utility,
    and
    integrity. A
    summary
    of the factors
    and
    considerations
    generally
    used
    by
    the
    Agency
    when
    evaluating
    and
    considering
    the use
    of scientific
    and
    technical
    infonnation
    is
    contained
    in
    EPA’s
    A Summary
    of General
    Assessment
    Factorsfor
    Evaluating
    the
    Quality
    ofScientific
    and Technical
    Information
    (U.S.
    EPA, 2003).
    Risk
    management
    applies
    directives
    in
    statutes,
    which
    may
    require
    consideration
    of
    potential
    risk
    or
    solely
    hazard
    or exposure
    potential,
    along with
    social,
    economic,
    technical,
    and other
    factors
    in decision
    making.
    Risk assessments
    may
    be used
    to
    support
    1-5

    decisions,
    but
    in order
    to
    maintain
    their
    integrity
    as
    decision-making
    tools,
    they
    are
    not
    influenced
    by
    consideration
    of
    the
    social
    or
    economic
    consequences
    of
    regulatory
    action.
    The
    assessment
    of
    risk
    from
    radiation
    sources
    is
    informed
    by
    the continuing
    examination
    of human
    data
    by the
    National
    Academy
    of
    Sciences/NRC
    in its
    series
    of numbered
    reports:
    “Biological
    Effects
    of
    Ionizing
    Radiation.”
    Although
    some
    of the
    general
    principles
    of
    these
    cancer
    guidelines
    may
    also
    apply
    to radiation
    risk
    assessments,
    some
    of
    the details
    of
    their
    risk
    assessment
    procedures
    may
    not,
    as they
    are
    most
    focused
    on
    other
    kinds
    of agents.
    Therefore,
    these
    cancer
    guidelines
    are
    not
    intended
    to
    provide
    the
    primary
    source
    of, or
    guidance
    for,
    the
    Agency’s
    evaluation
    of
    the
    carcinogenic
    risks
    of radiation.
    Not
    every
    EPA
    assessment
    has
    the
    same
    scope
    or
    depth,
    a
    factor
    recognized
    by
    the
    National
    Academy
    of
    Sciences
    (NRC,
    1996).
    For
    example,
    EPA’s
    Information
    Quality
    Guidelines
    (U.S.
    EPA,
    2002a,
    see Appendix
    B)
    discuss
    influential
    information
    that
    “will
    have
    or
    does
    have
    a clear
    and
    substantial
    impact
    ... on
    important
    public
    policies
    or
    private
    sector
    decisions ... that
    should
    adhere
    to a rigorous
    standard
    of quality.”
    It is
    often
    difficult
    to
    know
    a
    priori
    how
    the results
    of a
    risk
    assessment
    are
    likely
    to
    be
    used
    by
    the
    Agency.
    Some
    risk
    assessments
    may
    be
    used
    by
    Agency
    economists
    and
    policy
    analysts,
    and
    the
    necessary
    information
    for such
    analyses,
    as discussed
    in
    detail
    later in
    this
    document,
    should
    be
    included
    when
    practicable
    (U.S.
    EPA,
    2002a).
    On the
    other
    hand,
    Agency
    staff
    often
    conduct
    screening-
    level
    assessments
    for
    priority
    setting
    or separate
    assessments
    of
    hazard
    or
    exposure
    for
    ranking
    purposes
    or
    to
    decide
    whether
    to invest
    resources
    in collecting
    data
    for a
    full
    assessment.
    Moreover,
    a
    given
    assessment
    of
    hazard
    and
    dose
    response
    may
    be
    used
    with
    more
    than
    one
    exposure
    assessment
    that
    may
    be
    conducted
    separately
    and
    at different
    times
    as
    the need
    arises
    in
    studying
    environmental
    problems
    related
    to various
    exposure
    media.
    The
    cancer
    guidelines
    apply
    to
    these
    various
    situations
    in
    appropriate
    detail,
    given
    the scope
    and
    depth
    of
    the
    particular
    assessment.
    For
    example,
    a screening
    assessment
    may
    be
    based
    almost
    entirely
    on
    structure
    activity
    relationships
    (SARs)
    and
    default
    options,
    when
    other
    data
    are
    not
    readily
    available.
    When
    more
    data and
    resources
    are readily
    available,
    assessments
    can
    use
    a critical
    analysis
    of all
    of
    the
    available
    data
    as the
    starting
    point
    of
    the risk
    assessment.
    Under
    these
    conditions,
    default
    1-6

    options
    would
    only
    be
    used
    to address
    uncertainties
    or the
    absence
    of
    critical
    data.
    Default
    options
    are inferences
    based
    on
    general
    scientific
    knowledge
    of the
    phenomena
    in
    question
    and
    are also
    matters
    of
    policy
    concerning
    the
    appropriate
    way
    to bridge
    uncertainties
    that
    concern
    potential
    risk
    to human
    health.
    These
    cancer
    guidelines
    do
    not
    suggest
    that
    all
    of the
    kinds
    of
    data
    covered
    here
    will
    need
    to be
    available
    or used
    for
    either
    assessment
    or
    decision
    making.
    The
    level
    of
    detail
    of an
    assessment
    is
    a matter
    of
    Agency
    management discretion
    regarding
    applicable
    decision-making
    needs.
    The Agency
    generally
    presumes that
    key
    cancer
    information
    (e.g.,
    assessments
    contained
    in
    the
    Agency’s
    Integrated
    risk
    Information
    System)
    is
    “influential
    information”
    as defined
    by
    the
    EPA
    Information
    Quality
    Guidelines
    and
    “highly
    influential”
    as
    defined
    by
    OMB’s
    Information
    Quality
    Bulletin
    for Peer
    Review
    (0MB
    2004).
    1.3.
    KEY
    FEATURES
    OF
    THE
    CANCER
    GUIDELINES
    1.3.1.
    Critical
    Analysis
    of
    Available
    Information
    as
    the
    Starting
    Point
    for
    Evaluation
    As
    an increasing understanding
    of
    carcinogenesis
    is becoming
    available,
    these
    cancer
    guidelines
    adopt
    a view
    of
    default
    options
    that
    is
    consistent
    with
    EPA’s
    mission
    to
    protect
    human
    health
    while
    adhering
    to the
    tenets
    of
    sound
    science. Rather
    than
    viewing
    default
    options
    as the
    starting
    point
    from
    which
    departures
    may
    be
    justified
    by
    new
    scientific
    information,
    these
    cancer
    guidelines
    view
    a
    critical
    analysis
    of
    all
    of
    the available
    information
    that
    is relevant
    to
    assessing
    the
    carcinogenic
    risk
    as
    the
    starting
    point
    from which
    a
    default
    option
    may
    be
    invoked
    if
    needed
    to
    address
    uncertainty
    or
    the
    absence
    of
    critical
    information.
    Preference
    is
    given
    to using
    information that
    has
    been
    peer reviewed,
    e.g.,
    reported
    in
    peer-reviewed
    scientific
    journals.
    The
    primary
    goal
    of EPA
    actions
    is
    protection
    of human
    health;
    accordingly,
    as an
    Agency
    policy,
    risk
    assessment
    procedures,
    including
    default
    options
    that
    are
    used
    in
    the
    absence
    of
    scientific
    data
    to
    the
    contrary,
    should
    be
    health
    protective
    (U.S.
    EPA,
    1 999b).
    Use
    of health
    protective
    risk
    assessment
    procedures
    as described
    in
    these
    cancer
    guidelines
    means
    that
    estimates,
    while
    uncertain,
    are
    more
    likely
    to
    overstate
    than
    understate
    hazard
    and/or
    risk.
    NRC
    (1994)
    reaffirmed
    the
    use
    of
    default
    options
    as
    “a
    reasonable
    way
    to
    cope
    with
    uncertainty
    about
    the choice
    of
    appropriate
    models
    or
    theory”
    (p.
    104).
    NRC
    saw
    the
    1-7

    need
    to
    treat
    uncertainty
    in
    a
    predictable
    way
    that
    is
    “scientifically
    defensible,
    consistent
    with
    the
    agency’s
    statutory
    mission,
    and
    responsive
    to
    the
    needs
    of
    decision-makers”
    (p.
    86).
    The
    extent
    of
    health
    protection
    provided
    to
    the
    public
    ultimately
    depends
    upon
    what
    risk
    managers
    decide
    is
    the
    appropriate
    course
    of
    regulatory
    action.
    When
    risk
    assessments
    are
    performed
    using
    only
    one
    set
    of
    procedures,
    it
    may
    be
    difficult
    for
    risk
    managers
    to
    determine
    how
    much
    health
    protectiveness
    is
    built
    into
    a
    particular
    hazard
    determination
    or
    risk
    characterization.
    When
    there
    are
    alternative
    procedures
    having
    significant
    biological
    support,
    the
    Agency
    encourages
    assessments
    to
    be
    performed
    using
    these
    alternative
    procedures,
    if
    feasible,
    in
    order
    to
    shed
    light
    on
    the
    uncertainties
    in
    the
    assessment,
    recognizing
    that
    the
    Agency
    may
    decide
    to
    give
    greater
    weight
    to
    one
    set
    of
    procedures
    than
    another
    in
    a
    specific
    assessment
    or
    management
    decision.
    Encouraging
    risk
    assessors
    to
    be
    receptive
    to
    new
    scientific
    information,
    NRC
    discussed
    the
    need
    for
    departures
    from
    default
    options
    when
    a
    “sufficient
    showing”
    is
    made.
    It
    called
    on
    EPA
    to
    articulate
    clearly
    its
    criteria
    for
    a
    departure
    so
    that
    decisions
    to
    depart
    from
    default
    options
    would
    be
    “scientifically
    credible
    and
    receive
    public
    acceptance”
    (p.
    91).
    It
    was
    concerned
    that
    ad
    hoc
    departures
    would
    undercut
    the
    scientific
    credibility
    of
    a
    risk
    assessment.
    NRC
    envisioned
    that
    principles
    for
    choosing
    and
    departing
    from
    default
    options
    would
    balance
    several
    objectives,
    including
    “protecting
    the
    public
    health,
    ensuring
    scientific
    validity,
    minimizing
    serious
    errors
    in
    estimating
    risks,
    maximizing
    incentives
    for
    research,
    creating
    an
    orderly
    and
    predictable
    process,
    and
    fostering
    openness
    and
    trustworthiness”
    (p.
    81).
    Appendices
    N-i
    and
    N-2
    of
    NRC
    (1994)
    discussed
    two
    competing
    standards
    for
    choosing
    default
    options
    articulated
    by
    members
    of
    the
    committee.
    One
    suggested
    approach
    would
    evaluate
    a
    departure
    in
    terms
    of
    whether
    “it
    is
    scientifically
    plausible”
    and
    whether
    it
    “tends
    to
    protect
    public
    health
    in
    the
    face
    of
    scientific
    uncertainty”
    (p.
    601).
    An
    alternative
    approach
    “emphasizes
    scientific
    plausibility
    with
    regard
    to
    the
    use
    of
    alternative
    models”
    (p.
    631).
    Reaching
    no
    consensus
    on
    a
    single
    approach,
    NRC
    recognized
    that
    developing
    criteria
    for
    departures
    is
    an
    EPA
    policy
    matter.
    The
    basis
    for
    invoking
    a
    default
    option
    depends
    on
    the
    circumstances.
    Generally,
    if
    a
    gap
    in
    basic
    understanding
    exists
    or
    if
    agent-specific
    information
    is
    missing,
    a
    default
    option
    may
    be
    used.
    If
    agent-specific
    information
    is
    present
    but
    critical
    analysis
    reveals
    inadequacies,
    a
    default
    1-8

    option
    may
    also
    be
    used. If
    critical analysis
    of
    agent-specific
    information
    is
    consistent
    with
    one
    or more biologically
    based models
    as well
    as
    with the
    default
    option,
    the
    alternative
    models
    and
    the default
    option
    are both carried
    through
    the
    assessment
    and
    characterized
    for
    the risk
    manager.
    In this case,
    the default
    model not
    only
    fits
    the
    data,
    but also serves
    as
    a
    benchmark
    for
    comparison
    with
    other
    analyses.
    This
    case
    also highlights
    the importance
    of extensive
    experimentation
    to
    support
    a conclusion
    about mode
    of action,
    including
    addressing
    the
    issue
    of
    whether alternative
    modes
    of action
    are
    also
    plausible.
    Section
    2.4
    provides
    a
    framework
    for
    critical analysis
    of
    mode
    of action
    information
    to address
    the extent
    to
    which
    the available
    information
    supports
    the hypothesized
    mode
    of
    action,
    whether
    alternative
    modes
    of action
    are
    also
    plausible,
    and
    whether
    there
    is confidence
    that
    the
    same
    inferences
    can be
    extended
    to
    populations
    and
    lifestages
    that are not
    represented
    among
    the experimental
    data.
    Generally,
    cancer
    risk decisions
    strive
    to be
    “scientifically
    defensible,
    consistent
    with
    the
    agency’s
    statutory
    mission,
    and
    responsive
    to
    the needs
    of decision-makers”
    (NRC,
    1994).
    Scientific
    defensibility
    would
    be evaluated
    through
    use of EPA’s
    Science
    Advisory
    Board,
    EPA’s
    Office
    of Pesticide
    Programs’
    Scientific
    Advisory
    Panel,
    or
    other
    independent
    expert
    peer
    review
    panels
    to determine
    whether
    a consensus
    among scientific
    experts
    exists.
    Consistency
    with
    the
    Agency’s
    statutory
    mission
    would
    consider
    whether
    the
    risk assessment
    overall
    supports
    EPA’s
    mission
    to protect
    human health
    and safeguard
    the natural
    environment.
    Responsiveness
    to
    the
    needs of
    decisionmakers
    would
    take
    into
    account pragmatic
    considerations
    such
    as the nature
    of
    the decision;
    the
    required
    depth
    of
    analysis;
    the
    utility,
    time, and
    cost of
    generating
    new
    scientific
    data; and
    the time,
    personnel,
    and resources
    allotted to
    the risk
    assessment.
    With
    a
    multitude
    of
    types of data,
    analyses,
    and risk
    assessments,
    as well
    as
    the
    diversity
    of needs of
    decisionmakers,
    it is neither
    possible
    nor desirable
    to specif’
    step-by-step
    criteria
    for
    decisions
    to
    invoke a default
    option.
    A
    discussion
    of major
    default
    options
    appears
    in the
    Appendix.
    Screening-level
    assessments
    may
    more readily
    use
    default parameters,
    even
    worst
    case assumptions,
    that would
    not be appropriate
    in a full-scale
    assessment.
    On
    the
    other
    hand,
    significant
    risk management
    decisions
    will
    often
    benefit
    from
    a more comprehensive
    assessment,
    including
    alternative
    risk models
    having
    significant
    biological
    support.
    To
    the extent
    practicable,
    such
    assessments
    should
    provide
    central
    estimates
    of
    potential
    risks
    in conjunction
    with lower
    1-9

    and
    upper
    bounds
    (e.g., confidence
    limits)
    and
    a
    clear
    statement
    of the
    uncertainty
    associated
    with
    these
    estimates.
    In
    the
    absence
    of
    sufficient
    data
    or
    understanding
    to develop
    of
    a robust,
    biologically
    based model,
    an
    appropriate
    policy
    choice
    is to have
    a single
    preferred
    curve-fitting
    model
    for
    each
    type
    of data
    set. Many
    different
    curve-fitting
    models
    have
    been
    developed,
    and those
    that
    fit
    the observed
    data reasonably
    well may
    lead
    to several-fold
    differences
    in estimated
    risk
    at the
    lower
    end of
    the
    observed
    range.
    In
    addition,
    goodness-of-fit
    to the
    experimental
    observations
    is
    not
    by itself
    an
    effective
    means
    of discriminating
    among
    models
    that
    adequately
    fit
    the
    data
    (OSTP,
    1985). To
    provide
    some
    measure
    of consistency
    across
    different
    carcinogen
    assessments,
    EPA
    uses
    a standard
    curve-fitting
    procedure
    for tumor
    incidence
    data.
    Assessments
    that include
    a
    different
    approach
    should
    provide
    an
    adequate
    justification
    and compare
    their
    results
    with
    those
    from
    the
    standard
    procedure.
    Application
    of
    models
    to data
    should
    be
    conducted
    in an
    open
    and
    transparent
    manner.
    1.3.2.
    Mode
    of
    Action
    The
    use
    of mode
    of action
    2
    in the
    assessment
    of potential
    carcinogens
    is a main
    focus
    of
    these
    cancer
    guidelines.
    This
    area
    of emphasis
    arose
    because
    of the
    significant
    scientific
    advances
    that
    have
    developed
    concerning
    the
    causes
    of cancer
    induction.
    Elucidation
    of a
    mode
    of
    action
    for a
    particular
    cancer
    response
    in
    animals
    or
    humans
    is a data-rich
    determination.
    Significant
    information
    should
    be
    developed
    to
    ensure
    that a
    scientifically
    justifiable
    mode
    of
    action
    underlies
    the process
    leading
    to cancer
    at
    a
    given
    site.
    In
    the
    absence
    of
    sufficiently,
    scientifically
    justifiable
    mode
    of
    action
    information,
    EPA
    generally
    takes
    public
    health-
    protective,
    default
    positions
    regarding
    the
    interpretation
    of toxicologic
    and
    epidemiologic
    data:
    2
    The
    term
    “mode
    ofaction”
    is defined
    as a
    sequence
    of key
    events
    and processes,
    starting with
    interaction
    of an agent
    with a
    cell,
    proceeding
    through
    operational
    and anatomical
    changes,
    and
    resulting
    in
    cancer
    formation.
    A
    “key
    event”
    is
    an
    empirically
    observable
    precursor
    step that
    is itself a
    necessary
    element
    of the
    mode
    of action
    or
    is
    a
    biologically
    based
    marker
    for
    such an element.
    Mode
    of action
    is
    contrasted
    with
    “mechanism
    of
    action,”
    which
    implies
    a more
    detailed
    understanding
    and description
    of
    events,
    often
    at the molecular
    level,
    than is
    meant
    by
    mode
    of
    action.
    The
    toxicokinetic
    processes
    that
    lead
    to formation
    or distribution
    of the
    active
    agent
    to the target
    tissue
    are
    considered
    in
    estimating
    dose
    but
    are
    not
    part
    of
    the mode
    of
    action
    as the term
    is
    used
    here.
    There
    are many
    examples
    of possible
    modes
    of
    carcinogenic
    action, such
    as mutagenicity,
    mitogenesis,
    inhibition
    of cell
    death,
    cytotoxicity
    with
    reparative
    cell
    proliferation,
    and
    immune
    suppression.
    1-10

    animal
    tumor
    findings
    are judged
    to
    be relevant
    to
    humans,
    and
    cancer
    risks
    are
    assumed
    to
    conform
    with
    low dose
    linearity.
    Understanding
    of
    mode
    of
    action
    can
    be a key
    to identifying
    processes
    that
    may
    cause
    chemical
    exposures
    to
    differentially
    affect
    a
    particular
    population
    segment
    or
    lifestage.
    Some
    modes
    of action
    are
    anticipated
    to be
    mutagenic
    and
    are assessed
    with
    a linear
    approach.
    This
    is
    the mode
    of
    action
    of
    radiation
    and
    several
    other
    agents
    that
    are
    known
    carcinogens.
    Other
    modes
    of
    action
    may
    be modeled
    with
    either
    linear
    or
    nonlinear
    3
    approaches
    after
    a
    rigorous
    analysis
    of
    available
    data
    under
    the guidance
    provided
    in the
    framework
    for mode
    of
    action
    analysis
    (see
    Section
    2.4.3).
    1.3.3.
    Weight
    of
    Evidence
    Narrative
    The
    cancer
    guidelines
    emphasize
    the
    importance
    of weighing
    all of
    the
    evidence
    in
    reaching
    conclusions about
    the
    human
    carcinogenic
    potential
    of agents.
    This
    is
    accomplished
    in
    a single
    integrative
    step
    after
    assessing
    all
    of
    the
    individual
    lines
    of
    evidence,
    which
    is
    in
    contrast
    to
    the step-wise
    approach
    in
    the
    1986 cancer
    guidelines.
    Evidence
    considered
    includes
    tumor
    findings,
    or
    lack thereof
    in
    humans
    and
    laboratory
    animals;
    an
    agent’s
    chemical
    and
    physical
    properties;
    its
    structure-activity
    relationships
    (SARs)
    as compared
    with
    other
    carcinogenic
    agents;
    and
    studies
    addressing
    potential
    carcinogenic
    processes
    and
    mode(s)
    of action,
    either
    in
    vivo
    or
    in
    vitro.
    Data
    from
    epidemiologic
    studies
    are
    generally
    preferred
    for
    characterizing
    human
    cancer
    hazard
    and
    risk.
    However,
    all
    of
    the
    information
    discussed
    above
    could
    provide
    valuable
    insights
    into
    the
    possible
    mode(s)
    of
    action
    and
    likelihood
    of human
    cancer
    hazard
    and
    risk.
    The
    cancer
    guidelines
    recognize
    the
    growing
    sophistication
    of
    research
    methods,
    3
    The
    term
    “nonlinear”
    is used
    here
    in a narrower
    sense
    than its
    usual
    meaning
    in the
    field
    of
    mathematical
    modeling.
    In
    these
    cancer
    guidelines,
    the
    term
    “nonlinear”
    refers
    to
    threshold
    models
    (which
    show
    no
    response
    over
    a range
    of
    low
    doses
    that include
    zero)
    and
    some
    nonthreshold
    models
    (e.g.,
    a quadractic
    model,
    which
    shows
    some
    response
    at
    all
    doses
    above
    zero).
    In these
    cancer
    guidelines,
    a nonlinear
    model
    is one whose
    slope
    is
    zero
    at
    (and
    perhaps
    above)
    a dose
    of zero.
    A
    low-dose-linear
    model
    is
    one
    whose
    slope
    is
    greater
    than
    zero
    at a dose
    of zero.
    A
    low-dose-linear model
    approximates
    a straight
    line only
    at
    very
    low
    doses;
    at
    higher
    doses
    near
    the
    observed
    data,
    a
    low-dose-linear model
    can
    display
    curvature.
    The
    term
    “low-dose-linear”
    is
    often abbreviated
    “linear,”
    although
    a
    low-dose-linear model
    is
    not linear
    at all
    doses.
    Use
    of nonlinear
    approaches
    does
    not imply
    a
    biological
    threshold
    dose
    below
    which
    the
    response
    is zero.
    Estimating
    thresholds
    can
    be problematic;
    for
    example,
    a response
    that
    is not
    statistically
    significant
    can be
    consistent
    with a
    small
    risk that
    falls
    below
    an
    experiment’s
    power
    of
    detection.
    1—11

    particularly
    in their
    ability
    to
    reveal
    the
    modes
    of action
    of carcinogenic
    agents
    at cellular
    and
    subcellular
    levels
    as
    well
    as toxicokinetic
    processes.
    Weighing
    of the
    evidence
    includes
    addressing not
    only
    the
    likelihood
    of
    human
    carcinogenic
    effects
    of
    the
    agent
    but
    also the
    conditions
    under
    which
    such
    effects
    may
    be
    expressed,
    to
    the
    extent
    that
    these
    are revealed
    in the
    toxicological
    and
    other
    biologically
    important
    features
    of
    the agent.
    The
    weight
    of
    evidence
    narrative
    to characterize
    hazard
    summarizes
    the results
    of
    the
    hazard
    assessment
    and
    provides
    a
    conclusion
    with
    regard
    to human
    carcinogenic
    potential.
    The
    narrative
    explains
    the
    kinds
    of evidence
    available
    and how
    they
    fit
    together
    in
    drawing
    conclusions,
    and
    it points
    out significant
    issues/strengths/limitations
    of
    the
    data and
    conclusions.
    Because
    the narrative
    also
    summarizes
    the
    mode
    of action
    information,
    it sets
    the
    stage
    for
    the
    discussion
    of
    the
    rationale
    underlying
    a
    recommended
    approach
    to
    dose-response
    assessment.
    In
    order
    to
    provide
    some
    measure
    of clarity
    and consistency
    in
    an
    otherwise
    free-form,
    narrative
    characterization,
    standard
    descriptors
    are used
    as
    part
    of
    the hazard
    narrative
    to
    express
    the
    conclusion
    regarding
    the
    weight
    of
    evidence
    for
    carcinogenic
    hazard
    potential.
    There
    are
    five
    recommended
    standard
    hazard
    descriptors:
    “Carcinogenic
    to Humans,”
    “Likely
    to
    Be
    Carcinogenic to
    Humans,”
    “Suggestive
    Evidence
    of Carcinogenic Potential,”
    “Inadequate
    Information
    to
    Assess
    Carcinogenic
    Potential,”
    and “Not
    Likely
    to
    Be Carcinogenic
    to
    Humans.”
    Each
    standard
    descriptor
    may
    be applicable
    to
    a wide
    variety
    of data
    sets
    and weights
    of
    evidence
    and
    is presented only in
    the
    context
    of
    a
    weight
    of
    evidence
    narrative.
    Furthermore,
    as
    described
    in
    Section
    2.5
    of these
    cancer
    guidelines,
    more
    than
    one
    conclusion
    may
    be
    reached
    for
    an
    agent.
    1.3.4.
    Dose-response
    Assessment
    Dose-response
    assessment evaluates
    potential
    risks
    to humans
    at
    particular
    exposure
    levels.
    The
    approach
    to
    dose-response
    assessment
    for
    a particular
    agent
    is
    based
    on the
    conclusion reached
    as
    to its
    potential
    mode(s)
    of
    action
    for each
    tumor
    type.
    Because
    an
    agent
    may
    induce
    multiple
    tumor
    types,
    the dose-response
    assessment
    includes
    an analysis
    of all
    tumor
    types,
    followed
    by an
    overall
    synthesis
    that includes
    a
    characterization
    of the
    risk estimates
    across
    tumor
    types,
    the
    strength
    of the
    mode
    of
    action
    information
    of
    each
    tumor
    type,
    and
    the
    1-12

    anticipated
    relevance
    of each
    tumor type
    to
    humans,
    including
    susceptible
    populations
    and
    lifestages
    (e.g.,
    childhood).
    Dose-response
    assessment
    for
    each
    tumor
    type
    is
    performed
    in two
    steps:
    assessment
    of
    observed
    data
    to derive
    a
    point
    of
    departure
    (POD),
    4
    followed
    by extrapolation
    to
    lower
    exposures
    to
    the
    extent
    that is
    necessary.
    Data
    from
    epidemiologic
    studies,
    of sufficient
    quality,
    are generally
    preferred
    for estimating
    risks.
    When
    animal studies
    are
    the
    basis
    of the
    analysis,
    the estimation
    of a
    human-equivalent
    dose
    should
    utilize
    toxic
    okinetic
    data
    to
    inform
    cross
    species
    dose
    scaling
    if appropriate
    and if
    adequate
    data
    are
    available.
    Otherwise,
    default
    procedures
    should
    be applied.
    For
    oral
    dose,
    based
    on
    current
    science,
    an
    appropriate
    default
    option
    is to
    scale
    daily
    applied
    doses experienced
    for
    a lifetime
    in
    proportion
    to
    body
    weight
    raised
    to the
    3/4
    power
    (U.S.
    EPA, 1
    992b).
    For inhalation
    dose,
    based
    on
    current
    science,
    an
    appropriate
    default
    methodology
    estimates
    respiratory
    deposition
    of
    particles
    and
    gases
    and
    estimates
    internal
    doses
    of gases
    with different
    absorption
    characteristics.
    When
    toxicokinetic
    modeling
    (see
    Section
    3.1.2)
    is used
    without
    toxicodynamic
    modeling
    (see
    Section
    3.2.2),
    the
    dose-response
    assessment
    develops
    and
    supports
    an
    approach
    for
    addressing
    toxicodynamic
    equivalence,
    perhaps
    by
    retaining
    some
    of the
    cross-species
    scaling
    factor
    (see Section
    3.1.3).
    Guidance
    is
    also provided
    for
    adjustment
    of dose
    from
    adults
    to
    children
    (see
    Section
    4.3.1).
    Response
    data on
    effects
    of the
    agent on
    carcinogenic
    processes
    are analyzed
    (nontumor
    data)
    in
    addition
    to
    data on
    tumor
    incidence.
    If
    appropriate,
    the analyses
    of data
    on tumor
    incidence
    and
    on
    precursor
    effects
    may
    be
    used in
    combination.
    To
    the
    extent the
    relationship
    between
    precursor
    effects
    and
    tumor
    incidence
    are
    known,
    precursor
    data
    may
    be used
    to
    estimate
    a
    dose-response
    function
    below
    the observable
    tumor
    data.
    Study
    of the
    dose-response
    function
    for
    effects
    believed
    to
    be
    part
    of the
    carcinogenic
    process
    influenced
    by
    the agent
    may
    also
    assist
    in
    evaluating
    the
    relationship
    of exposure
    and response
    in
    the range
    of observation
    and
    at
    exposure
    levels
    below
    the
    range
    of
    observation.
    A
    “point
    of
    departure”
    (POD)
    marks
    the
    beginning
    of extrapolation
    to
    lower
    doses.
    The
    POD
    is an
    estimated
    dose
    (usually
    expressed
    in
    human-equivalent
    terms)
    near
    the
    lower end
    of
    the
    observed
    range,
    without
    significant
    extrapolation
    to lower
    doses.
    1-13

    The
    first step
    of
    dose-response
    assessment
    is
    evaluation
    within
    the
    range
    of
    observation.
    Approaches
    to
    analysis
    of
    the
    range
    of
    observation
    of
    epidemiologic
    studies
    are
    determined
    by
    the
    type
    of
    study
    and
    how
    dose
    and
    response
    are
    measured
    in the
    study.
    In
    the
    absence
    of
    adequate
    human
    data
    for dose-response analysis,
    animal
    data
    are
    generally
    used.
    If there
    are
    sufficient
    quantitative
    data
    and
    adequate
    understanding
    of
    the carcinogenic
    process,
    a
    biologically
    based
    model
    may
    be
    developed
    to
    relate
    dose
    and
    response
    data
    on an
    agent-specific
    basis.
    Otherwise,
    as a
    default
    procedure,
    a standard
    model
    can be
    used
    to curve-fit
    the
    data.
    The
    POD
    for
    extrapolating
    the
    relationship
    to
    environmental
    exposure
    levels
    of
    interest,
    when
    the latter
    are
    outside
    the
    range
    of
    observed
    data,
    is
    generally
    the
    lower
    95% confidence
    limit
    on
    the
    lowest
    dose
    level
    that
    can
    be
    supported
    for
    modeling
    by
    the data.
    SAB
    (1997)
    suggested
    that,
    “it may
    be
    appropriate
    to
    emphasize
    lower
    statistical
    bounds
    in
    screening
    analyses
    and
    in
    activities
    designed
    to develop
    an
    appropriate
    human
    exposure
    value,
    since
    such
    activities
    require
    accounting
    for
    various
    types
    of uncertainties
    and a
    lower
    bound
    on
    the
    central
    estimate
    is
    a scientifically-based
    approach
    accounting
    for
    the
    uncertainty
    in
    the
    true
    value
    of
    the
    ED
    10
    [or
    central
    estimate].”
    However,
    the
    consensus
    of
    the
    SAB
    (1997)
    was
    that,
    “both
    point
    estimates
    and
    statistical
    bounds
    can
    be
    useful
    in
    different
    circumstances,
    and
    recommended
    that the
    Agency
    routinely
    calculate
    and
    present
    the
    point
    estimate
    of
    the
    ED
    10
    [or
    central
    estimate]
    and
    the
    corresponding
    upper
    and
    lower
    95%
    statistical
    bounds.”
    For example,
    it may
    be
    appropriate
    to emphasize the central
    estimate
    in
    activities
    that
    involve
    formal
    uncertainty
    analysis
    that
    are
    required
    by
    0MB
    Circular
    A-4
    (0MB,
    2003)
    as
    well
    as ranking
    agents
    as
    to their
    carcinogenic
    hazard.
    Thus,
    risk assessors should
    calculate,
    to
    the
    extent
    practicable,
    and
    present
    the
    central
    estimate
    and
    the corresponding
    upper
    and
    lower
    statistical
    bounds
    (such
    as
    confidence
    limits)
    to
    inform
    decisiomiiakers.
    The
    second
    step
    of
    dose-response
    assessment
    is
    extrapolation
    to
    lower
    dose
    levels,
    if
    needed.
    This
    extrapolation
    is based
    on
    extension
    of a
    biologically
    based
    model
    if supported
    by
    substantial data
    (see Section
    3.3.2).
    Otherwise,
    default
    approaches
    can be
    applied
    that are
    consistent
    with
    current
    understanding
    of
    mode(s)
    of
    action
    of the
    agent,
    including
    approaches
    that
    assume
    linearity
    or
    nonlinearity
    of the
    dose-response
    relationship,
    or
    both.
    A
    default
    approach
    for
    linearity
    extends
    a
    straight
    line
    from
    the
    POD
    to
    zero
    dose/zero
    response
    (see
    1-14

    Section
    3.3.3).
    The
    linear
    approach
    is used
    when:
    (1) there
    is
    an absence
    of
    sufficient
    information
    on
    modes
    of
    action
    or (2)
    the mode
    of
    action
    information
    indicates
    that
    the
    dose-
    response
    curve
    at
    low dose
    is
    or is
    expected
    to
    be linear.
    Where
    alternative
    approaches
    have
    significant
    biological
    support,
    and
    no
    scientific
    consensus
    favors
    a single
    approach,
    an
    assessment
    may
    present
    results
    using
    alternative
    approaches.
    A
    nonlinear
    approach
    can
    be
    used
    to develop
    a
    reference
    dose
    or
    a reference
    concentration
    (see
    Section
    3.3.4).
    1.3.5.
    Susceptible Populations
    and
    Lifestages
    An important
    use
    of mode
    of
    action
    information
    is
    to identify
    susceptible
    populations
    and
    lifestages.
    It
    is rare
    to
    have
    epidemiologic
    studies
    or
    animal
    bioassays
    conducted
    in
    susceptible
    individuals.
    This
    information
    need
    can
    be
    filled
    by
    identifying
    the
    key
    events
    of
    the
    mode
    of
    action
    and
    then
    identifying
    risk
    factors,
    such
    as
    differences
    due
    to
    genetic
    polymorphisms,
    disease,
    altered
    organ
    function,
    lifestyle,
    and
    lifestage,
    that
    can augment
    these
    key
    events.
    To
    do
    this,
    the information
    about
    the
    key
    precursor
    events
    is
    reviewed
    to
    identify
    particular
    populations
    or
    lifestages
    that
    can
    be particularly
    susceptible
    to
    their
    occurrence
    (see
    Section
    2.4.3.4).
    Any
    information
    suggesting
    quantitative
    differences
    between
    populations
    or lifestages is
    flagged
    for
    consideration in
    the dose-response
    assessment
    (see
    Section
    3.5
    and
    U.S.
    EPA
    2002b).
    1.3.6.
    Evaluating
    Risks
    from
    Childhood
    Exposures
    NRC
    (1994)
    recommended
    that
    “EPA
    should
    assess
    risks
    to
    infants
    and
    children
    whenever
    it
    appears
    that
    their
    risks
    might
    be
    greater
    than
    those
    of
    adults.”
    Executive
    Order
    13045
    (1997)
    requires
    that
    “each
    Federal
    Agency
    shall
    make
    it
    a high
    priority
    to
    identify
    and
    assess
    environmental
    health
    and
    safety
    risks
    that
    may
    disproportionately
    affect
    children,
    and
    shall
    ensure
    that
    their
    policies,
    programs,
    and
    standards
    address
    disproportionate
    risks
    that
    result
    from
    environmental health
    risks
    or safety
    risks.”
    In assessing
    risks
    to children,
    EPA
    considers
    both
    effects
    manifest
    during
    childhood
    and
    early-life
    exposures
    that
    can
    contribute
    to
    effects
    at any
    time
    later
    in
    life.
    These
    cancer
    guidelines
    view
    childhood
    as a
    sequence
    of
    lifestages
    rather
    than
    viewing
    children
    as
    a
    subpopulation, the distinction
    being
    that
    a subpopulation
    refers
    to a portion
    of
    the
    1-15

    population,
    whereas
    a lifestage
    is inclusive
    of the
    entire
    population.
    Exposures
    that are
    of
    concern
    extend
    from
    conception
    through
    adolescence
    and
    also
    include
    pre-conception
    exposures
    of
    both
    parents.
    These
    cancer
    guidelines
    use
    the
    term
    “childhood”
    in
    this
    more
    inclusive
    sense.
    Rarely
    are
    there
    studies
    that
    directly
    evaluate
    risks
    following
    early-life
    exposure.
    Epidemiologic
    studies
    of
    early-life
    exposure
    to
    environmental
    agents
    are
    seldom
    available.
    Standard
    animal
    bioassays
    generally
    begin
    dosing
    after
    the
    animals
    are several
    weeks
    old,
    when
    many
    organ
    systems
    are
    mature.
    This
    could
    lead
    to an
    understatement
    of
    risk,
    because
    an
    accepted
    concept
    in
    the
    science
    of
    carcinogenesis
    is that
    young
    animals
    are
    usually
    more
    susceptible
    to the
    carcinogenic
    activity
    of
    a chemical
    than
    are mature
    animals
    (McConnell,
    1992).
    At
    this time,
    there
    is
    some
    evidence
    of higher
    cancer
    risks
    following
    early-life
    exposure.
    For
    radiation
    carcinogenesis,
    data
    indicate
    that
    risks
    for
    several
    forms
    of cancer
    are
    highest
    following
    childhood exposure
    (NRC,
    1990;
    Miller,
    1995;
    U.S.
    EPA,
    1999c).
    These
    human
    results
    are
    supported
    by
    the
    few
    animal
    bioassays
    that
    include
    perinatal
    (prenatal
    or
    early
    posthatal)
    exposure.
    Perinatal
    exposure
    to some
    agents
    can
    induce
    higher
    incidences
    of
    the
    tumors
    seen
    in
    standard
    bioassays;
    some
    examples
    include
    vinyl
    chloride
    (Maltoni
    et al.,
    1981),
    diethylnitrosamine
    (Peto
    et
    al.,
    1984),
    benzidine,
    DDT,
    dieldrin,
    and
    safrole
    (Vesselinovitch
    et
    al.,
    1979).
    Moreover,
    perinatal
    exposure
    to
    some
    agents,
    including
    vinyl
    chloride
    (Maltoni
    et
    al.,
    1981)
    and
    saccharin
    (Cohen,
    1995;
    Whysner
    and
    Williams,
    1996),
    can
    induce
    different
    tumors
    that are
    not
    seen
    in
    standard
    bioassays.
    Surveys
    comparing
    perinatal
    carcinogenesis
    bioassays
    with
    standard
    bioassays
    for
    a limited
    number
    of chemicals
    (McConnell,
    1992;
    U.S.
    EPA,
    1
    996b)
    have
    concluded
    that
    the
    same
    tumor
    sites
    are
    usually
    observed
    following
    either
    perinatal
    or
    adult
    exposure,
    and
    perinatal exposure
    in
    conjunction
    with
    adult
    exposure
    usually
    increases
    the
    incidence
    of
    tumors
    or
    reduces
    the
    latent
    period
    before
    tumors
    are
    observed.
    1-16

    The
    risk attributable
    to early-life
    exposure
    often
    appears
    modest
    compared
    with
    the
    risk
    from
    lifetime
    exposure,
    but
    it can be
    about
    10-fold
    higher than
    the
    risk
    from
    an
    exposure
    of
    similar
    duration
    occurring
    later in
    life (Ginsberg,
    2003).
    Further
    research
    is
    warranted
    to
    investigate
    the
    extent
    to which
    these
    findings
    apply to
    specific
    agents,
    chemical
    classes,
    and
    modes
    of
    action
    or in
    general.
    These
    empirical
    results
    are
    consistent
    with
    current
    understanding
    of the
    biological
    processes
    involved
    in
    carcinogenesis,
    which
    leads to
    a reasonable
    expectation
    that
    children
    can
    be
    more
    susceptible
    to many
    carcinogenic
    agents
    (Anderson
    et al.,
    2000; Birnbaum
    and
    Fenton,
    2003;
    Ginsberg,
    2003;
    Miller
    et
    al., 2002;
    Scheuplein
    et al.,
    2002).
    Some
    aspects
    potentially
    leading
    to
    childhood
    susceptibility
    are listed
    below.
    Differences
    in the
    capacity
    to metabolize
    and clear
    chemicals
    can
    result
    in larger
    or
    smaller
    internal
    doses of
    the active
    agent(s).
    More
    frequent
    cell
    division
    during
    development
    can
    result
    in
    enhanced
    expression
    of
    mutations
    due to
    the
    reduced
    time
    available
    for repair
    of
    DNA lesions
    (Slikker
    et
    al.,
    2004).
    Some
    embryonic
    cells,
    such
    as brain
    cells,
    lack key
    DNA
    repair
    enzymes.
    More
    frequent
    cell
    division
    during
    development
    can
    result
    in
    clonal
    expansion
    of
    cells
    with mutations
    from
    prior
    unrepaired
    DNA damage
    (Slikker
    et
    al.,
    2004).
    Some
    components
    of
    the
    immune
    system
    are not
    fully functional
    during
    development
    (Holladay
    and Smialowicz,
    2000;
    Holsapple
    et al.,
    2003).
    Hormonal
    systems
    operate
    at
    different
    levels
    during
    different
    lifestages.
    1-17

    Induction
    of
    developmental
    abnormalities
    can
    result
    in
    a predisposition
    to
    carcinogenic effects
    later
    in
    life
    (Anderson
    et
    al., 2000;
    Bimbaum
    and
    Fenton,
    2003;
    Fenton
    and
    Davis,
    2002).
    To
    evaluate
    risks
    from
    early-life exposure,
    these
    cancer
    guidelines
    emphasize
    the
    role
    of
    toxicokinetic
    information
    to estimate
    levels
    of the
    active
    agent
    in
    children
    and toxicodynamic
    information
    to identify
    whether
    any
    key
    events
    of the
    mode
    of
    action
    are
    of increased
    concern
    early
    in life.
    Developmental
    toxicity
    studies
    can
    provide
    information
    on
    critical
    periods
    of
    exposure
    for
    particular targets
    of
    toxicity.
    An
    approach
    to
    assessing
    risks
    from
    early-life
    exposure
    is
    presented
    in
    Figure
    1-1.
    In the
    hazard
    assessment,
    when
    there
    are
    mode
    of
    action
    data,
    the
    assessment
    considers
    whether
    these
    data
    have
    special
    relevance
    during
    childhood,
    considering
    the
    various
    aspects
    of
    development
    listed
    above.
    Examples
    of
    such
    data include
    toxicokinetics
    that
    predict
    a
    sufficiently
    large
    internal
    dose
    in children
    or a
    mode
    of
    action
    where
    a
    key
    precursor
    event
    is
    more
    likely
    to
    occur
    during
    childhood.
    There
    is no
    recommended
    default
    to settle
    the question
    of
    whether
    tumors
    arising
    through
    a
    mode
    of
    action
    are
    relevant
    during
    childhood;
    and
    adequate
    understanding
    the
    mode
    of
    action
    implies
    that
    there
    are sufficient
    data
    (on
    either
    the specific
    agent
    or
    the
    general
    mode
    of action)
    to
    form
    a
    confident
    conclusion
    about
    relevance
    during
    childhood
    (see
    Section
    2.4.3.4).
    In the
    dose-response
    assessment,
    the
    potential
    for
    susceptibility
    during
    childhood
    warrants
    explicit
    consideration
    in each
    assessment.
    These
    cancer
    guidelines
    encourage
    developing
    separate
    risk
    estimates
    for children
    according
    to a
    tiered
    approach
    that
    considers
    what
    pertinent
    data
    are
    available
    (see Section
    3.5).
    Childhood
    may
    be a
    susceptible
    period;
    moreover,
    exposures
    during
    childhood
    generally
    are not
    equivalent
    to
    exposures
    at other
    times
    and
    may
    be
    treated
    differently
    from
    exposures
    occurring
    later
    in
    life
    (see
    Section
    3.5).
    In
    addition,
    adjustment
    of
    unit risk
    estimates
    may
    be
    warranted
    when
    used
    to
    estimate
    risks
    from
    childhood
    exposure
    (see
    Section
    4.4).
    At this
    time,
    several
    limitations
    preclude
    a full
    assessment
    of
    children’s
    risk.
    There
    are
    no
    generally
    used
    testing
    protocols
    to
    identify
    potential
    environmental
    causes
    of
    cancers
    that
    are
    1-18

    unique
    to
    children,
    including
    several
    forms
    of childhood
    cancer
    and
    cancers
    that
    develop
    from
    parental
    exposures,
    and cases
    where
    developmental
    exposure
    may alter
    susceptibility
    to
    carcinogen
    exposure
    in
    the adult
    (Bimbaum
    and
    Fenton,
    2003).
    Dose-response
    assessment
    is
    limited
    by
    an
    inability
    to observe
    how
    developmental
    exposure
    can
    modif’
    incidence
    and
    latency
    and
    an inability
    to estimate
    the
    ultimate
    tumor
    response
    resulting
    from
    induced
    susceptibility
    to
    later
    carcinogen
    exposures.
    To partially
    address
    the
    limitations
    identified
    above,
    EPA
    developed
    in conjunction
    with
    these
    cancer
    guidelines,
    Supplemental
    Guidance
    for
    Assessing
    Susceptibility
    from
    Early-Lfe
    Exposure
    to Carcinogens (“Supplemental
    Guidance”).
    The Supplemental
    Guidance
    addresses
    a
    number
    of
    issues
    pertaining
    to
    cancer
    risks
    associated
    with
    early-life
    exposures
    generally,
    but
    provides
    specific
    guidance
    on
    procedures
    for
    adjusting
    cancer
    potency
    estimates
    only
    for
    carcinogens
    acting
    through
    a
    mutagenic
    mode
    of
    action.
    This Supplemental
    Guidance
    recommends,
    for such
    chemicals
    when
    no
    chemical-specific
    data
    exist,
    a default
    approach
    using
    estimates
    from
    chronic
    studies
    (i.e., cancer
    slope
    factors)
    with
    appropriate
    modifications
    to
    address
    the
    potential
    for
    differential
    risk
    of early-lifestage
    exposure.
    The
    Agency
    considered
    both the
    advantages
    and
    disadvantages
    to extending
    the
    recormnended,
    age
    dependent
    adjustment
    factors
    for
    carcinogenic
    potency
    to carcinogenic
    agents
    for
    which
    the mode
    of action
    remains
    unknown.
    EPA decided
    to recommend
    these
    factors
    only
    for carcinogens
    acting
    through
    a
    mutagenic
    mode
    of
    action
    based
    on a combination
    of
    analysis
    of
    available
    data
    and
    long-standing
    science
    policy
    positions
    which
    govern
    the
    Agency’s
    overall
    approach
    to
    carcinogen
    risk
    assessment.
    In
    general,
    the Agency
    prefers
    to rely
    on
    analyses
    of
    data, rather
    than
    general
    defaults.
    When
    data
    are
    available
    for
    a sensitive
    lifestage,
    they
    would
    be
    used directly
    to
    evaluate
    risks
    for
    that
    chemical
    and
    that
    lifestage
    on a case-by-case
    basis.
    In
    the
    case
    of
    nonmutagenic
    carcinogens,
    when
    the
    mode
    of action
    is unknown,
    the
    data were
    judged
    by
    EPA
    to be
    too
    limited
    and
    the
    modes
    of
    action too
    diverse
    to use
    this
    as
    a
    category
    for which
    a
    general
    default
    adjustment
    factor
    approach
    can
    be
    applied.
    In this
    situation,
    a
    linear
    low-dose
    extrapolation
    methodology
    (without
    further
    adjustment)
    is recommended.
    It is
    the
    Agency’s
    long-standing
    science
    policy
    position
    that
    use
    of the
    linear
    low-dose
    extrapolation
    approach
    1-19

    provides
    adequate
    public
    health
    conservatism
    in the
    absence
    of
    chemical-specific
    data
    indicating
    differential
    early-life
    sensitivity
    or when
    the
    mode
    of
    action
    is not
    mutagenic.
    The
    Agency
    expects
    to
    produce
    additional
    supplemental
    guidance
    for other
    modes
    of
    action,
    as
    data
    from
    new
    research
    and
    toxicity
    testing
    indicate
    it is
    warranted.
    EPA
    intends
    to
    focus
    its research,
    and
    work
    collaboratively
    with
    its
    federal
    partners,
    to improve
    understanding
    of
    the implications
    of
    early
    life
    exposure
    to
    carcinogens.
    Development
    of
    guidance
    for
    estrogenic
    agents
    and chemicals
    acting
    through
    other
    processes
    resulting
    in
    endocrine
    disruption
    and
    subsequent
    carcinogenesis,
    for
    example,
    might
    be
    a
    reasonable
    priority
    in light
    of
    the human
    experience
    with
    diethylstilbesterol
    and
    the
    existing
    early
    life animal
    studies.
    It
    is
    worth
    noting
    that
    each
    mode
    of
    action
    for
    endocrine
    disruption
    will probably
    require
    separate
    analysis.
    As
    the
    Agency
    examines
    additional
    carcinogenic
    agents,
    the
    age
    groupings
    may
    differ
    from
    those
    recommended for assessing
    cancer
    risks
    from
    early-life
    exposure
    to
    chemicals
    with
    a
    mutagenic
    mode
    of action.
    Puberty
    and
    its associated
    biological
    changes,
    for
    example,
    involve
    many
    biological
    processes
    that
    could
    lead
    to
    changes
    in
    sensitivity
    to the
    effects
    of
    some
    carcinogens,
    depending
    on
    their
    mode
    of
    action.
    The
    Agency
    is interested
    in identifying
    lifestages
    that
    may
    be
    particularly
    sensitive
    or refractory
    for carcinogenesis,
    and believes
    that
    the
    mode
    of
    action
    framework
    described
    in
    these
    cancer
    guidelines
    is an appropriate
    mechanism
    for
    elucidating
    these
    lifestages. For each
    additional
    mode
    of
    action
    evaluated,
    the
    various
    age
    groupings
    determined
    to
    be at
    differential
    risk may
    differ
    from
    those
    proposed
    in
    the
    Supplemental Guidance.
    For
    example,
    the
    age
    groupings
    selected
    for
    the
    age-dependent
    adjustments
    for
    carcinogens
    acting
    through
    a
    mutagenic
    mode
    of
    action
    were
    initially
    selected
    based
    on the
    available
    data,
    i.e.,
    for
    the laboratory
    animal
    age
    range
    representative
    of
    birth
    to
    <
    2
    years
    in
    humans.
    More
    limited
    data
    and
    information
    on human
    biology
    were
    used
    to
    determine
    a
    science-informed
    policy
    regarding
    2
    to
    <
    16 years.
    Data
    were
    not
    available
    to
    refine
    the
    latter
    age group.
    If
    more
    data
    become
    available
    regarding
    carcinogens
    with
    a
    mutagenic
    mode
    of
    action,
    consideration
    may
    be
    given
    to
    further
    refinement
    of
    these
    age
    groups.
    1-20

    1.3.7.
    Emphasis
    on
    Characterization
    The cancer
    guidelines
    emphasize
    the
    importance
    of
    a
    clear
    and
    useful
    characterization
    narrative
    that
    summarizes
    the
    analyses
    of
    hazard,
    dose-response,
    and
    exposure
    assessment.
    These
    characterizations
    summarize
    the
    assessments
    to explain
    the
    extent
    and weight
    of
    evidence,
    major
    points
    of
    interpretation
    and
    rationale
    for
    their
    selection,
    strengths
    and
    wealcnesses
    of
    the
    evidence
    and
    the
    analysis,
    and
    discuss
    alternative
    conclusions
    and uncertainties
    that
    deserve
    serious
    consideration
    (U.S.
    EPA,
    2000b).
    They
    serve
    as starting
    materials
    for the
    overall
    risk
    characterization
    process
    that
    completes
    the
    risk assessment.
    1-21

    Figure 1-1.
    Flow
    chart for
    early-life
    risk assessment
    using
    mode
    of
    action
    framework.
    Use
    linear
    extmpolatinn
    as
    a default.
    No
    further
    analys
    of
    tumo is.
    Model
    using
    MOA or
    use
    REYRfC
    method
    as
    default.
    Adjuments
    for
    suseeptible
    lifeages
    or populatons
    are pert
    ofthe
    process.
    Use
    the
    same
    linear
    extrapolation
    for
    all
    lifestages,
    unless
    have
    c hemical
    specific
    information
    on lifeages
    or
    populations
    Use
    framework
    in Cancer
    Guidelines
    to
    establish
    MOA(s)
    MOA
    sufficiently
    supported
    in animals?
    MOA
    can
    not
    be
    determined
    Yes
    MOA
    relevant
    to
    humans?
    No
    Yes
    Flag
    lifestage(s)
    orpopulation(s)
    that
    could
    be susceptibè
    (based
    on
    information
    about
    the specific
    MOA)
    for dose-response
    analysis.
    Determine
    extrapolation
    based
    on infomiat
    inn
    about
    specific
    MOA.
    Nonlinear
    Line
    ar, but
    nonmutagenic
    Linearitydueto
    mutagenicMOA
    V
    Suppèmental
    G.iidancefor
    Early-Life
    Expures
    Were
    chemical-specific
    data available
    Yes
    [vebp
    chemical-specific
    in MOA
    analysis
    to
    evaluate
    differences
    risk estimates
    incorporiting
    between
    adults
    and juveniles
    (more,
    lifestage
    susceptibility.
    ,orthe
    sume
    susceptibility)?
    No
    V
    Early- life
    suscept
    thility
    assumed.
    Apply
    age-
    dependent
    adist ment
    factors
    (ADAFs)
    as
    appropnateto
    develop
    risk
    estimates.
    1-22

    2.
    HAZARD
    ASSESSMENT
    2.1. OVERVIEW
    OF HAZARD
    ASSESSMENT
    AND
    CHARACTERIZATION
    2.1.1.
    Analyses
    of Data
    The purpose
    of
    hazard
    assessment
    is to
    review
    and
    evaluate
    data
    pertinent
    to two
    questions:
    (1)
    whether
    an
    agent
    may
    pose
    a
    carcinogenic
    hazard
    to human
    beings,
    and
    (2)
    under
    what
    circumstances
    an identified
    hazard
    may be
    expressed
    (NRC,
    1994). Hazard
    assessment
    involves
    analyses
    of a variety
    of
    data
    that may
    range
    from
    observations
    of
    tumor
    responses
    to
    analysis
    of
    structure-activity
    relationships
    (SARs).
    The
    purpose
    of
    the
    assessment
    is
    not simply
    to
    assemble
    these
    separate
    evaluations;
    its
    purpose
    is to construct
    a
    total
    analysis
    examining
    what
    the biological
    data reveal
    as a
    whole
    about carcinogenic
    effects
    and mode
    of
    action
    of the
    agent,
    and
    their
    implications
    for
    human
    hazard
    and dose-response
    evaluation.
    Conclusions
    are
    drawn
    from weight-of-evidence
    evaluations
    based on
    the combined
    strength
    and
    coherence
    of
    inferences
    appropriately
    drawn
    from
    all
    of
    the
    available
    information.
    To
    the
    extent
    that data
    permit,
    hazard
    assessment
    addresses
    the
    question
    of
    mode
    of
    action
    of an agent
    as both
    an
    initial
    step
    in
    identifying
    human
    hazard
    potential
    and as a
    component
    in
    considering
    appropriate
    approaches
    to
    dose-response
    assessment.
    The
    topics
    in this
    chapter
    include
    analysis
    of
    tumor
    data, both
    human
    and
    animal,
    and
    analysis
    of other
    key
    information
    about
    properties
    and effects
    that
    relate
    to carcinogenic
    potential.
    The
    chapter
    addresses
    how
    information
    can be
    used
    to evaluate
    potential
    modes
    of
    action.
    It also
    provides
    guidance
    on performing
    a
    weight
    of
    evidence
    evaluation.
    2.1.2.
    Presentation
    of
    Results
    Presentation
    of the
    results
    of
    hazard
    assessment
    should
    be informed
    by Agency
    guidance
    as discussed
    in
    Section
    2.6. The
    results
    are presented
    in a technical
    hazard
    characterization
    that
    serves
    as a
    support
    to later
    risk
    characterization.
    It
    includes:
    a summary
    of
    the
    evaluations
    of hazard
    data,
    the rationales
    for
    its
    conclusions,
    and
    2-1

    an explanation
    of the
    significant
    strengths
    or
    limitations
    of the
    conclusions.
    Another
    presentation
    feature
    is
    the
    use
    of
    a
    weight
    of evidence
    narrative
    that
    includes
    both
    a conclusion
    about
    the
    weight
    of
    evidence
    of
    carcinogenic
    potential
    and
    a summary
    of
    the
    data
    on which
    the conclusion
    rests.
    This
    narrative
    is a brief
    summary
    that
    in
    toto replaces
    the
    alphanumerical
    classification
    system
    used
    in
    EPA’s
    1986
    cancer
    guidelines
    (U.S.
    EPA,
    1986a).
    2.2.
    ANALYSIS
    OF
    TUMOR
    DATA
    Evidence
    of
    carcinogenicity
    comes
    from
    finding
    tumor
    increases
    in
    humans
    or
    laboratory
    animals
    exposed
    to
    a given
    agent
    or from
    finding
    tumors
    following
    exposure
    to structural
    analogues
    to
    the
    compound
    under
    review.
    The
    significance
    of observed
    or
    anticipated
    tumor
    effects
    is evaluated
    in reference
    to
    all the
    other
    key data
    on
    the agent.
    This
    section
    contains
    guidance
    for
    analyzing
    human
    and
    animal
    studies
    to
    decide
    whether
    there
    is an
    association
    between
    exposure
    to
    an
    agent
    or a structural
    analogue
    and
    occurrence
    of
    tumors.
    Note
    that
    the
    use
    of the
    term
    “tumor”
    in
    these
    cancer
    guidelines
    is defined
    as malignant
    neoplasms
    or
    a
    combination of
    malignant
    and corresponding
    benign
    neoplasms.
    Observation of
    only
    benign
    neoplasia
    may
    or
    may
    not have
    significance
    for
    evaluation
    under
    these
    cancer
    guidelines.
    Benign
    tumors
    that
    are
    not
    observed
    to
    progress
    to malignancy
    are assessed on a case-by-case
    basis.
    There
    is
    a range
    of
    possibilities for
    their
    overall
    significance.
    They
    may
    deserve
    attention
    because
    they
    are
    serious
    health
    problems
    even
    though
    they are
    not
    malignant;
    for
    instance,
    benign
    tumors
    may
    be
    a health
    risk
    because
    of their
    effect
    on
    the
    function of a target
    tissue
    such
    as
    the
    brain.
    They
    may
    be
    significant
    indicators
    of
    the
    need
    for
    further
    testing
    of an
    agent
    if they
    are
    observed
    in
    a
    short-
    term
    test protocol,
    or
    such
    an
    observation
    may
    add
    to the
    overall
    weight
    of evidence
    if the
    same
    agent
    causes
    malignancies
    in a
    long-term
    study.
    Knowledge of
    the mode
    of action
    associated
    with
    a
    benign
    tumor
    response
    may
    aid
    in the
    interpretation
    of
    other
    tumor
    responses
    associated
    with
    the
    same
    agent.
    In other
    cases,
    observation of
    a
    benign
    tumor
    response
    alone
    may have
    no
    significant
    health
    hazard
    implications
    when
    other
    sources
    of
    evidence
    show
    no
    suggestion
    of
    carcinogenicity.
    2-2

    2.2.1.
    Human
    Data
    Human
    data
    may
    come
    from
    epidemiologic
    studies
    or
    case
    reports.
    (Clinical
    human
    studies,
    which
    involve
    intentional
    exposures
    to
    substances,
    may
    provide
    toxicokinetic
    data,
    but
    generally
    not
    data
    on
    carcinogenicity.)
    The
    most
    common
    sources
    of
    human
    data
    for
    cancer
    risk
    assessment
    are
    epidemiologic
    investigations.
    Epidemiology
    is
    the
    study
    of the
    distribution
    of
    disease
    in
    human
    populations
    and
    the
    factors
    that
    may
    influence
    that
    distribution.
    The
    goals
    of
    cancer
    epidemiology
    are
    to
    identify
    distribution
    of
    cancer
    risk
    and determine
    the
    extent
    to
    which
    the
    risk
    can
    be attributed
    causally
    to
    specific
    exposures
    to
    exogenous
    or
    endogenous
    factors
    (see
    Centers
    for
    Disease
    Control
    and Prevention
    [CDC,
    2004]).
    Epidemiologic
    data
    are
    extremely
    valuable
    in risk
    assessment
    because
    they
    provide
    direct
    evidence
    on whether
    a substance
    is
    likely
    to
    produce
    cancer
    in
    humans,
    thereby
    avoiding
    issues
    such
    as:
    species-to-species
    inference,
    extrapolation
    to
    exposures
    relevant
    to
    people,
    effects
    of concomitant
    exposures
    due to
    lifestyles.
    Thus,
    epidemiologic
    studies
    typically
    evaluate
    agents
    under
    more
    relevant
    conditions.
    When
    human
    data
    of
    high
    quality
    and
    adequate
    statistical
    power
    are
    available,
    they
    are
    generally
    preferable
    over animal
    data
    and
    should
    be given
    greater
    weight
    in hazard
    characterization
    and
    dose-response
    assessment,
    although
    both
    can
    be used.
    Null
    results
    from
    epidemiologic
    studies
    alone
    generally
    do not
    prove
    the absence
    of
    carcinogenic effects
    because
    such
    results
    can
    arise
    either
    from
    an
    agent
    being
    truly
    not
    carcinogenic or from
    other
    factors
    such
    as:
    inadequate
    statistical
    power,
    inadequate
    study
    design,
    imprecise
    estimates,
    or
    confounding
    factors.
    Moreover,
    null
    results
    from
    a
    well-designed
    and
    well-conducted
    epidemiologic
    study
    that
    contains
    usable
    exposure
    data
    can
    help
    to
    define
    upper
    limits
    for
    the
    estimated
    dose
    of concern
    for human
    exposure
    in
    cases
    where
    the
    overall
    weight
    of
    the
    evidence
    indicates
    that
    the agent
    is
    potentially
    carcinogenic
    in
    humans.
    Furthermore,
    data
    from
    a
    well
    designed
    and
    well
    conducted
    epidemiologic
    study
    that
    does
    not
    show
    positive
    results,
    in
    conjunction
    with
    compelling
    mechanistic
    information,
    can
    lend
    support
    to a
    conclusion
    that
    animal
    responses
    may
    not
    be predictive
    of a
    human
    cancer
    hazard.
    Epidemiology
    can
    also
    complement
    experimental
    evidence
    in
    corroborating
    or
    clarifying
    the
    carcinogenic
    potential
    of
    the agent
    in
    question.
    For
    example,
    epidemiologic
    studies
    that
    show
    elevated
    cancer
    risk
    for
    tumor
    sites
    corresponding
    to
    those
    at
    which
    laboratory
    animals
    2-3

    experience
    increased
    tumor
    incidence
    can
    strengthen
    the
    weight
    of
    evidence
    of
    human
    carcinogenicity.
    Furthermore,
    biochemical
    or molecular
    epidemiology
    may
    help
    improve
    understanding
    of the
    mechanisms
    of
    human
    carcinogenesis.
    2.2.1.1.
    Assessment
    of
    Evidence
    of
    carcinogenicity
    front
    Human
    Data
    All
    studies
    that
    are considered
    to
    be of
    acceptable
    quality,
    whether
    yielding
    positive
    or
    null
    results,
    or
    even
    suggesting
    protective
    carcinogenic
    effects,
    should
    be
    considered
    in
    assessing
    the
    totality
    of
    the
    human
    evidence.
    Conclusions
    about
    the
    overall
    evidence
    for
    carcinogenicity
    from
    available
    studies
    in
    humans
    should
    be summarized
    along
    with
    a
    discussion
    of
    uncertainties
    and
    gaps
    in
    knowledge.
    Conclusions
    regarding
    the
    strength
    of the
    evidence
    for positive
    or
    negative
    associations
    observed,
    as well
    as evidence
    supporting
    judgments
    of
    causality,
    should
    be
    clearly
    described. In assessing
    the human
    data
    within
    the
    overall
    weight
    of
    evidence,
    determination about
    the
    strength
    of the
    epidemiologic
    evidence
    should
    clearly
    identify
    the
    degree
    to
    which
    the
    observed
    associations
    may
    be
    explained
    by other
    factors,
    including
    bias
    or
    confounding.
    Characteristics that
    are generally
    desirable
    in
    epidemiologic
    studies
    include
    (1)
    clear
    articulation
    of
    study
    objectives
    or hypothesis;
    (2) proper
    selection
    and
    characterization
    of
    comparison
    groups
    (exposed
    and
    unexposed
    groups
    or
    case and
    control
    groups);
    (3)
    adequate
    characterization of
    exposure;
    (4)
    sufficient
    length
    of
    follow-up
    for disease
    occunence;
    (5)
    valid
    ascertainment
    of
    the
    causes
    of
    cancer
    morbidity
    and
    mortality;
    (6)
    proper
    consideration
    of bias
    and
    confounding
    factors;
    (7)
    adequate
    sample
    size
    to
    detect
    an
    effect;
    (8) clear,
    well-documented,
    and appropriate methodology
    for
    data
    collection
    and
    analysis;
    (9)
    adequate
    response
    rate
    and
    methodology for handling
    missing
    data;
    and
    (10) complete
    and
    clear
    documentation
    of
    results.
    No
    single
    criterion
    determines
    the
    overall
    adequacy
    of
    a study.
    Practical
    and
    resource
    constraints
    may limit
    the
    ability
    to
    address
    all of
    these
    characteristics
    in
    a study.
    The
    risk assessor
    is
    encouraged
    to
    consider how
    the limitations
    of
    the
    available
    studies
    might
    influence
    the
    conclusions.
    While
    positive
    biases
    may be
    due,
    for example,
    to a
    healthy
    worker
    effect,
    it is
    also
    important
    to
    consider
    negative
    biases,
    for
    example,
    workers
    who
    may
    leave
    the workforce
    due
    to
    illness
    caused
    either
    by
    high
    exposures
    to
    the
    agent
    or
    to effects
    of confounders
    such
    as
    smoking.
    2-4

    The
    following
    discussions
    highlight
    the major
    factors
    included
    in
    an
    analysis
    of
    epidemiologic
    studies.
    2.2.1.2.
    Types
    ofStudies
    The
    major
    types
    of cancer
    epidemiologic
    study
    designs
    used
    for examining
    environmental
    causes
    of
    cancer
    are analytical
    studies
    and descriptive
    studies.
    Each
    study
    type has
    well-known
    strengths
    and
    weaknesses
    that
    affect
    interpretation
    of results,
    as
    summarized
    below
    (Lilienfeld
    and
    Lilienfeld,
    1979;
    Mausner
    and
    Kramer,
    1985;
    Kelsey
    et al.,
    1996;
    Rothman
    and
    Greenland,
    1998).
    Analytical
    epidemiologic
    studies,
    which
    include
    case-control
    and cohort
    designs,
    are
    generally
    relied
    on
    for identifring
    a causal
    association
    between
    human
    exposure
    and
    adverse
    health
    effects.
    In
    case-control
    studies,
    groups
    of
    individuals
    with
    (cases)
    and
    without
    (controls)
    a
    particular
    disease
    are identified
    and
    compared
    to
    determine
    differences
    in exposure.
    In cohort
    studies,
    a group
    of
    “exposed”
    and
    “nonexposed”
    individuals
    are
    identified
    and studied
    over
    time
    to
    determine
    differences
    in
    disease
    occurrence.
    Cohort
    studies
    can
    be
    performed
    either
    prospectively
    or
    retrospectively
    from historical
    records.
    The
    type of
    study
    chosen
    may
    depend
    on
    the
    hypothesis
    to be
    evaluated.
    For
    example,
    case-control
    studies
    may
    be
    more
    appropriate
    for
    rare cancers
    while
    cohort
    studies
    may
    be
    more
    appropriate
    for
    more
    commonly
    occurring
    cancers.
    On
    the
    other
    hand, descriptive
    epidemiologic
    studies
    examine
    symptom
    or disease
    rates
    among
    populations
    in relation
    to
    personal
    characteristics
    such
    as age,
    gender,
    race,
    and temporal
    or environmental
    conditions.
    Descriptive
    studies
    are most
    frequently
    used
    to
    generate
    hypotheses
    about
    exposure
    factors,
    but
    subsequent
    analytical
    designs
    are
    necessary
    to
    infer
    causality.
    For
    example,
    cross-sectional
    designs
    might
    be
    used to
    compare
    the
    prevalence
    of
    cancer
    between
    areas
    near
    and far
    from
    a Superfund
    site.
    However,
    in
    studies
    where
    exposure
    and
    disease
    information
    applies
    only to
    the
    current
    conditions,
    it is
    not possible
    to infer
    that
    the
    exposure
    actually
    caused
    the
    disease.
    Therefore,
    these
    studies
    are used
    to identify
    patterns
    or
    trends
    in
    disease
    occurrence
    over
    time
    or in different
    geographical
    locations,
    but
    typical
    2-5

    limitations
    in
    the
    characterization
    of
    populations
    in
    these
    studies
    make
    it difficult
    to
    infer
    the
    causal
    agent
    or
    degree
    of
    exposure.
    Case
    reports
    describe
    a particular
    effect
    in
    an individual
    or
    group
    of individuals
    who
    were
    exposed
    to
    a
    substance.
    These
    reports
    are
    often
    anecdotal
    or highly
    selective
    in
    nature
    and
    generally
    are
    of
    limited
    use
    for hazard
    assessment.
    Specifically,
    cancer
    causality
    can
    rarely
    be
    infened
    from
    case
    reports
    alone.
    Investigative
    follow-up
    may
    or
    may
    not accompany
    such
    reports.
    For
    cancer,
    the
    most
    common
    types
    of
    case
    series
    are associated
    with
    occupational
    and
    childhood
    exposures.
    Case
    reports
    can
    be
    particularly
    valuable
    for
    identifying
    unique
    features,
    such
    as
    an
    association
    with
    an uncommon
    tumor
    (e.g.,
    inhalation
    of
    vinyl
    chloride
    and
    hepatic
    angiosarcoma
    in workers
    or ingestion
    of
    diethylstilbestrol
    by
    mothers
    and clear-cell
    carcinoma
    of
    the vagina
    in
    offspring).
    2.2.1.3. Exposure
    Issues.
    For
    epidemiologic data
    to be useful
    in
    determining
    whether
    there
    is
    an association
    between
    health
    effects
    and
    exposure
    to
    an
    agent,
    there
    should
    be
    adequate
    characterization
    of
    exposure information.
    In general,
    greater
    weight
    should
    be
    given
    to studies
    with more
    precise
    and
    specific
    exposure
    estimates.
    Questions
    to address
    about
    exposure
    are:
    What
    can
    one
    reliably
    conclude
    about
    the
    exposure
    parameters including
    (but
    not limited
    to) the
    level,
    duration,
    route,
    and
    frequency
    of
    exposure
    of
    individuals
    in one
    population
    as compared
    with
    another?
    How
    sensitive
    are
    study
    results
    to
    uncertainties
    in
    these
    parameters?
    Actual
    exposure
    measurements
    are not
    available
    for
    many
    retrospective
    studies.
    Therefore,
    sunogates
    are
    often
    used
    to reconstruct
    exposure
    parameters.
    These
    may
    involve
    attributing
    exposures
    to job
    classifications
    in
    a
    workplace
    or
    to broader
    occupational
    or
    geographic
    groupings.
    Use
    of
    surrogates
    carries
    a potential
    for misclassification,
    i.e.,
    individuals
    may
    be
    placed
    in an
    incorrect
    exposure
    group.
    Misclassification
    generally
    leads
    to
    reduced
    ability
    of a
    study
    to
    detect
    differences
    between
    study
    and
    referent
    populations.
    When
    either
    current
    or
    historical
    monitoring
    data
    are available,
    the
    exposure
    evaluation
    includes
    consideration
    of
    the
    error
    bounds
    of the
    monitoring
    and
    analytic
    methods
    and
    whether
    2-6

    the data
    are
    from
    routine
    or
    accidental
    exposures.
    The potential
    for misclassification
    and
    for
    measurement
    errors
    is amenable
    to both
    qualitative
    and
    quantitative
    analysis.
    These
    are
    essential
    analyses
    for
    judging
    a
    study’s
    results,
    because
    exposure
    estimation
    is the
    most
    critical
    part of
    a
    retrospective
    study.
    2.2.1.4.
    Biological
    Markers.
    Biological
    markers
    potentially
    offer
    excellent
    measures
    of
    exposure
    (Hulka
    and
    Margolin,
    1992;
    Peto
    and
    Darby,
    1994).
    In
    some
    cases,
    molecular
    or cellular
    effects
    (e.g.,
    DNA
    or protein
    adducts,
    mutation,
    chromosomal
    aberrations,
    levels
    of
    thyroid-stimulating
    hormone)
    can be
    measured
    in blood,
    body
    fluids, cells,
    and
    tissues
    to
    serve
    as
    biomarkers
    of exposure
    in
    humans
    and animals
    (Callemen
    et al.,
    1978;
    Birner
    et
    al., 1990).
    As
    such, they
    can
    act
    as an
    internal
    surrogate
    measure
    of
    chemical
    dose,
    representing,
    as appropriate,
    either
    recent
    exposure
    (e.g.,
    serum
    concentration)
    or
    accumulated
    exposure
    over
    some
    period
    (e.g.,
    hemoglobin
    adducts).
    Validated
    markers
    of
    exposure
    such
    as
    alkylated
    hemoglobin
    from
    exposure
    to ethylene
    oxide
    (Van
    Sittert
    et
    al., 1985)
    or
    urinary
    arsenic
    (Enterline
    et al.,
    1987)
    can improve
    estimates
    of dose
    over the
    relevant
    time
    periods
    for
    the markers.
    Markers
    closely
    identified
    with
    effects
    promise
    to
    greatly
    increase
    the ability
    of
    studies
    to distinguish
    real effects
    from
    bias
    at
    low
    levels
    of relative
    risk
    between
    populations
    (Taylor
    et
    al.,
    1994; Biggs
    et al.,
    1993)
    and to
    resolve
    problems
    of
    confounding
    risk
    factors.
    However,
    when
    using
    molecular
    or cellular
    effects
    as biomarkers
    of
    exposure,
    since
    many
    of these
    changes
    are often
    not
    specific
    to just
    one type
    of
    exposure,
    it is
    important
    to be
    aware
    that
    changes
    may be
    due
    to
    exposures
    unrelated
    to the exposure
    of interest
    and attention
    must
    be
    paid
    to
    controlling
    for potential
    confounders.
    Biochemical
    or
    molecular
    epidemiologic
    studies
    may
    use biological
    markers
    of
    effect
    as
    indicators
    of
    disease
    or its precursors.
    The
    application
    of
    techniques
    for measuring
    cellular
    and
    molecular
    alterations
    due
    to exposure
    to specific
    environmental
    agents
    may
    allow
    conclusions
    to
    be
    drawn about
    the mechanisms of
    carcinogenesis
    (see
    section
    2.4 for
    more
    information
    on this
    topic).
    2-7

    2.2.1.5.
    Coifounding Factors.
    Control
    for potential
    confounding
    factors
    is
    an
    important
    consideration
    in
    the
    evaluation
    of
    the
    design
    and
    in the
    analysis
    of
    observational
    epidemiologic
    studies.
    A
    confounder
    is
    a
    variable
    that
    is related
    to
    both
    the
    health
    outcome
    of
    concern
    (cancer)
    and exposure.
    Common
    examples
    include
    age, socioeconomic
    status,
    smoking
    habits,
    and
    diet.
    For
    instance,
    if older
    people
    are
    more
    likely
    to
    be
    exposed
    to
    a given
    contaminant
    as well
    as
    more
    likely
    to
    have
    cancer
    because
    of
    their
    age,
    age
    is considered
    a confounder.
    Adjustment
    for
    potentially
    confounding
    factors
    (from
    a statistical
    as contrasted with
    an
    epidemiologic
    point
    of
    view)
    can
    occur
    either
    in
    the design
    of
    the
    study
    (e.g.,
    individual
    or group
    matching
    on
    critical
    factors)
    or in
    the
    statistical
    analysis
    of
    the
    results
    (stratification
    or
    direct
    or indirect
    adjustment).
    Direct
    adjustment
    in
    the
    statistical
    analysis
    may
    not
    be possible
    owing
    to
    the presentation
    of
    the
    data
    or because
    needed
    information
    was
    not
    collected
    during
    the
    study.
    In
    this case,
    indirect
    comparisons
    may
    be
    possible.
    For
    example,
    in
    the
    absence
    of
    data
    on smoking
    status
    among
    individuals
    in
    the
    study
    population, an
    examination of the
    possible
    contribution
    of
    cigarette
    smoking
    to increased
    lung
    cancer
    risk
    may
    be based
    on information
    from
    other
    sources,
    such
    as
    the American
    Cancer
    Society’s
    longitudinal studies
    (Hammand,
    1966;
    Garfinkel
    and Silverberg,
    1991).
    The
    effectiveness
    of
    adjustments
    contributes
    to the
    ability
    to
    draw
    inferences
    from
    a
    study.
    Different
    studies
    involving exposure
    to an
    agent
    may
    have
    different
    confounding
    factors.
    If consistent
    increases
    in
    cancer
    risk
    are observed
    across
    a collection
    of studies
    with
    different
    confounding
    factors,
    the
    inference
    that
    the
    agent
    under
    investigation
    was
    the etiologic
    factor
    is
    strengthened.
    There
    may
    also
    be
    instances
    where
    the
    agent
    of
    interest
    is a risk
    factor
    in
    conjunction
    with
    another
    agent.
    For
    instance,
    interaction
    as
    well
    as effect-measure
    modification
    are
    sometimes
    construed
    to
    be
    confounding,
    but
    they
    are different
    than
    confounding.
    Interaction
    is
    described
    as
    a situation
    in
    which
    two
    or
    more
    risk
    factors
    modify
    the
    effect
    of
    each
    other
    with
    regard
    to
    the
    occurrence
    of
    a
    given
    effect.
    This
    phenomenon
    is
    sometimes
    described
    as effect-measure
    modification or
    heterogeneity
    of
    effect
    (Szklo
    and
    Nieto,
    2000).
    Effect-measure
    modification
    refers
    to
    variation
    in
    the
    magnitude
    of measure
    exposure
    effect
    across
    levels
    of
    another
    variable
    (Rothman
    and
    Greenland,
    1998).
    The
    variable
    across
    which
    the
    effect
    measure
    varies
    and
    is
    2-8

    called
    an
    effect
    mod/Ier
    (e.g.,
    hepatitis
    virus
    B and
    afiatoxin
    in hepatic
    cancer).
    Interaction,
    on
    the
    other
    hand,
    means
    effect
    of
    the exposure
    on
    the
    outcome
    differs,
    depending
    on
    the
    presence
    of another
    variable
    (the
    effect
    modifier).
    When
    the
    effect
    of the
    exposure
    of interest
    is
    accentuated
    by
    another
    variable,
    it
    is
    said
    to
    be
    synergistic
    interaction.
    Synergistic
    interaction
    can
    be
    additive
    (e.g.,
    hepatitis
    virus
    B and
    aflatoxin
    in
    hepatic
    cancer)
    or multiplicative
    (e.g.,
    asbestos
    and
    smoking
    in lung
    cancer).
    If the
    effect
    of
    exposure
    is diminished
    or
    eliminated
    by
    another
    variable,
    it
    said
    to
    be antagonistic
    interaction
    (e.g.,
    intake
    of vitamin
    E and
    lower
    occurrence
    of
    lung
    cancer).
    2.2.1.6.
    Statistical
    Considerations.
    The
    analysis
    should
    apply
    appropriate
    statistical
    methods
    to ascertain
    whether
    the
    observed
    association
    between
    exposure
    and effects
    would
    be expected
    by
    chance.
    A
    description
    of
    the
    method
    or
    methods
    used
    should
    include
    the
    reasons
    for
    their
    selection.
    Statistical
    analyses
    of
    the
    bias,
    confounding, and interaction
    are
    part
    of
    addressing
    the
    significance
    of
    an
    association
    and
    the
    power
    of
    a study
    to
    detect
    an
    effect.
    The
    analysis
    augments
    examination
    of the
    results
    for
    the
    whole
    population
    with
    exploration
    of the
    results
    for
    groups
    with
    comparatively
    greater
    exposure
    or time
    since
    first
    exposure. This
    may
    support
    identifying
    an association
    or
    establishing
    a
    dose-response
    trend.
    When
    studies
    show
    no
    association,
    such
    exploration
    may
    apply
    to
    determining
    an
    upper
    limit
    on
    potential
    human
    risk
    for
    consideration
    alongside
    results
    of
    animal
    tumor
    effects
    studies.
    2.2.1.6.1.
    Likelihood
    of
    observing
    an
    effect.
    The
    power
    of
    a
    study
    — the
    likelihood
    of
    observing
    an effect
    if one
    exists
    — increases
    with
    sample
    size,
    i.e.,
    the number
    of subjects
    studied
    from
    a
    population. (For
    example,
    a quadrupling
    of
    a background
    rate
    in the
    1 per
    10,000
    range
    would
    require
    more
    subjects
    who
    have
    experienced
    greater
    or
    longer
    exposure
    or
    lengthier
    follow-up,
    than a
    doubling
    of
    a
    background
    rate in
    the 1
    per 100
    range.)
    If the
    size
    of the
    effect
    is
    expected
    to
    be
    very
    small
    at
    low
    doses,
    higher
    doses
    or longer
    durations
    of
    exposure
    may be
    needed
    to
    have
    an
    appreciable likelihood
    of
    observing
    an
    effect
    with
    a
    given
    sample
    size.
    Because
    of the
    often
    long
    latency
    period
    in cancer
    development,
    the
    likelihood
    of
    observing
    an effect
    also
    2-9

    depends
    on whether
    adequate
    time
    has
    elapsed
    since
    exposure
    began
    for
    effects
    to
    occur.
    Since
    the
    design of
    the study
    and
    the
    choice
    of analysis,
    as well
    as the design
    level
    of certainty
    in the
    results
    and
    the
    magnitude
    of
    response
    in
    an unexposed
    population
    also
    affect
    the
    likelihood
    of
    observing
    an
    effect,
    it is important
    to
    carefully
    interpret
    the
    absence
    of
    an observed
    effect.
    A
    unique
    feature
    that
    can be
    ascribed
    to the
    effects
    of a particular
    agent
    (such
    as a tumor
    type that
    is
    seen only
    rarely
    in the
    absence
    of
    the
    agent) can
    increase
    sensitivity
    by
    permitting
    separation
    of
    bias and
    confounding
    factors
    from
    real
    effects.
    Similarly,
    a biomarker
    particular
    to
    the agent
    can
    permit
    these
    distinctions.
    Statistical
    re-analyses
    of
    data,
    particularly
    an
    examination
    of
    different
    exposure
    indices,
    can
    give
    insight
    into potential
    exposure-response
    relationships.
    These
    are
    all
    factors
    to explore
    in
    statistical
    analysis
    of the
    data.
    2.2.1.6.2.
    Sampling
    and
    other
    bias issues.
    When
    comparing
    cases
    and controls
    or
    exposed
    and
    non-exposed
    populations,
    it
    would
    be
    preferable
    for
    the
    two populations
    to differ
    only
    in
    exposure
    to the
    agent
    in
    question.
    Because
    this
    is
    seldom
    the
    case,
    it
    is important
    to identif’
    sources
    of sampling
    and other
    potential
    biases
    inherent
    in
    a study
    design
    or data
    collection
    methods.
    Bias
    is a
    systematic
    error.
    In
    epidemiologic
    studies,
    bias
    can
    occur
    in
    the
    selection
    of
    cases
    and
    controls
    or exposed
    and
    non-exposed
    populations,
    as
    well
    as the
    follow up
    of
    the
    groups,
    or the
    classification
    of
    disease
    or exposure.
    The
    size
    of the
    risks
    observed
    can
    be
    affected
    by
    noncomparability between
    populations
    of
    factors
    such as
    general
    health,
    diet,
    lifestyle,
    or
    geographic
    location;
    differences
    in
    the
    way
    case
    and control
    individuals
    recall
    past
    events;
    differences
    in data
    collection
    that
    result
    in unequal
    ascertainment
    of health
    effects
    in
    the
    populations;
    and unequal
    follow-up
    of
    individuals
    (Rothman
    and
    Greenland,
    1998).
    Other
    factors
    worth
    consideration
    can
    be
    inherent
    in the
    available
    cohorts,
    e.g., use
    of
    occupational
    studies
    (the
    healthy
    worker
    effect),
    absence
    of
    one
    sex,
    or
    limitations
    in sample
    size for
    one
    or
    more
    ethnicities.
    The
    mere
    presence
    of
    biases
    does
    not invalidate
    a
    study,
    but
    should
    be reflected
    in the
    judgment
    of its
    strengths
    or
    weaknesses.
    Acceptance
    of
    studies
    for assessment
    depends
    on
    identifjing
    their
    sources
    of
    bias
    and the
    possible
    effects
    on
    study results.
    2-10

    2.2.1.6.3.
    Combining
    statistical
    evidence
    across
    studies.
    Meta-analysis
    is
    a means
    of
    integrating
    the
    results
    of multiple
    studies
    of similar
    health
    effects and
    risk
    factors.
    This
    technique
    is particularly
    useful
    when
    various
    studies
    yield
    varying
    degrees
    of risk
    or even
    conflicting
    associations
    (negative
    and
    positive).
    It is intended
    to introduce
    consistency
    and
    comprehensiveness
    into
    what
    otherwise
    might
    be
    a more
    subjective
    review
    of the
    literature.
    The
    value
    of such
    an
    analysis
    is dependent
    upon
    a
    systematic
    review
    of
    the literature
    that
    uses
    transparent
    criteria
    of inclusion
    and
    exclusion.
    In
    interpreting
    such
    analyses,
    it is important
    to
    consider
    the
    effects
    of differences
    in study
    quality,
    as
    well
    as the
    effect
    of
    publication
    bias.
    Meta-analysis
    may
    not
    be
    advantageous
    in
    some
    circumstances.
    These
    include
    when
    the
    relationship
    between
    exposure
    and
    disease
    is obvious
    from
    the individual
    studies;
    when there
    are
    only
    a few studies
    of the
    key
    health
    outcomes;
    when
    there
    is insufficient
    information
    from
    available
    studies
    related
    to
    disease,
    risk estimate,
    or exposure
    classification
    to insure
    comparability;
    or
    when
    there are
    substantial
    confounding
    or
    other
    biases
    that
    cannot
    be adjusted
    for in
    the
    analysis
    (Blair
    et
    al., 1995;
    Greenland,
    1987;
    Peto,
    1992).
    2.2.1.7.
    Evidence
    for
    Causality
    Determining
    whether
    an observed
    association
    (risk)
    is
    causal rather
    than
    spurious
    involves
    consideration
    of
    a
    number
    of factors.
    Sir
    Bradford
    Hill
    (Hill,
    1965)
    developed
    a set
    of
    guidelines
    for
    evaluating
    epidemiologic
    associations
    that can
    be
    used
    in
    conjunction
    with
    the
    discussion
    of
    causality
    such
    as the
    2004
    Surgeon
    General’s
    report
    on
    smoking
    (CDC,
    2004)
    and
    in
    other
    documents
    (e.g.,
    Rothman
    and Greenland
    1998;
    IPCS,
    1999)
    . The
    critical
    assessment
    of epidemiologic evidence
    is conceptually
    based
    upon
    consideration
    of salient
    aspects
    of
    the
    evidence
    of
    associations
    so
    as to
    reach
    fundamental
    judgments
    as
    to the likely
    causal significance
    of the observed
    associations.
    In
    so
    doing,
    it is appropriate
    to draw
    from
    those
    aspects
    initially
    presented
    in
    Hill’s
    classic
    monograph
    (Hill,
    1965)
    and
    widely
    used
    by the scientific
    community
    in
    conducting
    such
    evidence-based
    reviews.
    A
    number
    of
    these aspects
    are
    judged
    to be
    particularly
    salient
    in evaluating
    the
    body
    of evidence
    available
    in this
    review,
    including
    the
    aspects
    described
    by
    Hill
    as strength,
    experiment,
    consistency,
    plausibility,
    and
    coherence.
    Other
    aspects
    identified
    by Hill,
    including
    temporality
    and
    biological
    gradient,
    are
    also relevant
    and
    2-11

    considered here
    (e.g.,
    in
    characterizing
    lag
    structures
    and
    concentration-response
    relationships),
    but
    are
    more
    directly
    addressed
    in
    the
    design
    and
    analyses
    of the
    individual
    epidemiologic
    studies
    included
    in
    this
    assessment.
    As discussed
    below,
    these
    salient
    aspects
    are
    interrelated
    and
    considered
    throughout
    the
    evaluation
    of
    the
    epidemiologic
    evidence
    generally
    reflected
    in
    the
    integrative
    synthesis
    of
    the mode
    of
    action
    framework.
    The
    general
    evaluation
    of
    the
    strength
    of
    the epidemiological
    evidence
    reflects
    consideration
    not only
    of
    the magnitude
    of
    reported
    effects
    estimates
    and
    their statistical
    significance,
    but also
    of
    the precision
    of
    the effects
    estimates
    and
    the
    robustness
    of the
    effects
    associations.
    Consideration
    of the
    robustness
    of
    the associations
    takes
    into
    account
    a
    number
    of
    factors,
    including
    in
    particular
    the
    impact
    of alternative
    models
    and
    model
    specifications
    and
    potential
    confounding factors,
    as
    well
    issues
    related
    to the
    consequences
    of
    measurement
    error.
    Consideration
    of
    the consistency
    of
    the
    effects
    associations
    involves
    looking
    across
    the
    results
    of
    studies
    conducted
    by
    different
    investigators
    in different
    places
    and
    times.
    Particular
    weight
    may
    be
    given,
    consistent
    with
    Hill’s
    views,
    to
    the
    presence
    of
    “similar
    results
    reached
    in
    quite
    different
    ways,
    e.g.,
    prospectively
    and
    retrospectively”
    (Hill,
    1965).
    Looking
    beyond
    the
    epidemiological
    evidence,
    evaluation
    of the
    biological
    plausibility
    of the
    associations
    observed
    in
    epidemiologic
    studies
    reflects
    consideration
    of both
    exposure-related
    factors
    and
    toxicological
    evidence
    relevant
    to
    identification
    of
    potential
    modes
    of
    action
    (MOAs).
    Similarly,
    consideration
    of the
    coherence
    of health
    effects
    associations
    reported
    in
    the epidemiologic
    literature
    reflects
    broad
    consideration
    of
    information pertaining
    to the
    nature
    of the
    biological
    markers
    evaluated
    in
    toxicologic
    and
    epidemiologic
    studies.
    In
    identifying
    these
    aspects
    as being
    particularly
    salient
    in
    this
    assessment,
    it
    is
    also
    important
    to
    recognize
    that
    no
    one
    aspect
    is
    either
    necessary
    or
    sufficient
    for
    drawing
    inferences
    of
    causality.
    As
    Hill
    (1965)
    emphasized:
    “None
    of my
    nine
    viewpoints
    can
    bring
    indisputable
    evidence
    for
    or
    against
    the
    cause-and-effect
    hypothesis
    and none
    can
    be
    required
    as a sine
    qua non.
    What
    they
    can
    do,
    with
    greater
    or less
    strength,
    is to
    help us
    to
    make
    up our
    minds
    on
    the
    fundamental
    question
    is
    there
    any
    other
    way
    of explaining
    the set
    of
    facts
    2-12

    before
    us, is there
    any
    other answer
    equally,
    or more,
    likely
    than
    cause
    and
    effect?”
    While
    these
    aspects
    frame
    considerations
    weighed
    in
    assessing
    the epidemiologic
    evidence,
    they
    do not
    lend
    themselves
    to being
    considered
    in
    terms
    of simple
    formulas
    or
    hard-and-fast
    rules
    of
    evidence
    leading
    to answers
    about
    causality
    (Hill, 1965).
    One, for
    example,
    cannot
    simply
    count
    up
    the numbers
    of studies
    reporting
    statistically
    significant
    results
    or statistically
    non-significant
    results
    for
    carcinogenesis
    and related
    MOAs
    and
    reach
    credible
    conclusions
    about
    the
    relative
    strength
    of the
    evidence
    and the
    likelihood
    of causality.
    Rather,
    these
    important
    considerations
    are taken
    into
    account
    throughout
    the
    assessment
    with
    a goal
    of producing
    an objective
    appraisal
    of
    the evidence
    (informed
    by
    peer and
    public
    comment
    and
    advice),
    which
    includes
    the
    weighing
    of
    alternative
    views
    on
    controversial
    issues.
    Thus,
    although
    these
    guidelines
    have
    become
    known
    as “causal
    criteria,”
    it is
    important
    to
    note
    that they
    cannot
    be
    used as
    a strictly
    quantitative
    checklist.
    Rather,
    these
    “criteria”
    should
    be used
    to determine
    the strength
    of the
    evidence
    for
    concluding
    causality.
    In
    particular,
    the absence
    of
    one
    or
    more
    of the
    “criteria”
    does
    not
    automatically
    exclude
    a study
    from
    consideration
    (e.g., see
    discussion
    in
    CDC,
    2004).
    The
    list below
    has
    been
    adapted
    from
    Hill’s
    guidelines
    as an
    aid in judging
    causality.
    (a) Consistency
    of
    the observed
    association.
    An
    inference
    of
    causality
    is strengthened
    when
    a pattern
    of elevated
    risks is
    observed
    across
    several
    independent
    studies.
    The
    reproducibility
    of
    findings
    constitutes
    one
    of the
    strongest
    arguments
    for
    causality.
    If
    there
    are
    discordant
    results
    among
    investigations,
    possible
    reasons
    such
    as differences
    in
    exposure,
    confounding
    factors,
    and
    the
    power
    of
    the study
    are
    considered.
    (b)
    Strength
    of
    the observed
    association.
    The
    finding
    of
    large,
    precise
    risks
    increases
    confidence
    that
    the
    association
    is
    not
    likely
    due
    to
    chance,
    bias,
    or other
    factors.
    A modest
    risk,
    however,
    does
    not preclude
    a
    causal
    association
    and
    may
    reflect
    a lower
    level
    of exposure,
    an
    agent
    of lower
    potency,
    or
    a
    common
    disease
    with
    a
    high background
    level.
    (c) Specificity
    of
    the observed
    association.
    As
    originally
    intended,
    this refers
    to
    increased
    inference
    of causality
    if
    one
    cause is
    associated
    with
    a single
    effect
    or disease
    (Hill,
    1965).
    Based on
    our current
    understanding
    that many
    agents
    cause
    cancer
    at
    multiple
    sites,
    and
    2-13

    many
    cancers
    have
    multiple
    causes,
    this
    is
    now
    considered
    one
    of
    the
    weaker
    guidelines
    for
    causality.
    Thus,
    although
    the
    presence of
    specificity
    may
    support
    causality,
    its absence
    does
    not
    exclude
    it.
    (d)
    Temporal
    relationship
    ofthe
    observed
    association.
    A
    causal
    interpretation
    is
    strengthened
    when
    exposure
    is
    known
    to
    precede
    development
    of the
    disease.
    Because
    a latent
    period
    of up
    to
    20
    years
    or
    longer
    is
    often
    associated
    with
    cancer
    development
    in adults,
    the
    study
    should
    consider
    whether
    exposures
    occurred
    sufficiently
    long
    ago
    to produce
    an
    effect
    at
    the
    time
    the
    cancer
    is
    assessed.
    This
    is
    among
    the strongest
    criteria
    for an
    inference
    of
    causality.
    (e)
    Biological
    gradient
    (exposure-response
    relationship).
    A
    clear
    exposure-response
    relationship
    (e.g.,
    increasing
    effects
    associated
    with
    greater
    exposure)
    strongly
    suggests
    cause
    and
    effect,
    especially
    when
    such relationships
    are
    also
    observed
    for
    duration
    of exposure
    (e.g.,
    increasing
    effects
    observed
    following
    longer
    exposure
    times).
    There
    are many
    possible
    reasons
    that
    an
    epidemiologic
    study
    may
    fail
    to
    detect
    an exposure-response
    relationship.
    For
    example,
    an
    analysis
    that
    included
    decreasing
    exposures
    due
    to
    improved
    technology
    that
    is combined
    with
    higher
    prior
    exposure
    in an
    initial
    analysis
    can
    require
    a
    segmented
    analysis
    to
    apportion
    exposure.
    Other
    reasons
    for
    failure
    to
    detect
    a relationship
    may
    include
    a small
    range
    of
    exposures.
    Thus,
    the
    absence
    of an
    exposure-response
    relationship
    does
    not exclude
    a
    causal
    relationship.
    U)
    Biologicalplausibility.
    An
    inference
    of causality
    tends
    to
    be strengthened
    by
    consistency
    with data
    from
    experimental
    studies
    or
    other
    sources
    demonstrating
    plausible
    biological
    mechanisms.
    A
    lack
    of
    mechanistic
    data,
    however,
    is not
    a reason
    to reject
    causality.
    (g)
    Coherence.
    An
    inference
    of causality
    may
    be strengthened
    by
    other
    lines
    of
    evidence
    that
    support
    a
    cause-and-effect
    interpretation
    of
    the association.
    Information
    is
    considered
    from
    animal
    bioassays,
    toxicokinetic
    studies,
    and
    short-term
    studies.
    The
    absence
    of other
    lines
    of
    evidence,
    however,
    is
    not
    a
    reason
    to
    reject
    causality.
    (h)
    Experimental
    evidence
    (from
    human
    populations).
    Experimental
    evidence
    is
    seldom
    available
    from
    human
    populations
    and
    exists
    only
    when
    conditions
    of human
    exposure
    have
    occurred
    to
    create
    a
    “natural
    experiment”
    at different
    levels
    of
    exposure.
    Strong
    evidence
    2-14

    for
    causality
    can be
    provided
    when
    a change
    in
    exposure
    brings
    about
    a
    change
    in
    disease
    frequency,
    for
    example,
    the
    decrease
    in the
    risk
    of
    lung
    cancer that
    follows
    cessation
    of
    smoking.
    (i)
    Analogy.
    SARs
    and
    information
    on
    the
    agent’s
    structural
    analogues
    can
    provide
    insight
    into
    whether
    an
    association
    is
    causal.
    Similarly,
    information
    on mode
    of action
    for a
    chemical,
    as one of
    many
    structural
    analogues,
    can
    inform
    decisions
    regarding
    likely
    causality.
    2.2.2.
    Animal
    Data
    Various
    whole-animal
    test systems
    are
    currently
    used
    or
    are under
    development
    for
    evaluating
    potential
    carcinogenicity.
    Cancer
    studies
    involving
    chronic
    exposure
    for
    most
    of
    the
    lifespan
    of an
    animal
    are
    generally
    accepted
    for
    evaluation
    of
    tumor
    effects
    (Tomatis
    et al.,
    1989;
    Rail,
    1991;
    Allen
    et al.,
    1988; but
    see Ames
    and
    Gold,
    1990).
    Other
    studies
    of
    special
    design
    are
    useful
    for observing
    formation
    of
    preneoplastic
    lesions
    or
    tumors
    or investigating
    specific
    modes
    of
    action.
    Their
    applicability
    is
    determined
    on a
    case-by-case
    basis.
    2.2.2.1.
    Long-term
    Carcinogenicity
    Studies
    The
    objective
    of long-term
    carcinogenesis
    bioassays
    is to
    determine
    the
    potential
    carcinogenic
    hazard and
    dose-response
    relationships
    of the
    test agent.
    Carcinogenicity
    rodent
    studies
    are
    designed
    to examine
    the
    production
    of
    tumors
    as well
    as preneoplastic
    lesions
    and
    other indications
    of chronic
    toxicity
    that
    may
    provide
    evidence
    of treatment-related
    effects
    and
    insights
    into the
    way
    the test
    agent
    produces
    tumors.
    Current
    standardized
    carcinogenicity
    studies
    in
    rodents
    test
    at least
    50
    animals
    per
    sex per
    dose
    group in
    each of
    three
    treatment
    groups
    and in a
    concurrent
    control
    group,
    usually
    for
    18 to
    24 months,
    depending
    on
    the
    rodent
    species
    tested
    (OECD,
    1981;
    U.S.
    EPA,
    1 998c).
    The
    high
    dose
    in long-term
    studies
    is generally
    selected
    to
    provide
    the
    maximum
    ability
    to
    detect
    treatment-related
    carcinogenic
    effects
    while
    not
    compromising the
    outcome
    of the
    study
    through
    excessive
    toxicity
    or inducing
    inappropriate
    toxicokinetics
    (e.g.,
    overwhelming
    absorption
    or
    detoxification
    mechanisms).
    The
    purpose
    of
    two
    or more
    lower doses
    is
    to provide
    some
    information
    on
    the
    shape
    of the
    dose-response
    curve.
    Similar
    protocols
    have
    been
    and continue
    to be
    used
    by many
    laboratories
    worldwide.
    2-15

    All available
    studies
    of
    tumor effects
    in whole
    animals
    should
    be
    considered,
    at least
    preliminarily.
    The
    analysis
    should
    discard studies
    judged
    to
    be
    wholly inadequate
    in
    protocol,
    conduct,
    or results.
    Criteria
    for
    the technical
    adequacy
    of animal
    carcinogenicity
    studies
    have
    been
    published
    and should
    be used as
    guidance
    to judge
    the acceptability
    of individual
    studies
    (e.g.,
    NTP,
    1984;
    OSTP,
    1985;
    Chhabra et
    al.,
    1990).
    As these
    criteria,
    in whole or
    in part,
    may
    be
    updated
    by
    the
    National
    Toxicology
    Program (NTP)
    and
    others, the
    analyst should
    consult
    the
    appropriate
    sources
    to determine
    both the
    current
    standards
    as
    well as those
    that were
    contemporaneous
    with
    the study. Care
    should
    be taken
    to include
    studies
    that
    provide
    some
    evidence
    bearing
    on
    carcinogenicity
    or
    that help
    interpret
    effects
    noted
    in other studies,
    even
    if
    these
    studies have
    some limitations
    of
    protocol or
    conduct.
    Such limited,
    but
    not
    wholly
    inadequate,
    studies
    can contribute
    as their
    deficiencies
    permit.
    The
    findings
    of long-term
    rodent
    bioassays
    should be
    interpreted
    in conjunction
    with results
    of
    prechronic
    studies
    along
    with
    toxicokinetic
    studies
    and other
    pertinent information,
    if
    available.
    Evaluation
    of tumor
    effects
    takes into consideration
    both
    biological
    and statistical
    significance
    of the findings
    (Haseman,
    1984,
    1985, 1990,
    1995).
    The following
    sections highlight
    the major
    issues in the
    evaluation
    of
    long-term
    carcinogenicity
    studies.
    2.2.2.1.1.
    Dosing
    issues.
    Among
    the many criteria
    for
    technical
    adequacy
    of animal
    carcinogenicity
    studies is the
    appropriateness
    of
    dose selection.
    The selection
    of
    doses
    for
    chronic bioassays
    is
    based
    on scientific
    judgments
    and
    sound
    toxicologic
    principles.
    Dose
    selection
    should
    be
    made on the
    basis of relevant
    toxicologic
    information
    from
    prechronic,
    mechanistic,
    and
    toxicokinetic
    and mechanistic
    studies.
    A
    scientific
    rationale
    for dose
    selection
    should be
    clearly
    articulated
    (e.g.,
    NTP, 1984;
    ILSI,
    1997).
    How
    well the
    dose selection
    is
    made
    is evaluated
    after the
    completion
    of the bioassay.
    Interpretation
    of carcinogenicity
    study
    results
    is profoundly
    affected
    by study
    exposure
    conditions,
    especially
    by inappropriate
    dose
    selection.
    This
    is
    particularly
    important
    in
    studies
    that
    do not
    show positive
    results
    for carcinogenicity,
    because
    failure
    to use a sufficiently
    high
    dose reduces
    the
    sensitivity
    of
    the studies.
    A
    lack
    of
    tumorigenic
    responses
    at exposure
    levels
    that
    cause
    significant
    impairment
    of animal
    survival
    may
    also not
    be acceptable.
    In
    addition,
    2-16

    overt
    toxicity
    or qualitatively
    altered
    toxicokinetics
    due
    to
    excessively
    high
    doses
    may result
    in
    tumor
    effects
    that
    are
    secondary
    to the
    toxicity
    rather
    than
    directly
    attributable
    to the
    agent.
    With
    regard
    to the
    appropriateness
    of the
    high
    dose,
    an adequate
    high
    dose
    would
    generally
    be
    one
    that produces
    some toxic
    effects
    without
    unduly
    affecting
    mortality
    from
    effects
    other
    than
    cancer
    or producing
    significant
    adverse
    effects
    on
    the
    nutrition
    and
    health
    of the
    test
    animals
    (OECD,
    1981;
    NRC, 1993a).
    If
    the
    test
    agent
    does
    not appear
    to cause
    any
    specific
    target
    organ
    toxicity
    or
    perturbation
    of
    physiological
    function,
    an
    adequate
    high
    dose
    can
    be
    specified
    in
    terms
    of
    a percentage
    reduction
    of body
    weight
    gain
    over the
    lifespan
    of
    the
    animals.
    The
    high
    dose
    would
    generally
    be
    considered
    inadequate
    if neither
    toxicity
    nor change
    in
    weight
    gain is
    observed.
    On the
    other
    hand,
    significant
    increases
    in
    mortality
    from
    effects
    other
    than
    cancer
    generally
    indicate
    that
    an
    adequate
    high
    dose
    has
    been
    exceeded.
    Other
    signs
    of
    treatment-related
    toxicity
    associated
    with
    an excessive
    high dose
    may
    include
    (a)
    significant
    reduction
    of
    body
    weight
    gain
    (e.g.,
    greater
    than
    10%),
    (b) significant
    increases
    in
    abnormal
    behavioral
    and clinical
    signs,
    (c)
    significant
    changes
    in
    hematology
    or
    clinical
    chemistry,
    (d)
    saturation
    of
    absorption
    and
    detoxification
    mechanisms,
    or
    (e) marked
    changes
    in
    organ weight,
    morphology,
    and
    histopathology.
    It
    should
    be noted
    that
    practical
    upper
    limits have
    been
    established
    to
    avoid
    the use
    of excessively
    high
    doses in
    long-term
    carcinogenicity studies
    of environmental
    chemicals
    (e.g.,
    5%
    of
    the test
    substance
    in the feed
    for
    dietary
    studies
    or 1 g/kg
    body
    weight
    for oral
    gavage
    studies
    [OECD,
    1981]).
    For
    dietary
    studies,
    weight
    gain
    reductions
    should
    be
    evaluated
    as
    to whether
    there
    is
    a
    palatability problem
    or an issue
    with
    food
    efficiency;
    certainly,
    the latter
    is a toxic
    manifestation.
    In the case
    of
    inhalation
    studies
    with
    respirable
    particles,
    evidence
    of
    impairment
    of normal
    clearance
    of
    particles
    from
    the
    lung
    should
    be
    considered
    along
    with
    other
    signs
    of toxicity
    to
    the
    respiratory
    airways
    to determine
    whether
    the
    high
    exposure
    concentration
    has
    been
    appropriately
    selected
    (U.S.
    EPA,
    2001
    a).
    For
    dermal
    studies,
    evidence
    of skin
    irritation
    may
    indicate
    that
    an
    adequate
    high
    dose
    has
    been
    reached
    (U.S. EPA,
    1989).
    In
    order
    to obtain
    the
    most
    relevant
    information
    from
    a
    long-term
    carcinogenicity
    study,
    it
    is
    important
    to
    maximize
    exposure
    conditions
    to the
    test
    material.
    At
    the
    same time,
    caution
    is
    appropriate
    in
    using excessive
    high-dose
    levels
    that
    would
    confound
    the
    interpretation
    of
    study
    2-17

    results
    to
    humans.
    The
    middle
    and
    lowest
    doses
    should
    be selected
    to characterize
    the shape
    of
    the
    dose-response
    curve
    as
    much
    as possible.
    It is
    important
    that the
    doses
    be adequately
    spaced
    so that
    the
    study
    can provide
    relevant
    dose-response
    data
    for assessing
    human
    hazard
    and risk.
    If
    the
    testing
    of
    potential
    carcinogenicity
    is
    being
    combined
    with
    an evaluation
    of noncancer
    chronic
    toxicity,
    the
    study should
    be
    designed
    to
    include
    one
    dose
    in addition
    to the
    control(s)
    that
    is not expected
    to elicit
    adverse
    effects.
    There
    are
    several
    possible
    outcomes
    regarding
    the study
    interpretation
    of
    the
    significance
    and
    relevance
    of
    tumorigenic
    effects
    associated
    with
    exposure
    or
    dose
    levels
    below,
    at,
    or
    above
    an adequate
    high
    dose.
    The
    general
    guidance
    is given
    here;
    for
    each case,
    the
    information
    at
    hand
    should
    be evaluated
    and a rationale
    should
    be
    given
    for
    the position
    taken.
    Adequately
    high
    dose. If
    an
    adequately high
    dose has
    been
    used,
    tumor
    effects
    are
    judged
    positive
    or
    negative
    depending
    on the
    presence
    or
    absence
    of significant
    tumor
    incidence
    increases,
    respectively.
    Excessively
    high
    dose.
    If toxicity
    or mortality
    is
    excessive
    at the
    high
    dose,
    interpretation
    depends
    on
    whether
    or
    not
    tumors
    are
    found.
    Studies
    that show
    tumor
    effects
    only
    at excessive
    doses
    may be
    compromised
    and
    may or
    may not
    carry
    weight,
    depending
    on the
    interpretation
    in the
    context
    of other
    study results
    and
    other
    lines
    of
    evidence.
    Results
    of
    such
    studies,
    however,
    are
    generally
    not
    considered
    suitable
    for dose-response
    extrapolation
    if
    it
    is
    determined
    that
    the
    mode(s)
    of
    action
    underlying
    the
    tumorigenic
    responses
    at
    high doses
    is
    not
    operative
    at
    lower doses.
    Studies
    that
    show
    tumors
    at lower
    doses,
    even
    though
    the
    high
    dose is
    excessive
    and
    may
    be
    discounted,
    should
    be
    evaluated
    on their
    own
    merits.
    2-18

    If a study
    does
    not show
    an
    increase
    in tumor
    incidence
    at a toxic
    high
    dose
    and
    appropriately
    spaced
    lower
    doses
    are
    used without
    such toxicity
    or tumors,
    the
    study
    is
    generally
    judged
    as
    negative
    for carcinogenicity.
    Inadequately
    high
    dose. Studies
    of
    inadequate
    sensitivity
    where
    an
    adequately
    high
    dose
    has
    not
    been
    reached
    may
    be
    used
    to
    bound
    the
    dose range
    where
    carcinogenic
    effects
    might
    be expected.
    2.2.2.1.2.
    Statistical
    considerations.
    The
    main aim
    of statistical
    evaluation
    is
    to determine
    whether
    exposure
    to the test
    agent
    is associated
    with
    an
    increase
    of
    tumor
    development.
    Statistical
    analysis
    of a
    long-term
    study
    should
    be
    performed
    for
    each
    tumor
    type separately.
    The
    incidence
    of
    benign
    and
    malignant
    lesions
    of the
    same
    cell
    type,
    usually
    within
    a
    single tissue
    or
    organ,
    are
    considered
    separately
    but
    may
    be
    combined
    when
    scientifically
    defensible
    (McConnell
    etal.,
    1986).
    Trend
    tests
    and
    pairwise
    comparison
    tests
    are
    the
    recommended
    tests
    for determining
    whether
    chance,
    rather
    than
    a treatment-related
    effect,
    is
    a plausible
    explanation
    for
    an
    apparent
    increase
    in tumor
    incidence.
    A
    trend
    test such
    as the
    Cochran-Armitage
    test
    (Snedecor
    and
    Cochran,
    1967)
    asks
    whether
    the results
    in
    all dose
    groups
    together
    increase
    as
    dose increases.
    A
    pairwise
    comparison
    test
    such
    as
    the Fisher
    exact
    test
    (Fisher,
    1950)
    asks whether
    an
    incidence
    in
    one
    dose
    group
    is
    increased
    over
    that
    of
    the
    control
    group.
    By convention,
    for both
    tests
    a
    statistically significant
    comparison
    is one for
    which
    p
    is less
    than
    0.05
    that
    the increased
    incidence
    is
    due to
    chance.
    Significance
    in either
    kind
    of
    test is
    sufficient
    to reject
    the
    hypothesis
    that chance
    accounts
    for
    the result.
    A statistically
    significant
    response
    may
    or
    may
    not
    be
    biologically
    significant
    and vice
    versa. The
    selection
    of a
    significance
    level
    is a
    policy
    choice
    based
    on a
    trade-off
    between
    the
    risks of
    false
    positives
    and
    false
    negatives.
    A
    result
    with
    a significance
    level
    of greater
    or
    less
    than
    5%
    (the
    most common
    significance
    level)
    is
    examined
    to see
    if the result
    confirms
    other
    scientific
    information.
    When the
    assessment
    departs
    from
    a simple
    5%
    level,
    this
    should
    be
    2-19

    highlighted
    in the
    risk
    characterization.
    A
    two-tailed
    test
    or
    a
    one-tailed
    test
    can
    be
    used.
    In
    either
    case
    a
    rationale
    is
    provided.
    Statistical
    power
    can affect
    the
    likelihood
    that
    a
    statistically
    significant
    result
    could
    reasonably
    be expected. This
    is
    especially
    important
    in
    studies
    or
    dose groups
    with
    small
    sample
    sizes or
    low
    dose
    rates.
    Reporting
    the
    statistical
    power
    can
    be
    useful
    for
    comparing
    and
    reconciling
    positive
    and
    negative
    results
    from
    different
    studies.
    Considerations
    of
    multiple
    comparisons
    should
    also be
    taken
    into
    account.
    Haseman
    (1983)
    analyzed
    typical
    animal
    bioassays
    that
    tested
    both
    sexes
    of
    two
    species
    and
    concluded
    that,
    because
    of
    multiple
    comparisons,
    a
    single
    tumor
    increase
    for
    a
    species-sex-site
    combination
    that
    is statistically significant
    at
    the 1%
    level
    for
    common
    tumors
    or
    5%
    for rare
    tumors
    corresponds
    to
    a 7—8%
    significance
    level
    for
    the
    study
    as
    a whole.
    Therefore,
    animal
    bioassays
    presenting
    only
    one
    significant
    result
    that
    falls
    short
    of
    the
    1% level
    for
    a common
    tumor
    should
    be treated
    with
    caution.
    2.2.2.1.3.
    Concurrent and
    historical
    controls.
    The
    standard
    for
    determining
    statistical
    significance
    of tumor
    incidence
    comes
    from
    a comparison
    of
    tumors
    in
    dosed
    animals
    with
    those
    in
    concurrent
    control
    animals.
    Additional
    insights
    about
    both
    statistical
    and
    biological
    significance can come
    from
    an
    examination
    of
    historical
    control
    data
    (Tarone,
    1982;
    Haseman,
    1995).
    Historical
    control
    data
    can
    add
    to
    the
    analysis,
    particularly
    by enabling
    identification
    of
    uncommon
    tumor
    types
    or
    high spontaneous
    incidence
    of
    a tumor
    in
    a
    given
    animal
    strain.
    Identification of common
    or uncommon
    situations
    prompts
    further
    thought
    about
    the
    meaning
    of
    the
    response
    in the
    current
    study
    in
    context
    with
    other
    observations
    in
    animal
    studies
    and
    with
    other
    evidence
    about
    the carcinogenic
    potential
    of
    the
    agent.
    These
    other
    sources
    of
    information
    may
    reinforce
    or
    weaken
    the
    significance
    given
    to the
    response
    in the
    hazard
    assessment.
    Caution
    should
    be
    exercised
    in simply
    looking
    at the
    ranges
    of
    historical
    responses,
    because
    the
    range
    ignores
    differences
    in survival
    of
    animals
    among
    studies
    and
    is related
    to
    the number
    of
    studies
    in
    the
    database.
    In
    analyzing
    results
    for uncommon
    tumors
    in
    a
    treated
    group
    that
    are
    not statistically
    significant
    in
    comparison
    with
    concurrent
    controls,
    the analyst
    may
    be
    informed
    by
    the
    2-20

    experience
    of
    historical
    controls
    to
    conclude
    that
    the result
    is
    in fact
    unlikely
    to
    be due
    to chance.
    However,
    caution
    should
    be
    used
    in
    interpreting
    results.
    In
    analyzing
    results
    for common
    tumors,
    a
    different
    set of
    considerations
    comes
    into
    play.
    Generally
    speaking,
    statistically
    significant
    increases
    in
    tumors
    should
    not
    be
    discounted
    simply
    because
    incidence
    rates
    in
    the
    treated
    groups
    are within
    the
    range
    of historical
    controls
    or because
    incidence
    rates
    in the
    concurrent
    controls
    are somewhat
    lower
    than
    average.
    Random
    assignment
    of animals
    to
    groups
    and
    proper
    statistical
    procedures
    provide
    assurance
    that statistically
    significant
    results
    are
    unlikely
    to be
    due
    to chance
    alone.
    However,
    caution
    should
    be
    used
    in
    interpreting
    results
    that
    are
    barely
    statistically
    significant
    or in which
    incidence
    rates in
    concurrent
    controls
    are unusually
    low
    in comparison
    with
    historical
    controls.
    In cases
    where
    there
    may
    be
    reason
    to
    discount
    the biological
    relevance
    to
    humans
    of
    increases
    in common
    animal
    tumors,
    such considerations
    should
    be weighed
    on
    their
    own
    merits
    and
    clearly
    distinguished
    from
    statistical
    concerns.
    When
    historical
    control
    data
    are
    used,
    the
    discussion
    should address
    several
    issues
    that
    affect
    comparability
    of historical
    and
    concurrent
    control
    data, such
    as genetic
    drift
    in
    the
    laboratory
    strains,
    differences
    in
    pathology
    examination
    at different
    times
    and
    in different
    laboratories
    (e.g.,
    in
    criteria
    for
    evaluating
    lesions;
    variations
    in the
    techniques
    for the
    preparation
    or
    reading
    of
    tissue
    samples
    among
    laboratories),
    and
    comparability
    of animals
    from
    different
    suppliers.
    The
    most
    relevant
    historical
    data come
    from
    the
    same laboratory
    and
    the
    same
    supplier
    and
    are gathered
    within
    2 or
    3
    years
    one
    way
    or
    the
    other of
    the
    study under
    review;
    other
    data should
    be used
    only
    with
    extreme
    caution.
    2.2.2.1.4.
    Assessment
    of
    evidence
    of
    carcinogenicity
    from
    long-term
    animal
    studies.
    In
    general,
    observation
    of
    tumors
    under
    different
    circumstances
    lends
    support
    to
    the
    significance
    of
    the findings
    for
    animal
    carcinogenicity.
    Significance
    is
    generally
    increased
    by the
    observation
    of
    more
    of the
    factors listed
    below.
    For
    a factor
    such
    as malignancy,
    the
    severity
    of
    the
    observed
    pathology
    can
    also
    affect
    the
    significance.
    The
    following
    observations
    add
    significance
    to
    the
    tumor
    findings:
    2-21

    uncommon
    tumor
    types;
    tumors
    at
    multiple
    sites;
    tumors
    by
    more
    than
    one
    route
    of
    administration;
    tumors
    in
    multiple
    species,
    strains,
    or
    both
    sexes;
    progression
    of
    lesions
    from
    preneoplastic
    to
    benign
    to
    malignant;
    reduced
    latency
    of
    neoplastic
    lesions;
    metastases;
    unusual
    magnitude
    of
    tumor
    response;
    proportion
    of
    malignant
    tumors;
    and
    dose-related
    increases.
    In
    these
    cancer
    guidelines,
    tumors
    observed
    in
    animals
    are
    generally
    assumed
    to
    indicate
    that
    an
    agent
    may
    produce
    tumors
    in
    humans.
    Mode
    of
    action
    may
    help
    inform
    this
    assumption
    on
    a
    chemical-specific
    basis.
    Moreover,
    the
    absence
    of
    tumors
    in
    well-conducted,
    long-term
    animal
    studies
    in
    at
    least
    two
    species
    provides
    reasonable
    assurance
    that
    an
    agent
    may
    not
    be
    a
    carcinogenic
    concern
    for
    humans.
    2.2.2.1.5.
    Site
    concordance.
    Site
    concordance
    of
    tumor
    effects
    between
    animals
    and
    humans
    should
    be
    considered
    in
    each
    case.
    Thus
    far,
    there
    is
    evidence
    that
    growth
    control
    mechanisms
    at
    the
    level
    of
    the
    cell
    are
    homologous
    among
    mammals,
    but
    there
    is
    no
    evidence
    that
    these
    mechanisms
    are
    site
    concordant.
    Moreover,
    agents
    observed
    to
    produce
    tumors
    in
    both
    humans
    and
    animals
    have
    produced
    tumors
    either
    at
    the
    same
    site
    (e.g.,
    vinyl
    chloride)
    or
    different
    sites
    (e.g.,
    benzene)
    (NRC,
    1994).
    Hence,
    site
    concordance
    is
    not
    always
    assumed
    between
    animals
    and
    humans.
    On
    the
    other
    hand,
    certain
    modes
    of
    action
    with
    consequences
    for
    particular
    tissue
    sites
    (e.g.,
    disruption
    of
    thyroid
    function)
    may
    lead
    to
    an
    anticipation
    of
    site
    concordance.
    2.2.2.2.
    Perinatal
    Carcinogenicity
    Studies
    The
    objective
    of
    perinatal
    carcinogenesis
    studies
    is
    to
    determine
    the
    carcinogenic
    potential
    and
    dose-response
    relationships
    of
    the
    test
    agent
    in
    the
    developing
    organism.
    Some
    2-22

    investigators
    have
    hypothesized
    that
    the age
    of
    initial
    exposure
    to
    a chemical
    carcinogen
    may
    influence
    the carcinogenic response
    (Vesselinovitch
    et
    al., 1979;
    Rice,
    1979;
    McConnell,
    1992).
    Cunent
    standardized
    long-term
    carcinogenesis
    bioassays
    generally
    begin
    dosing
    animals
    at
    6—8
    weeks
    of age
    and
    continue
    dosing
    for the
    lifespan
    of
    the
    animal
    (18—24
    months). This
    protocol
    has
    been
    modified
    in
    some
    cases
    to investigate
    the
    potential
    of the
    test agent
    to
    induce
    transplacental
    carcinogenesis
    or
    to investigate
    the
    potential
    differences
    following
    perinatal
    and
    adult
    exposures,
    but
    cunently
    there
    is not
    a
    standardized
    protocol
    for testing
    agents
    for
    carcinogenic
    effects
    following
    prenatal
    or
    early
    postnatal
    exposure.
    Several
    cancer
    bioassay
    studies
    have
    compared
    adult
    and
    perinatal
    exposures
    (see
    McConnell,
    1992;
    U.S.
    EPA,
    1996b).
    A
    review
    of these
    studies
    reveals
    that
    perinatal
    exposure
    rarely
    identifies
    carcinogens
    that
    are
    not
    found
    in
    standard
    animal
    bioassays.
    Exposure
    that
    is
    perinatal
    can
    increase
    the
    incidence
    of a
    given
    type
    of
    tumor.
    The
    increase
    may
    reflect
    an
    increased
    length
    of
    exposure
    and
    a
    higher
    dose
    for
    the
    developing
    organism
    relative
    to
    the
    adult
    or
    an
    increase
    in
    susceptibility
    in
    some
    cases.
    Additionally,
    exposure
    that
    is perinatal
    through
    adulthood
    sometimes
    reduces
    the
    latency
    period
    for
    tumors
    to
    develop
    in the
    growing
    organism
    (U. S.
    EPA,
    1
    996b).
    EPA
    evaluates
    the
    usefulness
    of
    perinatal
    studies
    on
    an agent-by-agent
    basis
    (e.g.,
    U.S.
    EPA,
    1997a,
    b).
    Perinatal
    study
    data
    analysis
    generally
    follows
    the
    principles
    discussed
    above
    for
    evaluating
    other
    long-term
    carcinogenicity
    studies.
    When
    differences
    in
    responses
    between
    perinatal
    animals
    and adult
    animals
    suggest
    an
    increased
    susceptibility
    of perinatal or
    postnatal
    animals,
    such
    as
    the
    ones
    below,
    a
    separate
    evaluation
    of
    the response
    should
    be
    prepared:
    a difference
    in
    dose-response
    relationship,
    the
    presence
    of
    different
    tumor
    types,
    an
    earlier
    onset
    of tumors,
    or
    an increase
    in
    the incidence
    of
    tumors.
    2-23

    2.2.2.3.
    Other Studies
    Intermediate-term
    and
    acute dosing
    studies
    often
    use
    protocols
    that
    screen
    for
    carcinogenic
    or preneoplastic
    effects,
    sometimes
    in a single
    tissue.
    Some protocols
    involve
    the
    development
    of
    various
    proliferative
    lesions,
    such as
    foci of
    alteration
    in the
    liver
    (Gold
    sworthy
    et al.,
    1986).
    Others
    use
    tumor
    endpoints,
    such
    as
    the
    induction
    of lung
    adenomas
    in
    the
    sensitive
    strain
    A
    mouse
    (Maronpot
    et al.,
    1986)
    or
    tumor
    induction
    in
    initiation-promotion
    studies
    using
    various
    organs
    such
    as
    the bladder,
    intestine,
    liver,
    lung,
    mammary
    gland,
    and
    thyroid
    (Ito
    et al., 1992).
    In
    these
    tests,
    the
    selected
    tissue
    rather
    than
    the
    whole
    animal
    is,
    in
    a
    sense,
    the
    test system.
    Important
    information
    concerning
    the
    steps in
    the
    carcinogenic
    process
    and
    mode
    of
    action
    can
    be obtained
    from
    “startlstop”
    experiments.
    In these
    protocols,
    an agent
    is
    given for
    a
    period
    of time
    to induce
    particular
    lesions
    or
    effects
    and
    then
    stopped
    in order
    to
    evaluate
    the
    progression
    or
    reversibility
    of
    processes
    (Todd,
    1986;
    Marsman
    and Popp,
    1994).
    Assays
    in
    genetically
    engineered
    rodents
    may provide
    insight into
    the
    chemical
    and
    gene
    interactions
    involved
    in
    carcinogenesis
    (Tennant
    et
    al.,
    1995).
    These
    mechanistically
    based
    approaches
    involve
    activated
    oncogenes
    that
    are
    introduced
    (transgenic)
    or tumor
    suppressor
    genes
    that
    are
    deleted
    (knocked
    out). If
    appropriate
    genes are
    selected,
    not
    only
    may
    these
    systems
    provide
    information
    on
    mechanisms,
    but
    the rodents
    typically
    show
    tumor
    development
    earlier than
    in
    the
    standard
    bioassay.
    Transgenic
    mutagenesis
    assays
    also
    represent
    a
    mechanistic
    approach
    for
    assessing
    the
    mutagenic
    properties
    of agents
    as well
    as
    developing
    quantitative
    linkages
    between
    exposure,
    internal
    dose,
    and
    mutation
    related
    to
    tumor
    induction
    (Morrison
    and
    Ashby,
    1994;
    Sisk
    et al.,
    1994;
    Hayward
    et al.,
    1995).
    The
    support
    that these
    studies
    give
    to a determination
    of
    carcinogenicity
    rests
    on
    their
    contribution
    to
    the
    consistency
    of
    other
    evidence
    about
    an agent.
    For
    instance,
    benzoyl
    peroxide
    has promoter
    activity
    on
    the skin,
    but
    the overall
    evidence
    may
    be
    less
    supportive
    (Kraus
    et
    al.,
    1995).
    These
    studies
    also may
    contribute
    information
    about
    mode
    of
    action.
    It is important
    to
    recognize
    the
    limitations
    of these
    experimental
    protocols,
    such
    as short
    duration,
    limited
    histology,
    lack
    of complete
    development
    of
    tumors,
    or experimental
    manipulation
    of
    the
    carcinogenic
    process,
    that
    may
    limit
    their
    contribution
    to the
    overall
    assessment.
    Generally,
    their
    results
    are
    appropriate
    as
    aids
    in
    the interpretation
    of
    other
    toxicological
    evidence
    (e.g., rodent
    2-24

    chronic
    bioassays),
    especially
    regarding
    potential
    modes
    of action.
    On
    the
    basis
    of
    cunently
    available
    information,
    it is
    unlikely
    that
    any of
    these
    assays,
    which
    are conducted
    for
    6 months
    with
    15
    animals
    per group,
    will
    replace
    all chronic
    bioassays
    for
    hazard
    identification
    (Spalding
    et al.,
    2000;
    Gulezian
    et al.,
    2000;
    ILSI, 2001).
    2.2.3.
    Structural
    Analogue
    Data
    For
    some chemical
    classes,
    there
    is significant
    available
    information,
    largely
    from
    rodent
    bioassays,
    on
    the
    carcinogenicity
    of analogues.
    Analogue
    effects
    are
    instructive
    in
    investigating
    carcinogenic
    potential
    of
    an agent
    as well
    as
    in
    identifying
    potential
    target
    organs,
    exposures
    associated
    with
    effects,
    and
    potential
    functional
    class
    effects
    or
    modes
    of
    action.
    All
    appropriate
    studies
    should
    be included
    and
    analyzed,
    whether
    indicative
    of a
    positive
    effect
    or not.
    Evaluation
    includes
    tests
    in
    various
    animal
    species,
    strains,
    and
    sexes;
    with
    different
    routes
    of
    administration;
    and
    at various
    doses, as
    data are
    available.
    Confidence
    in
    conclusions
    is
    a
    function
    of
    how
    similar
    the analogues
    are to
    the
    agent
    under
    review
    in structure,
    metabolism,
    and
    biological
    activity.
    It is
    important
    to consider
    this
    confidence
    to
    ensure
    a balanced
    position.
    2.3. ANALYSIS
    OF OTHER
    KEY
    DATA
    The
    physical,
    chemical,
    and structural
    properties
    of
    an agent,
    as well
    as data
    on
    endpoints
    that
    are thought
    to be
    critical
    elements
    of the
    carcinogenic
    process,
    provide
    valuable
    insights
    into
    the
    likelihood
    of human
    cancer
    risk.
    The
    following
    sections
    provide
    guidance
    for analyses
    of
    these
    data.
    2.3.1.
    Physicochemical
    Properties
    Physicochemical
    properties
    affect
    an agent’s
    absorption,
    tissue
    distribution
    (bioavailability),
    biotransformation,
    and
    degradation
    in
    the
    body
    and
    are important
    determinants
    of
    hazard
    potential
    (and
    dose-response
    analysis).
    Properties
    that
    should
    be analyzed
    include,
    but
    are not
    limited
    to,
    molecular
    weight,
    size,
    and
    shape;
    valence
    state;
    physical
    state
    (gas,
    liquid,
    solid);
    water
    or
    lipid
    solubility,
    which
    can
    influence
    retention
    and
    tissue distribution;
    and
    potential
    for
    chemical
    degradation
    or stabilization
    in
    the
    body.
    2-25

    An
    agent’s
    potential
    for
    chemical
    reaction
    with
    cellular
    components,
    particularly
    with
    DNA
    and proteins,
    is also important.
    The
    agent’s
    molecular
    size
    and
    shape,
    electrophilicity,
    and
    charge
    distribution
    are
    considered
    in
    order
    to
    decide
    whether
    they
    would
    facilitate
    such
    reactions.
    2.3.2.
    Structure-Activity
    Relationships
    (SARs)
    SAR
    analyses
    and models
    can
    be used
    to predict
    molecular
    properties,
    surrogate
    biological
    endpoints,
    and
    carcinogenicity
    (see,
    e.g.,
    Richard,
    1998a,
    b;
    Richard
    and
    Williams,
    2002;
    Contrera
    et
    al., 2003).
    Overall,
    these
    analyses
    provide
    valuable
    initial
    information
    on
    agents,
    they
    may
    strengthen
    or
    weaken
    concern,
    and
    they
    are part
    of
    the weight
    of evidence.
    Currently,
    SAR
    analysis
    is most
    useful
    for
    chemicals
    and
    metabolites
    that are
    believed
    to
    initiate
    carcinogenesis
    through
    covalent
    interaction
    with
    DNA
    (i.e., DNA-reactive,
    mutagenic,
    electrophilic,
    or
    proelectrophilic
    chemicals)
    (Ashby
    and
    Tennant,
    1991).
    For organic
    chemicals,
    the
    predictive
    capability
    of SAR
    analysis
    combined
    with other
    toxicity
    information
    has been
    demonstrated (Ashby
    and
    Tennant,
    1994).
    The
    following
    parameters
    are
    useful
    in
    comparing
    an
    agent
    to its
    structural
    analogues
    and congeners
    that
    produce
    tumors
    and affect
    related
    biological
    processes
    such as
    receptor
    binding
    and
    activation,
    mutagenicity,
    and
    general
    toxicity
    (Woo
    and
    Arcos,
    1989):
    nature
    and
    reactivity
    of the
    electrophilic
    moiety
    or moieties
    present;
    potential
    to form
    electrophilic
    reactive
    intermediate(s)
    through
    chemical,
    photochemical,
    or
    metabolic
    activation;
    contribution
    of
    the
    carrier
    molecule
    to
    which
    the electrophilic
    moiety(ies)
    is
    attached;
    physicochemical
    properties
    (e.g., physical
    state,
    solubility,
    octanollwater
    partition
    coefficient,
    half-life
    in aqueous
    solution);
    2-26

    structural
    and
    substructural
    features
    (e.g.,
    electronic,
    stearic,
    molecular
    geometric);
    metabolic
    pattern
    (e.g.,
    metabolic
    pathways
    and
    activation
    and
    detoxification
    ratio);
    and
    possible
    exposure
    route(s)
    of the
    agent.
    Suitable
    SAR
    analysis
    of non-DNA-reactive
    chemicals
    and of
    DNA-reactive
    chemicals
    that
    do not
    appear
    to
    bind
    covalently
    to
    DNA
    should
    be
    based
    on knowledge
    or
    postulation
    of the
    probable
    mode(s)
    of
    action
    of closely
    related
    carcinogenic
    structural
    analogues
    (e.g.,
    receptor
    mediated,
    cytotoxicity related).
    Examination
    of
    the
    physicochemical
    and
    biochemical
    properties
    of
    the
    agent
    may then
    provide
    the rest
    of
    the
    infonnation
    needed
    in order
    to
    make
    an
    assessment
    of the
    likelihood
    of the
    agent’s
    activity
    by
    that
    mode
    of action.
    2.3.3.
    Comparative Metabolism
    and
    Toxicokinetics
    Studies
    of the
    absorption,
    distribution,
    biotransformation,
    and
    excretion
    of agents
    permit
    comparisons among
    species
    to
    assist
    in determining
    the
    implications
    of
    animal
    responses
    for
    human
    hazard
    assessment,
    supporting
    identification
    of
    active
    metabolites,
    identifying
    changes
    in
    distribution and
    metabolic
    pathway
    or
    pathways
    over a
    dose
    range,
    and
    making
    comparisons
    among
    different
    routes
    of
    exposure.
    If
    extensive
    data
    are available
    (e.g.,
    blood/tissue
    partition
    coefficients
    and
    pertinent
    physiological parameters
    of the
    species
    of interest),
    physiologically
    based
    toxicokinetic
    models
    can be
    constructed
    to
    assist
    in a determination
    of tissue
    dosimetry,
    species-to-species
    extrapolation
    of dose,
    and
    route-to-route extrapolation
    (Conolly
    and Andersen,
    1991;
    see
    Section
    3.1.2).
    If
    sufficient
    data
    are
    not available, it
    may
    be
    assumed
    as
    a default
    that
    toxicokinetic
    and
    metabolic
    processes
    are
    qualitatively
    comparable
    among
    species.
    Discussion
    of appropriate
    procedures for quantitative, interspecies
    comparisons
    appears
    in
    Chapter
    3.
    The
    qualitative
    question
    of
    whether
    an
    agent
    is
    absorbed
    by
    a particular
    route
    of
    exposure
    is important for weight
    of
    evidence
    classification,
    discussed
    in Section
    2.5.
    Decisions
    about
    2-27

    whether
    route
    of exposure
    is a limiting
    factor
    on
    expression
    of
    any hazard,
    e.g., absorption
    does
    not occur
    by
    a
    specified
    route,
    are generally
    based
    on
    studies
    in which
    effects
    of the
    agent
    or its
    structural
    analogues
    have
    been
    observed
    by different
    routes,
    on physical-chemical
    properties,
    or
    on
    toxicokinetics
    studies.
    Adequate
    metabolism
    and
    toxicokinetic
    data can
    be
    applied
    toward
    the following,
    as
    data
    permit.
    Confidence
    in conclusions
    is enhanced
    when
    in vivo
    data
    are
    available.
    Identing
    inetabolites
    and reactive
    intermediates
    of
    metabolism
    and
    determining
    whether
    one
    or more
    ofthese
    intermediates
    is likely
    to
    be responsible
    for the
    observed
    effects.
    Information
    on the
    reactive
    intermediates
    focuses
    on
    SAR
    analysis,
    analysis
    of
    potential
    modes
    of
    action,
    and estimation
    of
    internal
    dose
    in
    dose-response
    assessment
    (D’Souza
    et
    al.,
    1987; Krewski
    et al.,
    1987).
    Identifying
    and
    comparing
    the
    relative
    activities
    of
    metabolic
    pathways
    in animals
    and in
    humans,
    and
    at
    dfferent
    ages.
    This
    analysis
    can
    provide
    insights
    for
    extrapolating
    results
    of animal
    studies
    to humans.
    Describing
    anticipated
    distribution
    within
    the
    body
    andpossibly
    idenüfying
    target
    organs.
    Use
    of
    water solubility,
    molecular
    weight,
    and
    structure
    analysis
    can
    support
    qualitative
    inferences
    about
    anticipated
    distribution
    and
    excretion.
    In
    addition,
    describing
    whether
    the agent
    or
    metabolite
    of
    concern
    will
    be excreted
    rapidly
    or slowly
    or
    whether
    it will
    be
    stored
    in
    a
    particular
    tissue
    or
    tissues
    to
    be
    mobilized
    later
    can
    identify
    issues
    in comparing
    species
    and
    formulating
    dose
    response
    assessment
    approaches.
    Ident/j’ing
    changes
    in toxicokinetics
    and
    metabolic
    pathways
    with
    increases
    in
    dose. These
    changes
    may result
    in important
    differences
    between
    high
    and low
    dose
    levels
    in
    disposition
    of
    the agent
    or
    generation
    of
    its
    active
    forms.
    These
    2-28

    studies
    play an
    important
    role
    in providing
    a rationale
    for
    dose
    selection
    in
    carcinogenicity
    studies.
    Ident5’ing
    and comparing
    metabolic
    process
    dfferences
    by
    age, sex,
    or
    other
    characteristic
    so that
    susceptible
    subpopulations
    can
    be recognized.
    For
    example,
    metabolic
    capacity
    with
    respect
    to
    P450
    enzymes
    in
    newborn
    children
    is
    extremely
    limited
    compared
    to
    that
    in
    adults,
    so
    that
    a carcinogenic
    metabolite formed
    through
    P450
    activity
    will
    have
    limited
    effect
    in
    the
    young,
    whereas
    a
    carcinogenic
    agent
    deactivated through
    P450
    activity
    will
    result
    in
    increased
    susceptibility
    of
    this
    lifestage
    (Cresteil, 1998).
    A
    variety
    of changes
    in
    toxicokinetics
    and
    physiology
    occur
    from
    the
    fetal
    stage
    to
    post-weaning
    to young
    child.
    Any
    of
    these
    changes
    may
    make
    a
    difference
    for
    risk
    (Renwick,
    1998).
    Determining
    bioavailabiliiy
    via
    different
    routes
    of
    exposure
    by
    analyzing
    uptake
    processes
    under
    various
    exposure
    conditions.
    This
    analysis
    supports
    identification
    of
    hazards
    for
    untested
    routes.
    In
    addition,
    use
    of
    physicochemical
    data
    (e.g.,
    octanol-water
    partition
    coefficient
    information)
    can
    support
    an
    inference
    about
    the
    likelihood
    of
    dermal
    absorption
    (Flynn,
    1990).
    Attempts
    should
    be made
    in
    all
    of
    these
    areas
    to clarify
    and
    describe
    as much
    as
    possible
    the
    variability
    to be
    expected
    because
    of
    differences
    in
    species,
    sex,
    age, and
    route
    of
    exposure.
    The analysis takes
    into
    account
    the
    presence
    of
    subpopulations
    of
    individuals
    who
    are
    particularly
    vulnerable
    to
    the effects
    of
    an agent
    because
    of toxicokinetic
    or
    metabolic
    differences
    (genetically or environmentally
    determined)
    (Bois
    et
    al.,
    1995)
    and is
    a special
    emphasis
    for
    assessment
    of
    risks
    to
    children.
    2.3.4.
    Toxicological and
    Clinical
    Findings
    Toxicological
    findings
    in
    experimental
    animals
    and
    clinical
    observations
    in
    humans
    are
    important resources
    for
    the
    cancer
    hazard
    assessment.
    Such
    findings
    provide
    information
    on
    2-29

    physiological
    effects
    and
    effects
    on
    enzymes,
    hormones,
    and
    other
    important
    macromolecules
    as
    well
    as on
    target
    organs
    for toxicity.
    For
    example,
    given
    that
    the cancer
    process
    represents
    defects
    in
    processes
    such as
    terminal
    differentiation,
    growth
    control,
    and
    cell
    death,
    developmental
    studies
    of
    agents
    may
    provide
    an understanding
    of
    the
    activity
    of an
    agent
    that
    canies
    over
    to cancer
    assessment.
    Toxicity
    studies
    in
    animals
    by
    different
    routes
    of
    administration
    support
    comparison
    of
    absorption
    and
    metabolism
    by
    those
    routes.
    Data
    on
    human
    variability
    in standard
    clinical
    tests
    may
    also
    provide
    insight
    into
    the range
    of
    human
    susceptibility
    and
    the
    common
    mechanisms
    of
    agents
    that
    affect
    the
    tested
    parameters.
    2.3.5.
    Events
    Relevant
    to Mode
    of
    Carcinogenic
    Action
    Knowledge
    of the
    biochemical
    and
    biological
    changes
    that
    precede
    tumor
    development
    (which
    include,
    but are
    not limited
    to,
    mutagenesis,
    increased
    cell proliferation,
    inhibition
    of
    programmed
    cell
    death,
    and
    receptor
    activation)
    may provide
    important
    insight
    for
    determining
    whether
    a cancer
    hazard
    exists
    and
    may
    help
    inform
    appropriate
    consideration
    of
    the
    dose-
    response
    relationship
    below
    the range
    of observable tumor
    response.
    Because
    cancer
    can
    result
    from
    a series
    of genetic
    alterations
    in the
    genes
    that
    control
    cell
    growth,
    division,
    and
    differentiation
    (Vogeistein
    et
    al.,
    1988;
    Hanahan
    and Weinberg,
    2000;
    Kinzler
    and
    Vogeistein,
    2002),
    the
    ability
    of
    an agent
    to
    affect
    genotype
    (and
    hence
    gene
    products)
    or gene
    expression
    is
    of
    obvious
    importance
    in
    evaluating
    its
    influence
    on
    the
    carcinogenic
    process.
    Initial
    and
    key
    questions
    to
    examine
    are:
    Does
    the agent
    (or
    its
    metabolite)
    interact
    directly
    with
    DNA,
    leading
    to mutations
    that
    bring
    about
    changes
    in
    gene
    products
    or
    gene
    expression?
    Does
    the
    agent
    bring
    about
    effects
    on
    gene
    expression
    via other
    nondirect
    DNA
    interaction
    processes?
    Furthermore, carcinogenesis
    involves
    a complex
    series
    and
    interplay
    of events
    that
    alter
    the
    signals
    a
    cell
    receives
    from
    its extracellular
    environment,
    thereby
    promoting
    uncontrolled
    growth.
    Many,
    but
    not
    all,
    mutagens
    are
    carcinogens,
    and
    some,
    but
    not all,
    agents
    that
    induce
    cell
    proliferation lead
    to tumor
    development.
    Thus,
    understanding
    the
    range
    of
    key steps
    in
    the
    carcinogenic process
    upon
    which
    an agent
    might
    act is
    essential
    for
    evaluating
    its
    mode
    of
    action.
    Determination of
    carcinogens
    that
    are
    operating
    by
    a
    mutagenic
    mode
    of
    action,
    for example,
    entails
    evaluation of
    in
    vivo
    or
    in vitro
    short-term
    testing
    results
    for
    genetic
    endpoints,
    metabolic
    2-30

    profiles,
    physicochemical
    properties,
    and structure-activity
    relationship
    (SAR)
    analyses
    in a
    weight-of-evidence
    approach
    (Dearfield
    et al., 1991;
    U.S. EPA,
    1986b;
    Waters
    et al., 1999).
    Key
    data
    for
    a mutagenic
    mode
    of action
    may be
    evidence
    that
    the carcinogen
    or
    a metabolite
    is
    DNA-reactive
    and/or
    has
    the ability
    to bind
    to
    DNA.
    Also, mutagenic
    carcinogens
    usually
    produce
    positive effects
    in multiple
    test
    systems
    for
    different
    genetic
    endpoints,
    particularly
    gene
    mutations
    and structural
    chromosome
    aberrations,
    and in
    tests
    performed
    in
    vivo which
    generally
    are
    supported
    by positive
    tests in
    vitro. Additionally,
    carcinogens
    may
    be
    identified
    as
    operating
    via a mutagenic
    mode
    of
    action
    if they have
    similar properties
    and SAR
    to
    mutagenic
    carcinogens.
    Endpoints
    that
    provide insight
    into an
    agent’s
    ability to
    alter
    gene
    products
    and
    gene
    expression,
    together
    with
    other
    features of
    an agent’s
    potential
    mode
    of
    carcinogenic
    action,
    are discussed
    below.
    2.3.5.1.
    Direct
    DNA-Reactive
    Effects
    It
    is
    well
    known that
    many
    carcinogens
    are electrophiles
    that interact
    with DNA,
    resulting
    in DNA adducts
    and
    breakage (referred
    to in
    these cancer
    guidelines
    as
    direct
    DNA
    effects).
    Usually
    during
    the
    process of
    DNA
    replication,
    these
    DNA
    lesions
    can be converted
    into
    and
    fixed as mutations
    and
    chromosomal
    alterations
    that
    then may initiate
    and
    otherwise
    contribute
    to
    the carcinogenic
    process
    (Shelby
    and
    Zeiger,
    1990;
    Tinwell and
    Ashby,
    1991; IARC,
    1999).
    Thus,
    studies
    of
    mutations
    and other
    genetic
    lesions
    continue
    to inform
    the
    assessment
    of
    potential
    human
    cancer
    hazard and
    in
    the
    understanding
    of an agent’s
    mode
    of
    carcinogenic
    action.
    EPA has
    published
    testing
    guidelines
    for
    detecting the
    ability
    of an agent
    to
    damage
    DNA
    and
    produce
    mutations
    and
    chromosomal
    alterations
    (as discussed
    in Dearfield
    et al.,
    1991).
    Briefly,
    standard
    tests
    for gene mutations
    in
    bacteria and
    mammalian
    cells
    in vitro
    and in
    vivo
    and
    for
    structural chromosomal
    aberrations
    in
    vitro and
    in
    vivo
    are important
    examples
    of
    relevant
    methods.
    New
    molecular
    approaches,
    such as mouse
    mutations
    and
    cancer
    transgenic
    models,
    are providing
    a means
    to examine
    mutation
    at tissue sites
    where
    the tumor
    response
    is
    observed
    (Heddle
    and
    Swiger,
    1996;
    Tennant et
    al., 1999).
    Additionally,
    continued
    improvements
    in
    fluorescent-based
    chromosome
    staining
    methods
    (fluorescent
    in
    situ
    2-31

    hybridization
    [FISH)
    )
    will
    allow
    the detection
    of
    specific
    chromosomal
    abnormalities
    in relevant
    target
    tissues
    (Tucker
    and
    Preston,
    1998).
    Endpoints
    indicative
    of DNA
    damage
    but
    not
    measures
    of mutation
    per
    se,
    such
    as
    DNA
    adducts
    or strand
    breakage, may
    be detected
    in relevant
    target
    tissues
    and
    thus
    contribute
    to
    evaluating
    an agent’s
    mutagenic
    potential.
    Evidence of
    chemical-specific
    DNA
    adducts
    (e.g.,
    reactions
    at oxygen
    sites
    in
    DNA
    bases
    or
    with
    ring
    nitrogens
    of
    guanine
    and
    adenine)
    provides
    information
    on
    a mutagen’s
    ability
    to
    directly
    interact
    with
    DNA
    (La
    and Swenberg,
    1996).
    Some
    planar
    molecules
    (e.g.,
    9-aminoacridine)
    intercalate
    between
    base
    pairs
    of DNA,
    which
    results
    in
    a
    physical
    distortion
    in
    DNA
    that
    may
    lead
    to
    mutations
    when
    DNA
    replicates.
    As
    discussed
    below,
    some
    carcinogens
    do
    not
    interact
    directly
    with
    DNA,
    but
    they can
    produce
    increases
    in
    endogenous
    levels
    of DNA
    adducts
    (e.g.,
    8-hydroxyguanine)
    by indirect
    mechanisms.
    2.3.5.2.
    Indirect
    DNA
    Effects
    or
    Other
    Effects
    on
    Genes/Gene
    Expression
    Although
    some
    carcinogens
    may
    result
    in
    an
    elevation
    of mutations
    or
    cytogenetic
    anomalies,
    as
    detected
    in
    standard
    assays,
    they
    may
    do
    so
    by
    indirect
    mechanisms.
    These
    effects
    may
    be
    brought
    about
    by
    chemical-cell
    interactions
    rather
    than
    by
    the
    chemical
    (or
    its
    metabolite)
    directly
    interacting
    with
    DNA.
    An
    increase
    in mutations
    might
    be
    due
    to cytotoxic
    exposures
    causing
    regenerative
    proliferation
    or
    to mitogenic
    influences
    (Cohen
    and
    Ellwein,
    1990).
    Increased
    cell
    division
    may
    elevate
    mutation
    by
    clonal
    expansion
    of
    initiated
    cells
    or
    by
    increasing
    the
    number
    of
    genetic
    errors
    by
    rapid
    cell
    division
    and
    reduced
    time for
    DNA
    repair.
    Some
    agents
    might
    result
    in an
    elevation
    of mutations
    by interfering
    with
    the enzymes
    involved
    in DNA
    repair
    and
    recombination
    (Barrett
    and
    Lee,
    1992).
    Damage
    to certain
    critical
    DNA
    repair
    genes
    or
    other
    genes
    (e.g.,
    the
    p53
    gene)
    may
    result
    in
    genomic
    instability,
    which
    predisposes
    cells to
    further
    genetic
    alterations
    and
    increases
    the
    probability
    of neoplastic
    progression (Harris
    and
    Hollstein,
    1993;
    Levine
    et
    al.,
    1994;
    Rouse
    and
    Jackson,
    2002).
    Likewise,
    DNA
    repair
    processes
    may
    be
    saturated
    at
    certain
    doses
    of
    a chemical,
    leading
    to an
    elevation
    of
    genetic
    alterations.
    2-32

    The
    initiation
    of
    programmed
    cell
    death
    (apoptosis)
    can
    potentially
    be
    blocked
    by
    an
    agent,
    thereby
    permitting
    replication
    of
    cells
    carrying
    genetic
    errors
    that
    would
    normally
    be
    removed
    from
    the
    proliferative
    pooi.
    At certain
    doses
    an
    agent
    may
    also
    generate
    reactive
    oxygen
    species
    that
    produce
    oxidative
    damage
    to
    DNA
    and
    other
    macromolecules
    (Chang
    et al.
    1988;
    Kehrer,
    1993;
    Clayson
    et al.,
    1994).
    The
    role of
    cellular
    alterations
    that
    are attributable
    to
    oxidative
    damage
    in tumorigenesis
    (e.g.,
    8-hydroxyguanine)
    is currently
    unclear.
    Several
    carcinogens have
    been
    shown
    to
    induce
    aneuploidy
    (the
    loss
    or
    gain
    of
    chromosomes)
    (Barrett,
    1992;
    Gibson
    et
    al.,
    1995).
    Aneuploidy
    can result
    in
    the
    loss
    of
    heterozygosity
    or
    genomic
    instability
    (Cavenee
    et al.,
    1986;
    Fearon
    and
    Vogeistein,
    1990).
    Agents
    that
    cause
    aneuploidy
    typically
    interfere
    with
    the
    normal
    process
    of chromosome
    segregation
    by
    interacting
    with
    non-DNA
    targets
    such
    as
    the
    proteins
    needed
    for chromosome
    segregation
    and
    chromosome
    movement.
    Whether
    this
    chromosome
    imbalance
    is
    the
    cause
    or
    the
    effect
    of
    tumorigenesis
    is not
    clear.
    Thus,
    it
    is important
    to understand
    if
    the
    agent
    induces
    aneuploidy
    as a
    key early
    event
    in
    the
    carcinogenic
    process.
    It is
    possible
    for
    an
    agent
    to alter
    gene
    expression
    by
    transcriptional,
    translational,
    or
    post-
    translational
    modifications. For
    example,
    perturbation
    of DNA
    methylation
    patterns
    may
    cause
    effects
    that
    contribute
    to carcinogenesis
    (Jones,
    1986;
    Holliday,
    1987;
    Goodman
    and
    Counts,
    1993;
    Chuang
    et al.,
    1996;
    Baylin
    and
    Bestor,
    2002).
    Overexpression
    of genes
    by
    DNA
    amplification has
    been
    observed
    in
    certain
    tumors
    (Vainio
    et al.,
    1992).
    Mechanisms
    of
    altering
    gene
    expression
    may
    involve
    cellular
    reprogramming
    through
    hormonal
    or
    receptor-mediated
    mechanisms
    (Barrett,
    1992;
    Ashby
    et
    al.,
    1994).
    Both
    cell
    proliferation
    and programmed
    cell
    death
    can
    be
    part
    of the
    maintenance
    of
    homeostasis in
    many
    normal
    tissues,
    and
    alterations
    in the
    level
    or
    rate
    of
    either
    can
    be
    important
    elements
    of
    the
    carcinogenic
    process.
    The
    balance
    between
    the two
    can
    directly
    affect
    the
    survival
    and
    growth
    of initiated
    cells
    as well
    as
    preneoplastic
    and
    tumor
    cell
    populations
    (i.e.,
    increase
    in
    cell
    proliferation
    or decrease in cell
    death)
    (Moolgavkar,
    1986;
    Cohen
    and
    Ellwein,
    1990,
    1991;
    Cohen
    et al.,
    1991;
    Bellamy
    et
    al., 1995).
    Thus,
    measurements
    of these
    events
    can
    contribute
    to
    the
    weight
    of the
    evidence
    for
    cancer
    hazard
    prediction
    and to
    mode
    of action
    2-33

    understanding. In
    studies
    of
    proliferative
    effects,
    distinctions
    should
    be made
    between
    mitogenesis
    and
    regenerative
    proliferation
    (Cohen
    and Ellwein,
    1990, 1991;
    Cohen
    et
    al., 1991).
    In
    applying
    information
    from
    studies
    on
    cell
    proliferation
    and
    apoptosis
    to
    risk
    assessment,
    it
    is important
    to
    identifi
    the tissues
    and
    target
    cells involved,
    to
    measure
    effects
    in
    both
    normal
    and neoplastic
    tissue,
    to distinguish
    between
    apoptosis
    and necrosis,
    and to
    determine
    the dose
    that
    affects these
    processes.
    Gap-junctional
    intercellular
    communication
    is
    believed
    to
    play
    a role
    in
    tissue
    and organ
    development
    and
    in
    the
    maintenance
    of a normal
    cellular
    phenotype
    within
    tissues.
    A
    growing
    body
    of evidence
    suggests
    that
    chemical
    interference with
    gap-junctional
    intercellular
    communication
    is
    a
    contributing
    factor
    in tumor
    development
    (Swierenga
    and Yamasaki,
    1992;
    Yamasaki,
    1995).
    2.3.5.3.
    Precursor
    Events
    and
    Biomarker
    Information
    Most
    testing
    schemes
    for
    mutagenicity
    and
    other short-term
    assays
    were
    designed
    for
    hazard
    identification
    purposes;
    thus,
    these
    assays
    are
    generally
    conducted
    using acute
    exposures.
    For
    data on
    “precursor
    steps”
    to
    be
    useful
    in
    informing
    the
    dose-response
    curve
    for tumor
    induction
    below
    the level
    of
    observation,
    it is often
    useful
    for
    data
    to come
    from in
    vivo
    studies
    and
    from
    studies
    where
    exposure
    is repeated
    or
    given
    over
    an extended
    period
    of time.
    Although
    consistency
    of
    results
    across
    different
    assays
    and
    animal
    models
    provides
    a stronger
    basis
    for
    drawing
    conclusions,
    it is
    desirable
    to have
    data
    on
    the
    precursor
    event
    in
    the same
    target
    organ,
    sex,
    animal
    strain, and
    species
    as
    the
    tumor
    data. In
    evaluating
    an agent’s
    mode
    of
    action,
    it is
    usually
    not sufficient
    to determine
    that some
    event
    commences
    upon
    dosing.
    It is
    important
    to
    understand
    whether
    it is
    a necessary
    event
    that
    plays a
    key
    role
    in
    the
    process
    that
    leads
    to
    tumor
    development
    versus
    an effect
    of
    the cancer
    process
    itself
    or
    simply
    an
    associated
    event.
    Various
    endpoints
    can serve
    as biological
    markers
    of
    effects
    in
    biological
    systems
    or
    samples.
    These
    may
    help
    identify
    doses
    at
    which
    elements
    of the
    carcinogenic
    process
    are
    operating;
    aid in
    interspecies
    extrapolations
    when
    data are
    available
    from
    both
    experimental
    animal
    and
    human
    cells;
    and
    under
    certain
    circumstances,
    provide
    insights
    into the
    possible
    shape of
    the
    dose-response
    curve
    below
    levels
    where
    tumor
    incidences
    are observed
    (e.g.,
    Choy,
    1993).
    2-34

    Genetic
    and other
    findings
    (such
    as
    changes
    in proto-oncogenes
    and
    tumor
    suppressor
    genes
    in preneoplastic
    and
    neoplastic
    tissue
    or,
    possibly,
    measures
    of
    endocrine
    disruption)
    can
    indicate
    the
    potential
    for
    disease
    and, as
    such,
    serve
    as biomarkers
    of
    effect.
    They,
    too,
    can
    be
    used
    in different
    ways.
    The
    spectrum
    of
    genetic
    changes
    in proliferative
    lesions
    and
    tumors
    following
    chemical
    administration
    to experimental
    animals
    can
    be
    determined
    and compared
    with that
    in spontaneous
    tumors
    in control
    animals,
    in
    animals
    exposed
    to
    other
    agents
    of varying
    structural
    and functional
    activities,
    and
    in
    persons
    exposed
    to
    the
    agent
    under
    study.
    Biomarkers
    of
    effect
    and/or
    precursors
    may
    help
    to
    identify
    subpopulations
    of
    individuals
    who may
    be at an
    elevated
    risk for
    a certain
    cancer
    or
    exposure
    to a
    certain
    agent,
    e.g.,
    cytochrome
    P450
    2D6/debrisoquine
    sensitivity
    for
    lung
    cancer
    (Caporaso
    et
    al., 1989)
    or inherited
    colon cancer
    syndromes
    (Kinzler
    et
    al.,
    1991;
    Peltomäki
    et al., 1993).
    As with
    biomarkers
    of exposure,
    it
    may be
    justified
    in some
    cases
    to use
    biomarkers
    of
    effect
    and/or
    precursors
    for
    dose-response
    assessment
    or to
    provide
    insight
    into
    the potential
    shape
    of the
    dose-response
    curve
    at doses
    below
    those
    at which
    tumors
    are induced
    experimentally.
    In
    applying
    biomarker
    data to
    cancer assessment
    an assessment
    should
    consider:
    analytical
    methodology,
    routes
    of exposure,
    exposure
    to mixtures,
    time
    after exposure,
    sensitivity
    and
    specificity
    of
    biomarkers,
    and
    dose-response
    relationships.
    2-35

    2.3.5.4.
    Judging
    Data
    Criteria
    that
    are generally
    applicable
    for
    judging
    the adequacy
    of mechanistically
    based
    data
    include:
    mechanistic
    relevance
    of the
    data
    to carcinogenicity,
    number
    of
    studies
    of each
    endpoint,
    consistency
    of
    results
    in
    different
    test systems
    and
    different
    species,
    similar
    dose-response
    relationships
    for
    tumor
    and
    mode
    of
    action-related
    effects,
    conduct
    of
    the
    tests in
    accordance
    with
    generally
    accepted
    protocols,
    and
    degree
    of
    consensus
    and
    general
    acceptance
    among
    scientists
    regarding
    interpretation
    of
    the
    significance
    and
    specificity
    of
    the tests.
    Although
    important
    information
    can be
    gained
    from
    in vitro
    test
    systems,
    a higher
    level
    of
    confidence
    is generally
    given
    to
    data
    that are
    derived
    from
    in
    vivo
    systems,
    particularly
    those
    results
    that
    show
    a site
    concordance
    with
    the
    tumor
    data.
    It is
    important
    to
    remember
    that
    when
    judging
    and
    considering
    the use
    of
    any
    data,
    the
    basic
    standard
    of
    quality,
    as defined
    by
    the
    EPA
    Information
    Quality
    Guidelines,
    should
    be
    satisfied.
    2.4.
    MODE
    OF
    ACTION—GENERAL
    CONSIDERATIONS
    ANT)
    FRAMEWORK
    FOR
    ANALYSIS
    2.4.1.
    General
    Considerations
    The
    interaction
    between
    the
    biology
    of the
    organism
    and
    the
    chemical
    properties
    of
    the
    agent
    determine
    whether
    there
    is
    an
    adverse
    effect.
    Thus,
    mode
    of
    action
    analysis
    is
    based
    on
    physical,
    chemical,
    and
    biological
    information
    that
    helps
    to explain
    key
    events
    in
    an
    agent’s
    influence
    on
    development
    of tumors.
    The
    entire
    range
    of
    information
    developed
    in
    the
    assessment
    is
    reviewed
    to
    arrive
    at
    a reasoned
    judgment.
    An
    agent
    may
    work
    by
    more
    than
    one
    mode
    of
    action,
    both
    at
    different
    sites
    and
    at the
    same
    tumor
    site. Thus
    the
    mode
    of
    action
    and
    human
    relevance
    cannot
    necessarily
    be
    generalized
    to
    other
    toxic
    endpoints
    or tissues
    or
    cell
    types
    without
    additional
    analyses
    (IPCS,
    1999;
    Meek
    et
    al., 2003).
    At least
    some
    information
    2-36

    bearing on
    mode of action
    (e.g., SAR, screening
    tests for mutagenicity)
    is
    present
    for most
    agents
    undergoing
    assessment
    of carcinogenicity,
    even though
    certainty
    about
    exact
    molecular
    mechanisms
    may
    be rare.
    Information
    for
    mode
    of action
    analysis generally
    includes tumor
    data in humans
    and
    animals
    and among
    structural analogues,
    as well
    as the other
    key data. The more
    complete
    the
    data
    package and
    the
    generic
    knowledge
    about
    a given mode
    of action, the more
    confidence
    one
    has and the
    more one can
    rely
    on assessment
    of available
    data rather than
    reverting to
    default
    options
    to address
    the
    absence of information
    on mode of
    action.
    Reasoned
    judgments
    are
    generally
    based
    on a data-rich
    source of chemical, chemical
    class,
    and
    tumor type-specific
    information.
    Many
    times there
    will be conflicting
    data
    and
    gaps
    in the
    information
    base;
    it is
    important
    to carefully evaluate
    these
    uncertainties
    before reaching
    any conclusion.
    In
    making decisions
    about
    potential
    modes of action
    and the relevance
    of animal
    tumor
    findings
    to humans
    (Ashby et al.,
    1990; Ashby and Tennant,
    1991; Teimant,
    1993; IPCS
    1999;
    Sonich-Mullin
    et al., 2001; Meek
    et al., 2003),
    very often the results
    of chronic
    animal studies
    may
    give important clues.
    Some of the
    important
    factors
    to review include:
    tumor types,
    for example, those
    responsive
    to endocrine
    influence
    or those
    produced
    by
    DNA-reactive carcinogens;
    number of
    studies and of tumor
    sites, sexes,
    and species affected
    or unaffected
    in
    those
    studies and if the data
    present a coherent
    story;
    similarity of metabolic
    activation
    and detoxification
    for a specific chemical
    between
    humans and
    tested
    species;
    influence of route
    of exposure
    on the spectrum
    of tumors and whether
    they
    occur
    at
    point
    of exposure or systemic
    sites;
    2-37

    effect
    of high
    dose
    exposures
    on
    the
    target
    organ
    or
    systemic
    toxicity
    that
    may
    not
    reflect
    typical
    physiological
    conditions,
    for example,
    urinary
    chemical
    changes
    associated
    with
    stone
    formation,
    effects
    on
    immune
    surveillance;
    presence
    of
    proliferative
    lesions,
    for
    example,
    hepatic
    foci,
    or hyperplasia;
    effect
    of dose
    and
    time
    on
    the progression
    of
    lesions
    from
    preneoplastic
    to
    benign
    tumors,
    then
    to
    malignant;
    ratio
    of
    malignant
    to
    benign
    tumors
    as
    a
    function
    of dose
    and
    time;
    time
    of
    appearance
    of tumors
    after
    commencing
    exposure;
    o
    development
    of tumors
    that
    invade
    locally
    or systemically,
    or lead
    to
    death;
    tumors
    at
    organ
    sites
    with
    high
    or
    low
    background
    historical
    incidence
    in
    laboratory
    animals;
    biomarkers
    in
    tumor
    cells,
    both
    induced
    and
    spontaneous,
    for
    example,
    DNA
    or
    protein
    adducts,
    mutation
    spectra,
    chromosome
    changes,
    oncogene
    activation;
    and/or
    shape
    of the
    dose-response curve
    in
    the
    range
    of tumor
    observation,
    for
    example,
    linear
    versus
    nonlinear.
    Some
    of
    the
    myriad
    ways
    in
    which
    information
    from
    chronic
    animal
    studies
    influences
    mode
    of
    action
    judgments
    include,
    but
    are not
    limited
    to,
    the following:
    multisite
    and
    multispecies
    tumor
    effects
    that
    are
    often
    associated
    with
    mutagenic
    agents;
    2-38

    tumors
    restricted
    to one
    sex
    or
    species
    suggesting
    an influence
    restricted
    to gender,
    strain,
    or species;
    late
    onset
    of tumors
    that
    are
    primarily
    benign,
    are
    at
    sites
    with
    a high
    historical
    background
    incidence,
    or
    show
    reversal
    of
    lesions
    on
    cessation
    of
    exposure
    suggesting
    a
    growth-promoting
    mode
    of action;
    the possibility
    that an
    agent acting
    differently
    in different
    tissues;
    or
    the
    possibility
    that
    has more
    than
    one mode
    of action
    in
    a single
    tissue.
    Simple
    knowledge
    of sites
    of tumor
    increase
    in
    rodent
    studies
    can
    give
    preliminary
    clues
    as
    to mode
    of
    action.
    Experience
    at
    the
    National
    Toxicology
    Program
    (NTP)
    indicates
    that
    substances
    that
    are
    DNA
    reactive
    and that
    produce
    gene
    mutations
    may be
    unique
    in producing
    tumors
    in
    certain
    anatomical
    sites,
    whereas
    tumors
    at
    other
    sites
    may
    arise
    from
    both
    mutagenic
    or
    norunutagenic
    influences
    (Ashby
    and
    Tennant,
    1991;
    Huff
    et aL, 1991).
    The types
    of data
    and
    their
    influence
    on
    judgments
    regarding
    mode
    of action
    are
    expected
    to
    evolve,
    both
    as science
    advances
    and as
    the risk
    assessment
    community
    gains
    more
    experience
    with these
    analyses.
    This
    section
    contains
    a framework
    for
    evaluating
    hypothesized
    mode(s)
    of
    action.
    This
    framework
    has
    similarities
    to
    and
    differences
    with
    the
    concepts
    presented
    in other
    MOA
    frameworks
    (e.g.,
    IPCS,
    1999;
    Sonich-Mullin
    et al.,
    2001;
    Meek
    et
    aL, 2003).
    Differences
    are often
    due to
    the
    context
    of the
    use
    for
    the framework.
    For example,
    the
    Meek
    et
    al. (2003)
    presents
    a
    stand-alone
    document
    for addressing
    mode of
    action
    issues;
    thus,
    it
    recommends
    that
    conclusions
    concerning
    MOA
    be
    rendered
    separately.
    In these
    cancer
    guidelines,
    however,
    they
    are
    incorporated
    into
    the context
    of
    all of
    the data
    regarding
    weight
    of
    the
    evidence
    for
    carcinogenicity.
    2-39

    2.4.2.
    Evaluating
    an
    Hypothesized
    Mode
    of Action
    2.4.2.1.
    Peer Review
    In
    reaching
    conclusions,
    the
    question
    of “general
    acceptance”
    of
    a mode
    of action
    should
    be tested
    as
    part
    of the
    independent
    peer
    review
    that EPA
    obtains
    for
    its assessment
    and
    conclusions.
    In
    some cases
    the
    mode of
    action
    may
    already
    have
    been
    established
    by
    development
    of
    a large
    body
    of
    research
    information
    and
    characterization
    of the
    phenomenon
    over
    time.
    In some
    cases
    there will
    have
    been development
    of an Agency
    policy
    (e.g., mode
    of
    action
    involving
    alpha-2u-globulin
    in the
    male
    rat
    [U.S.
    EPA,
    1991
    b])
    or
    a
    series
    of previous
    assessments
    in
    which both
    the
    mode of
    action
    and
    its
    applicability
    to
    particular
    cases
    has
    been
    explored.
    If so,
    the assessment
    and
    its peer
    review
    can
    focus
    on
    the
    evidence
    that a
    particular
    agent
    acts
    in
    this mode.
    The
    peer
    review
    should
    also evaluate
    the strengths
    and weaknesses
    of
    competing
    modes
    of action.
    In other
    cases,
    the mode
    of action
    may
    not
    have
    previously
    been
    the subject
    of an Agency
    document.
    If
    so, the
    data
    to
    support
    both
    the mode
    of
    action
    and
    the
    associated
    activity
    of the
    agent
    should
    undergo
    EPA
    assessment
    and subsequent
    peer
    review.
    2.4.2.2.
    Use
    of
    the Framework
    The
    framework
    supports
    a full
    analysis
    of mode
    of
    action
    information,
    but
    it can also
    be
    used as
    a screen
    to
    decide
    whether
    sufficient
    information
    is available
    to evaluate
    or whether
    the
    data
    gaps are
    too substantial
    to
    justify
    further
    analysis.
    Mode
    of
    action
    conclusions
    are used
    to
    address
    the
    question
    of human
    relevance
    of
    animal
    tumor
    responses,
    to
    address
    differences
    in
    anticipated
    response
    among
    humans,
    such
    as between
    children
    and
    adults
    or
    men
    and
    women;
    and
    as
    the basis
    of
    decisions
    about
    the
    anticipated
    shape
    of
    the
    dose-response
    relationship.
    Guidance
    on
    the latter
    appears
    in Section
    3.
    This
    framework
    is
    intended
    to provide
    an
    analytical
    approach
    for
    evaluating
    the
    mode
    of
    action.
    It is
    neither
    a
    checklist
    nor a
    list of required
    criteria.
    As
    the
    type
    and
    amount
    of
    information
    will
    depend
    on the mode
    of
    action postulated,
    scientific
    judgment
    is
    important
    to
    determine
    if
    the
    weight
    of
    evidence
    is
    sufficient.
    2-40

    2.4.3.
    Framework
    for
    Evaluating
    Each Hypothesized
    Carcinogenic
    Mode
    of Action
    This
    framework
    is
    intended
    to be
    an analytic
    tool for
    judging
    whether
    available
    data
    support
    a mode
    of carcinogenic
    action
    hypothesized
    for
    an
    agent. It
    is based upon
    considerations
    for causality
    in
    epidemiologic
    investigations
    originally
    articulated
    by Hill
    (1965)
    but
    later
    modified
    by others
    and extended
    to
    experimental
    studies. The
    original
    Hill criteria
    were
    applied
    to epidemiologic
    data, whereas
    this
    framework
    is
    applied
    to a much wider
    assortment
    of
    experimental
    data, so
    it
    retains the
    basic principles
    of Hill
    but
    is much
    modified
    in content.
    The
    modified Hill
    criteria
    can be
    useful
    for
    organizing
    thinking
    about
    aspects
    of
    causation,
    and
    they
    are
    consistent
    with
    the scientific
    method
    of developing
    hypotheses
    and
    testing
    those
    hypotheses
    experimentally.
    During
    analysis
    by EPA,
    and
    as
    guidance
    for
    peer
    review, a key
    question
    is whether
    the data to support
    a mode
    of action
    meet the standards
    generally
    applied
    in
    experimental
    biology regarding
    inference
    of causation.
    All pertinent
    studies are
    reviewed
    in analyzing
    a mode
    of action,
    and
    an
    overall
    weighing
    of evidence
    is
    performed,
    laying
    out
    the
    strengths,
    weaknesses,
    and uncertainties
    of
    the
    case
    as
    well
    as potential
    alternative
    positions
    and rationales.
    Identifying
    data gaps
    and research
    needs
    is
    also
    part of the
    assessment.
    To evaluate
    whether
    an hypothesized
    mode
    of
    action is operative,
    an
    analysis starts
    with
    an outline
    of the
    scientific
    findings
    regarding
    the hypothesized
    key events
    leading
    to cancer,
    and
    then weighing
    information
    to determine
    whether
    there is
    a causal relationship
    between
    these
    events
    and cancer
    formation,
    i.e., that
    the
    effects
    are critical
    for
    induction
    of
    tumors. It
    is
    not
    generally
    expected
    that
    the complete
    sequence
    will
    be known
    at the molecular
    level.
    Instead,
    empirical
    observations
    made
    at different
    levels of
    biological
    organization—biochemical,
    cellular,
    physiological,
    tissue,
    organ,
    and system—are
    analyzed.
    Several
    important
    points
    should
    be
    considered
    when working
    with
    the
    framework:
    The topics
    listed for analysis
    should
    not be regarded
    as a
    checklist
    of necessary
    “proofs.”
    The
    judgment of
    whether
    an
    hypothesized
    mode
    of
    action
    is supported
    by
    available
    data
    takes account
    of the analysis
    as
    a whole.
    2-41

    The
    framework
    provides
    a
    structure
    for
    organizing
    the
    facts
    upon
    which
    conclusions
    as to
    mode
    of action
    rest.
    The
    purpose
    of
    using
    the
    framework
    is to
    make
    analysis
    transparent
    and
    to
    allow
    the
    reader
    to
    understand
    the facts
    and
    reasoning
    behind
    a
    conclusion.
    The
    framework
    does
    not
    dictate
    an answer.
    The
    weight
    of
    evidence
    that is
    sufficient
    to support
    a
    decision
    about
    a
    mode
    of
    action
    may
    be
    less
    or
    more,
    depending
    on
    the
    purpose
    of
    the
    analysis,
    for
    example,
    screening,
    research
    needs
    identification,
    or full
    risk
    assessment.
    To
    make
    the
    reasoning
    transparent,
    the
    purpose
    of the
    analysis
    should
    be made
    apparent
    to
    the
    reader.
    Toxicokinetic
    studies
    may
    contribute
    to mode
    of
    action
    analysis
    by contributing
    to
    identifring
    the
    active
    form(s)
    of
    an
    agent
    that
    is
    central
    to
    the
    mode
    of
    action.
    Apart
    from contributing
    in this
    way,
    toxicokinetics
    studies
    may
    reveal
    effects
    of
    saturation
    of
    metabolic
    processes.
    These
    may not
    be
    considered
    key
    events
    in
    a
    mode
    of
    action,
    but
    they
    are
    given
    separate
    consideration
    in
    assessing
    dose
    metrics
    and
    potential
    nonlinearity
    of
    the
    dose-response
    relationship.
    Generally, “sufficient”
    support
    is
    a
    matter
    of scientific
    judgment
    in
    the
    context
    of
    the
    requirements
    of the
    decisionmaker
    or
    in
    the
    context
    of
    science
    policy
    guidance
    regarding
    a
    certain
    mode
    of action.
    Even
    when
    an
    hypothesized
    mode
    of
    action
    is supported
    for
    a described
    response
    in
    a
    specific
    tissue,
    it
    may
    not
    explain
    other
    tumor
    responses
    observed,
    which
    should
    get
    separate
    consideration
    in
    hazard
    and
    dose-response
    assessment.
    For
    each tumor
    site
    being
    evaluated,
    the
    mode
    of
    action
    analysis
    should
    begin
    with
    a
    description
    of
    the
    relevant
    data
    and
    key
    events
    that
    may
    be
    associated
    with
    an
    hypothesized
    mode
    of
    action
    and
    its sequence
    of key
    events
    (see
    Section
    2.4.3.1).
    This
    can be
    followed
    by a
    2-42

    discussion
    of
    various
    aspects
    of
    the
    experimental
    support
    for hypothesized
    mode(s)
    of
    action
    in
    animals
    and
    humans
    (see
    Section
    2.4.3.2).
    The possibility
    of other
    modes
    of
    action
    also
    should
    be considered
    and
    discussed
    (see
    Section
    2.4.3.3);
    if there
    is evidence
    for
    more
    than
    one mode
    of
    action,
    each
    should
    receive
    a
    separate
    analysis.
    Conclusions
    about each
    hypothesized
    mode
    of
    action
    should
    address
    whether
    the mode
    of
    action
    is
    supported
    in
    animals
    and
    is
    relevant
    to
    humans
    and
    which
    populations
    or
    lifestages
    can
    be
    particularly
    susceptible
    (see
    Section
    2.4.3.4).
    In
    a
    risk
    assessment
    document,
    the
    analysis
    of
    an hypothesized
    mode
    of action
    can
    be
    presented
    before
    or with
    the
    characterization
    of an
    agent’s
    potential
    hazard
    to
    humans.
    2.4.3.1.
    Description
    ofthe
    Hypothesized
    Mode
    of
    Action
    Summary
    descrztion
    of
    the
    hypothesized
    mode
    ofaction.
    For
    each tumor
    site, the
    mode
    of action
    analysis
    begins
    with
    a
    description
    of
    the hypothesized
    mode
    of action
    and
    its
    sequence
    of key
    events.
    If
    there
    is
    evidence
    for
    more
    than
    one
    mode
    of action,
    each
    receives
    a separate
    analysis.
    Identification
    of
    key events.
    In
    order
    to
    judge
    how well
    data
    support
    involvement
    of a
    key
    event
    in
    carcinogenic
    processes,
    the
    experimental
    definition
    of the
    event
    or events
    should
    be
    clear
    and
    reproducible.
    To support
    an association,
    experiments
    should
    define
    and
    measure
    an
    event
    consistently.
    Can
    a list of
    events
    be identified
    that
    are key
    to the
    carcinogenic
    process?
    Are
    the
    events
    well
    defined?
    Pertinent
    observations
    may include,
    but
    are not
    limited
    to, receptor-ligand
    changes,
    cytotoxicity,
    cell
    cycle
    effects,
    increased
    cell
    growth,
    organ
    weight
    differences,
    histological
    changes,
    hormone
    or
    other
    protein
    perturbations,
    or
    DNA
    and
    chromosome
    effects.
    2-43

    2.4.3.2.
    Discussion
    of
    the
    Experimental
    Support
    for
    the
    Hypothesized
    Mode
    of
    Action
    The
    experimental
    support
    for
    the
    hypothesized
    mode
    of
    action
    should
    be
    discussed
    from
    several
    viewpoints
    patterned
    after
    the
    Hill
    criteria
    (see
    Section
    2.2.1.7).
    For
    illustration,
    the
    explanation
    of
    each
    topic
    includes
    typical
    questions
    to
    be
    addressed
    to
    the
    available
    empirical
    data
    and
    experimental
    observations
    anticipated
    to
    be
    pertinent.
    The
    latter
    will
    vary
    from
    case
    to
    case.
    For
    a
    particular
    mode
    of
    action,
    certain
    observations
    may
    be
    established
    as
    essential
    in
    practice
    or
    policy,
    for
    example,
    measures
    of
    thyroid
    hormone
    levels
    in
    supporting
    thyroid
    hormone
    elevation
    as
    a
    key
    event
    in
    carcinogenesis.
    Strength,
    consistency,
    specflcity
    of
    association.
    A
    statistically
    significant
    association
    between
    events
    and
    a
    tumor
    response
    observed
    in
    well-conducted
    studies
    is
    generally
    supportive
    of
    causation.
    Consistent
    observations
    in
    a
    number
    of
    such
    studies
    with
    differing
    experimental
    designs
    increase
    that
    support,
    because
    different
    designs
    may
    reduce
    unknown
    biases.
    Studies
    showing
    “recovery,”
    i.e,
    absence
    or
    reduction
    of
    carcinogenicity
    when
    the
    event
    is
    blocked
    or
    diminished,
    are
    particularly
    useful
    tests
    of
    the
    association.
    Specificity
    of
    the
    association,without
    evidence
    of
    other
    modes
    of
    action,
    strengthens
    a
    causal
    conclusion.
    A
    lack
    of
    strength,
    consistency,
    and
    specificity
    of
    association
    weakens
    the
    causal
    conclusions
    for
    a
    particular
    mode
    of
    action.
    ‘V1hat
    is
    the
    level
    of
    statistical
    and
    biological
    significance
    for
    each
    event
    and
    for
    cancer?
    Do
    independent
    studies
    and
    different
    experimental
    hypothesis-testing
    approaches
    produce
    the
    same
    associations?
    Does
    the
    agent
    produce
    effects
    other
    than
    those
    hypothesized?
    Is
    the
    key
    event
    associated
    with
    precursor
    lesions?
    2-44

    Pertinent
    observations include
    tumor
    response
    associated
    with
    events
    (site
    of
    action
    logically
    relates
    to
    event[s]),
    precursor
    lesions
    associated
    with
    events,
    initiation-promotion
    studies,
    and
    stop/recovery
    studies.
    Dose-response
    concordance.
    If
    a key
    event
    and
    tumor
    endpoints
    increase
    with
    dose
    such
    that
    the
    key
    events
    forecast
    the
    appearance
    of tumors
    at a later
    time
    or
    higher
    dose,
    a
    causal
    association
    can be
    strengthened.
    Dose-response
    associations
    of the
    key
    event
    with
    other
    precursor
    events
    can
    add
    further
    strength.
    Difficulty
    arises
    when
    an event
    is not
    causal
    but
    accompanies the
    process
    generally.
    For
    example,
    if
    tumors
    and the
    hypothesized
    precursor
    both
    increase
    with
    dose,
    the
    two
    responses
    will
    be correlated
    regardless
    of
    whether
    a
    causal
    relationship
    exists.
    This
    is
    similar
    to the
    issue
    of
    confounding
    in epidemiologic
    studies.
    Dose-
    response
    studies
    coupled
    with
    mechanistic
    studies
    can
    assist
    in
    clarifying
    these
    relationships.
    What
    are the
    correlations
    among
    doses
    producing
    events
    and cancer?
    Pertinent observations
    include,
    but are
    not
    limited
    to, 2-year
    bioassay
    observation
    of
    lesions
    correlated
    with
    observations
    of
    hormone
    changes
    and
    the same
    lesions
    in
    shorter
    term
    studies
    or
    in
    interim
    sacrifice.
    Temporal
    relationship.
    If an event
    is shown
    to
    be causally
    linked
    to
    tumorigenesis,
    it
    will
    precede
    tumor
    appearance. An
    event
    may
    also
    be
    observed
    contemporaneously
    or
    after
    tumor
    appearance; these
    observations may
    add
    to the
    strength
    of association
    but
    not
    to
    the temporal
    association.
    What
    is
    the
    ordering
    of
    events
    that
    underlie
    the
    carcinogenic
    process?
    Is this
    ordering
    consistent
    among
    independent
    studies?
    Pertinent
    observations include
    studies
    of varying
    duration
    observing
    the
    temporal
    sequence
    of
    events
    and
    development
    of
    tumors.
    2-45

    Biological plausibility
    and
    coherence.
    It
    is important
    that
    the
    hypothesized
    mode
    of
    action
    and
    the
    events
    that
    are part
    of it
    be based
    on
    contemporaneous
    understanding
    of
    the
    biology
    of
    cancer
    to be
    accepted.
    If the
    body
    of infonnation
    under
    scrutiny
    is
    consistent
    with
    other
    examples
    (including
    structurally
    related
    agents)
    for which
    the
    hypothesized
    mode
    of
    action
    is accepted, the case
    is
    strengthened.
    Because
    some
    modes
    of
    action
    can
    be
    anticipated
    to evoke
    effects
    other
    than
    cancer,
    the
    available
    toxicity
    database
    on
    noncancer
    effects,
    for
    example,
    reproductive
    effects
    of
    certain
    hormonal
    disturbances,
    can
    contribute
    to
    this
    evaluation.
    Is the
    mode
    of
    action
    consistent
    with
    what is
    known
    about
    carcinogenesis
    in
    general
    and
    for
    the
    case
    specifically?
    Are
    carcinogenic
    effects
    and
    events
    consistent
    across
    structural
    analogues?
    Is the
    database
    on
    the
    agent
    internally
    consistent
    in
    supporting
    the purported
    mode
    of action,
    including
    relevant
    noncancer
    toxicities?
    Pertinent
    observations
    include
    the scientific
    basis
    for considering
    an
    hypothesized
    mode
    of
    action
    generally, given
    the
    contemporaneous state
    of knowledge
    of
    carcinogenic
    processes;
    previous
    examples
    of
    data
    sets
    showing
    the
    mode
    of
    action;
    data sets
    on
    analogues;
    and
    coherence
    of
    data
    in
    this case
    from
    cancer
    and noncancer
    toxicity
    studies.
    2.4.3.3.
    Consideration
    of
    the
    Possibility
    of
    Other
    Modes
    of
    Action
    The
    possible
    involvement
    of
    more
    than
    one
    mode
    of action
    at the
    tumor
    site
    should
    be
    considered. Pertinent
    observations
    that
    are
    not consistent
    with
    the
    hypothesized
    mode
    of action
    can
    suggest
    the
    possibility
    of other
    modes
    of action.
    Some
    pertinent
    observations
    can
    be
    consistent with
    more
    than
    one
    mode
    of
    action.
    Furthermore,
    different
    modes
    of
    action
    can
    operate
    in
    different
    dose
    ranges;
    for
    example,
    an
    agent
    can
    act
    predominantly
    through
    cytotoxicity at
    high doses
    and
    through
    mutagenicity
    at
    lower
    doses
    where
    cytotoxicity
    may
    not
    occur.
    2-46

    If there
    is evidence
    for
    more
    than
    one
    mode
    of action,
    each
    should
    receive
    a separate
    analysis.
    There may
    be an
    uneven
    level
    of experimental
    support
    for
    the different
    modes
    of
    action.
    Sometimes
    this
    can reflect
    disproportionate
    resources
    spent
    on
    investigating
    one
    particular
    mode
    of
    action and
    not the
    validity
    or
    relative
    importance
    of
    the other
    possible
    modes
    of action.
    Ultimately,
    however,
    the information
    on
    all
    of
    the modes
    of
    action
    should
    be
    integrated
    to
    better understand
    how
    and when
    each
    mode acts,
    and
    which
    mode(s)
    may
    be
    of
    interest
    for
    exposure
    levels
    relevant
    to human
    exposures
    of interest.
    2.4.3.4.
    Conclusions
    About
    the
    Hypothesized
    Mode
    ofAction
    Conclusions
    about
    the
    hypothesized
    mode
    of action
    should
    address
    the issues
    listed
    below.
    For
    those
    agents
    for
    which the
    mode
    of
    action
    is
    considered
    useful
    for the
    risk
    assessment,
    the
    weight
    of the
    evidence
    concerning
    mode
    of action
    in animals
    as well
    as
    its
    relevance
    for
    humans
    would
    be
    incorporated
    into
    the
    weight
    of evidence
    narrative
    (Section
    2.5).
    (a)
    Is the
    hypothesized
    mode
    of
    action
    sufficiently
    supported
    in the test
    animals?
    Associations
    observed
    between
    key events
    and
    tumors
    may or
    may
    not
    support
    an
    inference
    of
    causation.
    The conclusion
    that
    the agent
    causes
    one or more
    key
    events
    that results
    in tumors
    is
    strengthened
    as
    more
    aspects
    of
    causation
    are satisfied
    and weakened
    as
    fewer
    are
    satisfied.
    Consistent
    results
    in different
    experiments
    that test
    the
    hypothesized
    mode
    of action
    build
    support
    for
    that
    mode
    of action.
    Replicating
    results
    in
    a
    similar
    experiment
    does
    not
    generally
    meaningfully
    strengthen
    the original
    evidence,
    and discordant
    results generally
    weaken
    that
    support.
    Experimental
    challenge
    to the
    hypothesized
    mode
    of action,
    where
    interrupting
    the
    sequence
    of
    key
    events
    suppresses
    the
    tumor
    response
    or enhancement
    of
    key events
    increases
    the
    tumor
    response,
    creates
    very
    strong
    support
    for
    the
    mode of
    action.
    (b)
    Is
    the
    hypothesized
    mode
    ofaction
    relevant
    to humans?
    If
    an hypothesized
    mode
    of
    action
    is sufficiently
    supported
    in
    the
    test
    animals,
    the sequence
    of key
    precursor
    events
    should
    be
    reviewed
    to
    identify
    critical
    similarities
    and
    differences
    between
    the test
    animals
    and
    humans.
    The
    question
    of
    concordance
    can
    be
    complicated
    by
    cross-species
    differences
    in
    toxicokinetics
    or
    2-47

    toxicodynamics.
    For
    example,
    the
    active
    agent
    can
    be
    formed
    through
    different
    metabolic
    pathways
    in
    animals
    and
    humans.
    Any
    information
    suggesting
    quantitative
    differences
    between
    animals
    and
    humans
    is
    flagged
    for
    consideration
    in
    the
    dose-response
    assessment.
    This
    includes
    the
    potential
    for
    different
    internal
    doses
    of
    the
    active
    agent
    or
    for
    differential
    occurrence
    of
    a
    key
    precursor
    event.
    “Relevance”
    of
    a
    potential
    mode
    of
    action
    is
    considered
    in
    the
    context
    of
    characterization
    of
    hazard,
    not
    level
    of
    risk.
    Anticipated
    levels
    of
    human
    exposure
    are
    not
    used
    to
    determine
    whether
    the
    hypothesized
    mode
    of
    action
    is
    relevant
    to
    humans.
    Exposure
    information
    is
    integrated
    into
    the
    overall
    risk
    characterization.
    The
    question
    of
    relevance
    considers
    all
    populations
    and
    lifestages.
    It
    is
    possible
    that
    the
    conditions
    under
    which
    a
    mode
    of
    action
    operates
    exist
    primarily
    in
    a
    particular
    population
    or
    lifestage,
    for
    example,
    in
    those
    with
    a
    pre-existing
    hormonal
    imbalance.
    Other
    populations
    or
    lifestages
    may
    not
    be
    analogous
    to
    the
    test
    animals,
    in
    which
    case
    the
    question
    of
    relevance
    would
    be
    decided
    by
    inference.
    Special
    attention
    should
    be
    paid
    to
    whether
    tumors
    can
    arise
    from
    childhood
    exposure,
    considering
    various
    aspects
    of
    development
    during
    these
    lifestages.
    Because
    the
    studies
    that
    support
    a
    mode
    of
    action
    are
    typically
    conducted
    in
    mature
    animals,
    conclusions
    about
    relevance
    during
    childhood
    generally
    rely
    on
    inference.
    There
    is
    currently
    no
    standard
    Agency
    position
    regarding
    the
    issue
    of
    whether
    tumors
    arising
    through
    the
    hypothesized
    mode
    of
    action
    are
    relevant
    during
    childhood;
    understanding
    the
    mode
    of
    action
    implies
    that
    there
    are
    sufficient
    data
    (on
    either
    the
    specific
    agent
    or
    the
    general
    mode
    of
    action)
    to
    form
    a
    confident
    conclusion
    about
    relevance
    during
    childhood.
    (c)
    Which
    populations
    or
    lifestages
    can
    be
    particularly
    susceptible
    to
    the
    hypothesized
    mode
    of
    action?
    If
    an
    hypothesized
    mode
    of
    action
    is
    judged
    relevant
    to
    humans,
    information
    about
    the
    key
    precursor
    event(s)
    is
    reviewed
    to
    identify
    populations
    or
    lifestages
    that
    might
    reasonably
    expected
    to
    be
    particularly
    susceptible
    to
    their
    occurrence.
    Although
    agent-specific
    data
    would
    provide
    the
    strongest
    indication
    of
    susceptibility,
    this
    review
    may
    also
    rely
    on
    general
    knowledge
    about
    the
    precursor
    events
    and
    characteristics
    of
    individuals
    susceptible
    to
    these
    2-48

    events.
    Any information
    suggesting
    quantitative
    differences
    between
    populations
    or
    lifestages
    should
    be
    flagged for
    consideration
    in the dose-response
    assessment
    (see
    Section
    3.5). This
    includes
    the potential
    for a higher
    internal
    dose of
    the active
    agent
    or for
    an
    increased
    occurrence
    of a key precursor
    event.
    Quantitative
    differences
    may
    result in
    separate
    risk
    estimates
    for
    susceptible
    populations
    or lifestages.
    The possibility
    that
    childhood
    is a susceptible
    period
    for exposure
    should
    be
    explicitly
    addressed.
    Generic
    understanding
    of the mode
    of action
    can
    be
    used to
    gauge
    childhood
    susceptibility,
    and
    this
    determination
    can be
    refined through
    analysis
    of
    agent-specific
    data.
    2.4.4
    Evolution
    with Experience
    Several
    groups
    have
    proposed
    or
    incorporated
    mode of
    action into
    their
    risk
    assessments
    (see,
    e.g.,
    U.S.
    EPA,
    1991b;
    Sonich-Mullin
    et
    a!., 2001;
    Meek
    et al.,
    2003). As
    the
    frameworks
    and
    mandates
    under which
    these evaluations
    were
    produced
    differ,
    the specific
    procedures
    described
    in and
    conclusions
    drawn
    may also
    differ.
    Nevertheless,
    the
    number
    of case
    studies
    from
    all venues
    remains limited.
    More
    experience
    with differing
    modes
    of action
    are
    expected
    to
    highlight
    and
    illustrate the
    strengths
    and
    limitations
    of
    the
    general
    framework
    proposed
    in
    these
    cancer
    guidelines.
    Moreover,
    additional toxicological
    techniques
    may expand
    or change
    scientific
    judgments
    regarding
    which information
    is
    useful
    for mode
    of
    action
    determinations.
    As warranted,
    additional
    guidance
    may be proposed
    as
    experience
    is gained
    andlor as
    toxicological
    knowledge
    advances.
    2.5.
    WEIGHT
    OF
    EVIDENCE
    NARRATIVE
    The weight
    ofevidence
    narrative
    is
    a
    short
    summary
    (one
    to two
    pages)
    that
    explains
    an
    agent’s
    human carcinogenic
    potential and
    the
    conditions
    that characterize
    its expression.
    It
    should be
    sufficiently
    complete
    to
    be
    able
    to
    stand
    alone,
    highlighting
    the
    key
    issues
    and
    decisions
    that were
    the
    basis
    for
    the evaluation
    of the
    agent’s potential
    hazard.
    It
    should
    be
    sufficiently
    clear
    and transparent
    to
    be useful to
    risk
    managers
    and non-expert
    readers.
    It
    may
    be
    useful to
    summarize
    all
    of the significant
    components
    and
    conclusions
    in the
    first paragraph
    of
    the
    narrative and
    to
    explain complex
    issues in
    more depth
    in
    the
    rest
    of the
    narrative.
    2-49

    The
    weight
    of
    the
    evidence
    should
    be
    presented
    as
    a
    narrative
    laying
    out
    the
    complexity
    of
    information
    that
    is
    essential
    to
    understanding
    the
    hazard
    and
    its
    dependence
    on
    the
    quality,
    quantity,
    and
    type(s)
    of
    data
    available,
    as
    well
    as
    the
    circumstances
    of
    exposure
    or
    the
    traits
    of
    an
    exposed
    population
    that
    may
    be
    required
    for
    expression
    of
    cancer.
    For
    example,
    the
    narrative
    can
    clearly
    state
    to
    what
    extent
    the
    determination
    was
    based
    on
    data
    from
    human
    exposure,
    from
    animal
    experiments,
    from
    some
    combination
    of
    the
    two,
    or
    from
    other
    data.
    Similarly,
    information
    on
    mode
    of
    action
    can
    specify
    to
    what
    extent
    the
    data
    are
    from
    in
    vivo
    or
    in
    vitro
    exposures
    or
    based
    on
    similarities
    to
    other
    chemicals.
    The
    extent
    to
    which
    an
    agent’s
    mode
    of
    action
    occurs
    only
    on
    reaching
    a
    minimum
    dose
    or
    a
    minimum
    duration
    should
    also
    be
    presented.
    A
    hazard
    might
    also
    be
    expressed
    disproportionately
    in
    individuals
    possessing
    a
    specific
    gene;
    such
    characterizations
    may
    follow
    from
    a
    better
    understanding
    of
    the
    human
    genome.
    Furthermore,
    route
    of
    exposure
    should
    be
    used
    to
    qualify
    a
    hazard
    if,
    for
    example,
    an
    agent
    is
    not
    absorbed
    by
    some
    routes.
    Similarly,
    a
    hazard
    can
    be
    attributable
    to
    exposures
    during
    a
    susceptible
    lifestage
    on
    the
    basis
    of
    our
    understanding
    of
    human
    development.
    The
    weight
    of
    evidence-of-evidence
    narrative
    should
    highlight:
    the
    quality
    and
    quantity
    of
    the
    data;
    all
    key
    decisions
    and
    the
    basis
    for
    these
    major
    decisions;
    and
    any
    data,
    analyses,or
    assumptions
    that
    are
    unusual
    for
    or
    new
    to
    EPA.
    To
    capture
    this
    complexity,
    a
    weight
    of
    evidence
    narrative
    generally
    includes
    conclusions
    about
    human
    carcinogenic
    potential
    (choice
    of
    descriptor(s),
    described
    below),
    2-50

    a summary of the
    key
    evidence
    supporting
    these
    conclusions
    (for each
    descriptor
    used),
    including
    information
    on
    the
    type(s)
    of
    data
    (human
    and/or
    animal,
    in
    vivo
    and/or
    in vitro)
    used
    to
    support
    the
    conclusion(s),
    available
    information
    on
    the
    epidemiologic
    or
    experimental
    conditions
    that
    characterize
    expression
    of carcinogenicity
    (e.g.,
    if
    carcinogenicity
    is
    possible
    only
    by
    one
    exposure
    route
    or only
    above
    a
    certain
    human
    exposure
    level),
    a summary
    of
    potential
    modes
    of action
    and
    how they
    reinforce
    the
    conclusions,
    indications
    of any
    susceptible
    populations
    or
    lifestages,
    when
    available,
    and
    a summary
    of
    the key
    default
    options
    invoked
    when
    the
    available
    information
    is
    inconclusive.
    To
    provide
    some
    measure
    of
    clarity
    and
    consistency
    in an
    otherwise
    free-form
    narrative,
    the
    weight
    of
    evidence
    descriptors
    are
    included
    in
    the
    first
    sentence
    of the
    narrative.
    Choosing
    a
    descriptor
    is
    a
    matter
    ofjudgment
    and
    cannot
    be
    reduced
    to
    a formula.
    Each descriptor
    may
    be
    applicable
    to
    a wide
    variety
    of potential
    data
    sets and
    weights
    of
    evidence.
    These
    descriptors
    and
    narratives
    are
    intended
    to
    permit
    sufficient
    flexibility
    to accommodate
    new
    scientific
    understanding
    and
    new
    testing
    methods
    as
    they are
    developed
    and
    accepted
    by the
    scientific
    community
    and the
    public.
    Descriptors
    represent
    points
    along
    a
    continuum
    of
    evidence;
    consequently, there
    are
    gradations
    and borderline
    cases
    that
    are
    clarified
    by
    the full
    narrative.
    Descriptors, as
    well
    as an
    introductory
    paragraph,
    are a
    short
    summary
    of
    the
    complete
    narrative
    that
    preserves
    the
    complexity
    that
    is an
    essential
    part
    of the
    hazard
    characterization.
    Users
    of
    these
    cancer
    guidelines
    and
    of the
    risk
    assessments
    that
    result
    from
    the
    use
    of these
    cancer
    guidelines
    should
    consider
    the
    entire
    range
    of information
    included
    in
    the
    narrative
    rather
    than
    focusing
    simply
    on
    the
    descriptor.
    2-51

    In
    borderline
    cases, the
    narrative
    explains
    the
    case
    for choosing
    one descriptor
    and
    discusses
    the
    arguments
    for considering
    but not
    choosing
    another.
    For
    example,
    between
    “suggestive”
    and
    “likely”
    or
    between
    “suggestive”
    and
    “inadequate,”
    the
    explanation
    clearly
    communicates
    the
    information
    needed
    to
    consider
    appropriately
    the
    agents
    carcinogenic
    potential
    in
    subsequent
    decisions.
    Multiple
    descriptors
    can be
    used for
    a single
    agent,
    for
    example,
    when
    carcinogenesis
    is
    dose-
    or route-dependent.
    For
    example,
    if an
    agent
    causes
    point-of-contact
    tumors
    by
    one
    exposure
    route
    but
    adequate
    testing
    is negative
    by
    another
    route,
    then
    the agent
    could
    be
    described
    as
    likely
    to be carcinogenic
    by the
    first
    route but
    not
    likely to
    be carcinogenic
    by
    the
    second.
    Another
    example
    is when
    the mode
    of action
    is
    sufficiently
    understood
    to conclude
    that
    a
    key event
    in
    tumor
    development
    would
    not occur
    below
    a certain
    dose
    range.
    In
    this
    case,
    the
    agent could
    be
    described
    as likely
    to be
    carcinogenic
    above
    a certain
    dose
    range
    but not
    likely
    to
    be carcinogenic
    below
    that range.
    Descriptors
    can be
    selected
    for an
    agent
    that
    has
    not
    been tested
    in
    a cancer
    bioassay
    if
    sufficient
    other
    information,
    e.g., toxicokinetic
    and
    mode
    of
    action
    information,
    is available
    to
    make
    a strong,
    convincing,
    and logical
    case
    through
    scientific
    inference.
    For
    example,
    if
    an
    agent
    is one of
    a well-defined
    class of
    agents
    that are
    understood
    to operate
    through
    a
    common
    mode
    of
    action
    and
    if that agent
    has
    the
    same
    mode
    of
    action, then
    in
    the
    narrative
    the
    untested
    agent would
    have
    the same
    descriptor
    as the class.
    Another
    example
    is when
    an untested
    agent’s
    effects
    are
    understood
    to be caused
    by
    a human
    metabolite,
    in which
    case
    in
    the
    narrative
    the
    untested
    agent
    could
    have
    the
    same
    descriptor
    as
    the metabolite.
    As
    new
    testing
    methods
    are
    developed
    and
    used,
    assessments
    may
    increasingly
    be
    based
    on inferences
    from
    toxicokinetic
    and
    mode
    of
    action
    information
    in
    the
    absence
    of tumor
    studies
    in animals
    or
    humans.
    When
    a
    well-studied
    agent produces
    tumors
    only
    at a
    point
    of
    initial
    contact,
    the
    descriptor
    generally
    applies
    only
    to
    the
    exposure
    route
    producing
    tumors
    unless
    the mode
    of
    action
    is
    relevant
    to other
    routes.
    The
    rationale
    for
    this conclusion
    would
    be
    explained
    in
    the
    narrative.
    W]aen
    tumors
    occur
    at a site
    other than
    the
    point
    of initial
    contact,
    the
    descriptor
    generally
    applies
    to
    all
    exposure
    routes that
    have
    not been
    adequately
    tested
    at
    sufficient
    doses.
    An
    2-52

    exception
    occurs
    when
    there
    is
    convincing
    information,
    e.g.,
    toxicokinetic
    data
    that absorption
    does
    not
    occur
    by
    another
    route.
    When
    the
    response
    differs
    qualitatively
    as well
    as quantitatively
    with dose,
    this
    information
    should
    be part
    of the
    characterization
    of the
    hazard.
    In
    some
    cases
    reaching
    a
    certain
    dose range
    can
    be a precondition
    for effects
    to
    occur,
    as when
    cancer
    is secondary
    to
    another
    toxic
    effect that
    appears
    only
    above
    a certain
    dose.
    In other
    cases
    exposure
    duration
    can be
    a
    precondition
    for hazard
    if effects
    occur
    only after
    exposure
    is
    sustained
    for a
    certain
    duration.
    These
    considerations
    differ
    from
    the issues
    of relative
    absorption
    or
    potency
    at different
    dose
    levels
    because
    they
    may
    represent
    a discontinuity
    in
    a
    dose-response
    function.
    When
    multiple
    bioas
    says
    are
    inconclusive,
    mode of
    action
    data are
    likely
    to hold
    the
    key
    to resolution
    of
    the more
    appropriate
    descriptor.
    When
    bioas
    says
    are few,
    further
    bioassays
    to
    replicate
    a study’s
    results
    or to
    investigate
    the
    potential
    for effects
    in
    another
    sex, strain,
    or
    species
    may
    be
    useful.
    When
    there are
    few pertinent
    data, the
    descriptor
    makes
    a statement
    about
    the
    database,
    for
    example,
    “Inadequate
    Information
    to
    Assess
    Carcinogenic
    Potential,”
    or
    a database
    that
    provides
    “Suggestive
    Evidence
    of
    Carcinogenic
    Potential.”
    With
    more information,
    the
    descriptor
    expresses
    a conclusion
    about
    the
    agent’s
    carcinogenic
    potential
    to
    humans.
    If the
    conclusion
    is
    positive,
    the
    agent
    could
    be
    described
    as
    “Likely
    to Be
    Carcinogenic
    to
    Humans”
    or,
    with strong
    evidence,
    “Carcinogenic
    to
    Humans.”
    If the
    conclusion
    is
    negative,
    the
    agent
    could
    be
    described
    as “Not
    Likely
    to Be
    Carcinogenic
    to
    Humans.”
    Although
    the term
    “likely”
    can
    have a probabilistic
    connotation
    in
    other contexts,
    its
    use
    as
    a
    weight
    of
    evidence
    descriptor
    does
    not
    correspond
    to
    a quantifiable
    probability
    of
    whether
    the
    chemical
    is
    carcinogenic.
    This is
    because
    the
    data
    that
    support
    cancer
    assessments
    generally
    are not
    suitable
    for
    numerical
    calculations
    of the
    probability
    that
    an agent
    is a
    carcinogen.
    Other
    health
    agencies
    have expressed
    a comparable
    weight of
    evidence
    using
    terms
    such
    as
    “Reasonably Anticipated
    to Be a
    Human
    Carcinogen”
    (NTP)
    or
    “Probably
    Carcinogenic
    to
    Humans”
    (International
    Agency
    for Research
    on Cancer).
    The
    following
    descriptors
    can
    be used
    as an
    introduction
    to
    the weight
    of evidence
    narrative.
    The
    examples
    presented
    in the
    discussion
    of the
    descriptors
    are illustrative.
    The
    2-53

    examples
    are
    neither
    a
    checklist
    nor
    a limitation
    for
    the descriptor.
    The
    complete
    weight
    of
    evidence
    narrative,
    rather
    than
    the
    descriptor
    alone,
    provides
    the
    conclusions
    and
    the
    basis
    for
    them.
    “Carcinogenic
    to
    Humans”
    This
    descriptor
    indicates
    strong
    evidence
    of
    human
    carcinogenicity.
    It
    covers
    different
    combinations
    of evidence.
    This
    descriptor
    is
    appropriate
    when
    there
    is
    convincing
    epidemiologic
    evidence
    of
    a
    causal
    association
    between
    human
    exposure
    and cancer.
    Exceptionally,
    this
    descriptor
    may
    be
    equally
    appropriate
    with
    a lesser
    weight
    of
    epidemiologic
    evidence
    that
    is strengthened
    by other
    lines
    of
    evidence.
    It can
    be
    used
    when
    of
    the
    following
    conditions
    are
    met:
    (a)
    there
    is
    strong
    evidence
    of
    an
    association
    between
    human
    exposure
    and
    either
    cancer
    or
    the
    key
    precursor
    events
    of the
    agent’s
    mode
    of
    action
    but
    not enough
    for a
    causal
    association,
    (b) there
    is extensive
    evidence
    of
    carcinogenicity
    in animals,
    (c)
    the
    mode(s)
    of
    carcinogenic
    action
    and
    associated
    key
    precursor
    events
    have
    been
    identified
    in
    animals,
    and
    (d) there
    is
    strong
    evidence
    that
    the
    key
    precursor
    events
    that
    precede
    the
    cancer
    response
    in animals
    are
    anticipated
    to occur
    in humans
    and
    progress
    to
    tumors,
    based
    on
    available
    biological
    information.
    In
    this
    case,
    the
    narrative
    includes
    a summary
    of both
    the
    experimental
    and
    epidemiologic
    information
    on
    mode
    of action
    and
    also
    an
    indication
    of
    the relative
    weight
    that
    each
    source
    of
    information
    carries,
    e.g.,
    based
    on
    human
    information,
    based
    on
    limited
    human
    and
    extensive
    animal
    experiments.
    “Likely
    to
    Be
    Carcinogenic
    to Humans”
    This
    descriptor
    is appropriate
    when
    the weight
    of the
    evidence
    is
    adequate
    to
    demonstrate
    carcinogenic
    potential
    to
    humans
    but
    does
    not reach
    the
    weight
    of evidence
    for
    the descriptor
    2-54

    “Carcinogenic
    to Humans.”
    Adequate
    evidence
    consistent
    with
    this descriptor
    covers
    a broad
    spectrum.
    As
    stated
    previously,
    the
    use
    of the
    term
    “likely”
    as
    a
    weight
    of
    evidence
    descriptor
    does
    not correspond
    to a quantifiable
    probability.
    The
    examples
    below
    are meant
    to represent
    the
    broad
    range
    of data
    combinations
    that
    are
    covered
    by
    this
    descriptor;
    they
    are
    illustrative
    and
    provide
    neither
    a checklist
    nor a
    limitation
    for the
    data
    that
    might
    support
    use
    of
    this
    descriptor.
    Moreover,
    additional
    information,
    e.g.,
    on
    mode
    of
    action,
    might
    change
    the choice
    of descriptor
    for
    the illustrated
    examples.
    Supporting
    data for
    this descriptor
    may
    include:
    an agent
    demonstrating
    a plausible
    (but
    not definitively
    causal)
    association
    between
    human
    exposure
    and
    cancer,
    in most
    cases with
    some
    supporting
    biological,
    experimental
    evidence,
    though
    not
    necessarily
    carcinogenicity
    data
    from
    animal
    experiments;
    an agent
    that
    has
    tested
    positive
    in
    animal
    experiments
    in more
    than
    one
    species,
    sex,
    strain,
    site,
    or
    exposure
    route,
    with or
    without
    evidence
    of
    carcinogenic
    ity
    in
    humans;
    a
    positive
    tumor
    study
    that
    raises additional
    biological
    concerns
    beyond
    that
    of a
    statistically
    significant
    result,
    for example,
    a
    high
    degree
    of
    malignancy,
    or
    an
    early
    age at
    onset;
    a
    rare animal
    tumor
    response
    in a
    single
    experiment
    that
    is assumed
    to be
    relevant
    to
    humans;
    or
    a
    positive
    tumor
    study
    that
    is strengthened
    by other
    lines
    of evidence,
    for example,
    either
    plausible
    (but
    not definitively
    causal)
    association
    between
    human
    exposure
    and
    cancer
    evidence
    that
    the
    agent or
    an
    important
    metabolite
    causes
    events
    generally
    known
    to be
    associated
    with
    tumor
    formation
    (such
    as DNA
    reactivity
    or
    effects
    on
    cell growth
    control)
    likely
    to be
    related
    to
    the
    tumor response
    in this
    case.
    2-55

    “Suggestive Evidence
    of
    Carcinogenic
    Potential”
    This
    descriptor
    of the
    database
    is
    appropriate
    when
    the
    weight
    of
    evidence
    is
    suggestive
    of
    carcinogenicity;
    a
    concern
    for
    potential
    carcinogenic
    effects
    in
    humans
    is raised,
    but
    the
    data
    are
    judged
    not
    sufficient
    for a
    stronger
    conclusion.
    This
    descriptor
    covers
    a spectntm
    of
    evidence
    associated
    with
    varying
    levels
    of
    concern
    for
    carcinogenicity,
    ranging
    from
    a positive
    cancer
    result
    in
    the
    only
    study
    on
    an agent
    to
    a
    single
    positive
    cancer
    result
    in an
    extensive
    database
    that
    includes
    negative
    studies
    in other
    species.
    Depending
    on
    the
    extent
    of the
    database,
    additional
    studies
    may
    or may
    not
    provide
    further
    insights.
    Some
    examples
    include:
    a small,
    and possibly
    not
    statistically
    significant,
    increase
    in tumor
    incidence
    observed
    in
    a
    single
    animal
    or
    human
    study
    that
    does
    not
    reach
    the
    weight
    of
    evidence
    for the
    descriptor
    “Likely
    to Be
    Carcinogenic
    to Humans.’
    The
    study
    generally
    would
    not
    be
    contradicted
    by
    other
    studies
    of equal
    quality
    in the
    same
    population
    group
    or
    experimental
    system
    (see
    discussions
    of
    conflicting
    evidence
    and
    differing
    results,
    below);
    a small
    increase
    in a
    tumor
    with
    a high
    background
    rate
    in
    that
    sex and
    strain,
    when
    there
    is some
    but
    insufficient
    evidence
    that the
    observed
    tumors
    may
    be
    due
    to
    intrinsic
    factors
    that
    cause
    background
    tumors
    and
    not
    due
    to the
    agent
    being
    assessed.
    (When
    there
    is a
    high
    background
    rate
    of
    a specific
    tumor
    in
    animals
    of
    a
    particular
    sex
    and
    strain,
    then
    there
    may
    be biological
    factors
    operating
    independently
    of
    the
    agent
    being
    assessed
    that
    could
    be
    responsible
    for
    the
    development
    of
    the
    observed
    tumors.)
    In
    this
    case, the
    reasons
    for determining
    that
    the tumors
    are not
    due
    to the
    agent
    are explained;
    evidence
    of
    a positive
    response
    in a
    study
    whose
    power,
    design,
    or
    conduct
    limits
    the
    ability
    to
    draw
    a
    confident
    conclusion
    (but
    does
    not
    make
    the
    study
    fatally
    2-56

    flawed),
    but
    where
    the carcinogenic
    potential
    is
    strengthened
    by other
    lines
    of
    evidence
    (such
    as structure-activity
    relationships);
    or
    a
    statistically
    significant
    increase
    at
    one
    dose
    only,
    but
    no
    significant
    response
    at
    the
    other
    doses
    and
    no
    overall
    trend.
    “Inadequate
    Information
    to
    Assess
    Carcinogenic
    Potential”
    This
    descriptor
    of
    the
    database
    is appropriate
    when
    available
    data
    are
    judged
    inadequate
    for
    applying
    one
    of
    the other
    descriptors.
    Additional
    studies
    generally
    would
    be
    expected
    to
    provide
    further
    insights.
    Some
    examples
    include:
    little
    or no
    pertinent
    information;
    conflicting
    evidence,
    that
    is,
    some
    studies
    provide
    evidence
    of carcinogenicity
    but
    other
    studies
    of
    equal
    quality
    in
    the
    same
    sex and
    strain
    are
    negative.
    Differing
    results,
    that
    is, positive
    results
    in some
    studies
    and
    negative
    results
    in one
    or
    more
    different
    experimental
    systems,
    do not
    constitute
    conflicting
    evidence,
    as
    the
    term
    is
    used
    here.
    Depending
    on
    the
    overall
    weight
    of
    evidence,
    differing
    results
    can
    be
    considered
    either
    suggestive
    evidence
    or
    likely
    evidence;
    or
    negative
    results
    that
    are
    not sufficiently
    robust
    for
    the
    descriptor,
    “Not
    Likely
    to
    Be
    Carcinogenic
    to Humans.”
    “Not
    Likely
    to
    Be
    Carcinogenic
    to
    Humans”
    This
    descriptor
    is
    appropriate
    when
    the
    available
    data
    are considered
    robust
    for
    deciding
    that
    there
    is no
    basis
    for
    human
    hazard
    concern.
    In
    some
    instances,
    there
    can
    be
    positive
    results
    in
    experimental animals
    when
    there
    is
    strong,
    consistent
    evidence
    that
    each
    mode
    of action
    in
    experimental animals
    does
    not operate
    in
    humans.
    In
    other
    cases,
    there
    can be
    convincing
    2-57

    evidence
    in both
    humans
    and
    animals
    that
    the agent
    is
    not
    carcinogenic.
    The
    judgment
    may
    be
    based
    on
    data
    such
    as:
    animal
    evidence
    that
    demonstrates
    lack
    of carcinogenic
    effect
    in
    both
    sexes
    in
    well-
    designed
    and
    well-conducted
    studies
    in
    at least
    two
    appropriate
    animal
    species
    (in
    the
    absence
    of other
    animal
    or human
    data
    suggesting
    a
    potential
    for cancer
    effects),
    convincing
    and
    extensive
    experimental
    evidence
    showing
    that
    the only
    carcinogenic
    effects
    observed
    in animals
    are
    not
    relevant
    to
    humans,
    convincing
    evidence
    that
    carcinogenic
    effects
    are
    not
    likely
    by
    a
    particular
    exposure
    route
    (see
    Section
    2.3), or
    convincing
    evidence
    that
    carcinogenic
    effects
    are
    not
    likely
    below
    a defined
    dose
    range.
    A
    descriptor
    of
    “not
    likely”
    applies
    only
    to the
    circumstances
    supported
    by
    the
    data.
    For
    example,
    an agent
    may
    be “Not
    Likely
    to
    Be Carcinogenic”
    by
    one
    route
    but not
    necessarily
    by
    another.
    In
    those
    cases
    that
    have
    positive
    animal
    experiment(s)
    but
    the
    results
    are
    judged
    to
    be
    not relevant
    to
    humans,
    the
    narrative
    discusses
    why
    the
    results
    are not
    relevant.
    Multzple
    Descriptors
    More
    than
    one
    descriptor
    can be
    used
    when
    an
    agent’s
    effects
    differ
    by
    dose
    or
    exposure
    route.
    For
    example,
    an agent
    may
    be
    “Carcinogenic
    to
    Humans”
    by
    one
    exposure
    route
    but
    “Not
    Likely
    to
    Be
    Carcinogenic”
    by
    a route
    by
    which
    it is
    not absorbed.
    Also,
    an agent
    could
    be
    “Likely
    to Be
    Carcinogenic”
    above
    a specified
    dose
    but
    “Not
    Likely
    to
    Be
    Carcinogenic”
    below
    that
    dose because a key
    event
    in tumor
    fonnation
    does
    not
    occur
    below
    that
    dose.
    2-58

    2.6. HAZARD CHARACTERIZATION
    The
    hazard
    characterization
    contains
    the
    hazard
    information
    needed
    for
    a full
    risk
    characterization
    (U.S.
    EPA,
    2000b).
    It
    presents
    the
    results
    of
    the hazard
    assessment
    and
    explains
    how
    the
    weight
    of
    evidence
    conclusion was
    reached.
    The
    hazard
    characterization
    summarizes,
    in
    plain
    language, conclusions
    about
    the agent’s
    potential
    effects,
    whether
    they
    can be
    expected
    to
    depend
    qualitatively
    on
    the
    circumstances
    of
    exposure,
    and if
    anyone
    can
    be
    expected
    to
    be
    especially
    susceptible.
    It discusses
    the
    extent
    to
    which
    these
    conclusions
    are
    supported
    by
    data
    or
    are the
    result
    of
    default
    options
    invoked
    because
    the
    data
    are
    inconclusive.
    It
    explains
    how
    complex
    cases
    with
    differing
    results
    in
    different
    studies
    were
    resolved.
    The
    hazard
    characterization
    highlights
    the major
    issues
    addressed
    in
    the
    hazard
    assessment
    and
    discusses
    alternative
    interpretations of
    the
    data
    and
    the
    degree
    to
    which
    they
    are supportable
    scientifically
    and
    are
    consistent
    with
    EPA
    guidelines.
    When
    the
    conclusion
    is
    supported
    by
    mode
    of
    action
    information,
    the hazard
    characterization
    also
    provides
    a
    clear summary
    of
    the mode
    of
    action
    conclusions
    (see Section
    2.4.3.4),
    including
    the completeness
    of the
    data,
    the
    strengths
    and
    limitations
    of
    the
    inferences
    made,
    the
    potential
    for
    other
    modes
    of
    action,
    and
    the
    implications
    of
    the mode
    of
    action
    for
    selecting
    viable
    approaches
    to
    the dose-response
    assessment.
    The
    hazard
    characterization
    also
    discusses
    the extent
    to
    which
    mode
    of
    action
    information
    is
    available
    to address
    the
    potential
    for
    disproportionate
    risks
    in specific
    populations
    or lifestages
    or
    the potential
    for
    enhanced
    risks
    on
    the
    basis
    of
    interactions
    with
    other
    agents
    or stressors,
    if
    anticipated.
    Topics
    that
    can
    be
    addressed
    in
    a
    hazard
    characterization
    include:
    summary
    of
    the
    results
    of
    the hazard
    assessment;
    identification
    of
    any
    likely
    susceptible
    populations
    and
    lifestages,
    especially
    attending
    to
    children,
    infants,
    and
    fetuses;
    conclusions
    about
    the agent’s
    mode
    of
    action,
    and
    implications
    for
    selecting
    approaches
    to
    the
    dose-response
    assessment;
    2-59

    identification
    of
    the
    available
    lines
    of
    evidence
    (e.g.,
    animal
    bioassays,
    epidemiologic
    studies,
    toxicokinetic
    information,
    mode
    of
    action
    studies,
    and
    information
    about
    structural
    analogues
    or
    metabolites),
    highlighting
    data
    quality
    and
    coherence
    of
    results
    from
    different
    lines
    of
    evidence;
    and
    strengths
    and
    limitations
    of
    the
    hazard
    assessment,
    highlighting
    significant
    issues
    in
    interpreting
    the
    data,
    alternative
    interpretations
    that
    are
    considered
    equally
    plausible,
    critical
    data
    gaps,
    and
    default
    options
    invoked
    when
    the
    available
    information
    is
    inconclusive.
    2-60

    3.
    DOSE-RESPONSE
    ASSESSMENT
    Dose-response assessment
    estimates
    potential
    risks
    to
    humans
    at exposure
    levels
    of
    interest.
    Dose-response
    assessments
    are
    useful
    in
    many
    applications:
    estimating
    risk
    at different
    exposure
    levels,
    estimating
    the
    risk
    reduction
    for
    different
    decision
    options,
    estimating
    the
    risk
    remaining
    after
    an
    action
    is taken,
    providing
    the
    risk
    information
    needed
    for
    benefit-cost
    analyses
    of different
    decision
    options,
    comparing
    risks
    across
    different
    agents
    or
    health effects,
    and
    setting
    research
    priorities.
    The
    purpose
    of the
    assessment
    should
    consider
    the
    quality
    of the data
    available,
    which
    will
    vary
    from
    case
    to
    case.
    A
    dose-response
    analysis
    is
    generally
    developed
    from
    each
    study
    that
    reports
    quantitative
    data on
    dose
    and response.
    Alternative
    measures
    of
    dose
    are
    available
    for analyzing
    human
    and
    animal
    studies
    (see Section
    3.1).
    A
    two-step
    approach
    distinguishes
    analysis
    of
    the
    dose-
    response
    data
    from
    inferences
    made about
    lower doses.
    The
    first
    step
    is an
    analysis
    of dose
    and
    response
    in the
    range
    of
    observation
    of the
    experimental
    or epidemiologic
    studies
    (see Section
    3.2).
    Modeling
    is encouraged
    to incorporate
    a
    wide
    range
    of experimental
    data
    into
    the dose-
    response
    assessment
    (see
    Sections
    3.1.2,
    3.2.1,
    3.2.2, 3.2.3).
    The
    modeling
    yields
    a point of
    departure
    (POD)
    near the
    lower
    end of
    the
    observed
    range,
    without
    significant
    extrapolation
    to
    lower
    doses
    (see Sections
    3.2.4,
    3.2.5).
    The
    second
    step
    is extrapolation
    to lower
    doses
    (see
    Section
    3.3).
    The
    extrapolation
    approach
    considers
    what
    is
    known
    about the
    agent’s
    mode
    of
    action
    (see Section
    3.3.1).
    Both
    linear
    and nonlinear
    approaches
    are
    available
    (see Sections
    3.3.3,
    3.3.4).
    When
    multiple
    estimates
    can
    be developed,
    the strengths
    and
    weaknesses
    of each
    are presented.
    In
    some cases,
    they
    may
    be combined
    in
    a way
    that
    best
    represents
    human
    cancer
    risk
    (see Section
    3.3.5).
    Special
    consideration
    is given
    to describing
    dose-response
    differences
    attributable
    to
    different
    human
    exposure
    scenarios
    (see
    Section
    3.4)
    and
    to
    susceptible
    populations
    and
    lifestages
    (see
    Section
    3.5).
    It
    is
    important
    to
    discuss
    significant
    uncertainties
    encountered
    in
    the
    analysis
    (see
    Section
    3.6) and
    to
    characterize
    other
    important
    aspects
    of the
    dose-response
    assessment
    (see Section
    3.7).
    The
    scope,
    depth,
    and use
    of a dose-response
    assessment
    vary
    in different
    circumstances.
    Although
    the
    quality
    of
    dose-response
    data
    is not necessarily
    related
    to
    the
    weight
    of
    evidence
    3-1

    descriptor,
    dose-response
    assessments
    are
    generally
    completed
    for
    agents
    considered
    “Carcinogenic
    to
    Humans”
    and
    “Likely
    to Be
    Carcinogenic
    to Humans.”
    When
    there
    is
    suggestive
    evidence,
    the Agency
    generally
    would
    not
    attempt
    a dose-response
    assessment,
    as
    the
    nature
    of the
    data
    generally
    would
    not
    support
    one;
    however,
    when
    the evidence
    includes
    a
    well-
    conducted
    study,
    quantitative
    analyses
    may
    be useful
    for
    some
    purposes,
    for
    example,
    providing
    a
    sense of
    the
    magnitude
    and uncertainty
    of potential
    risks,
    ranking
    potential
    hazards,
    or
    setting
    research
    priorities.
    In
    each
    case,
    the rationale
    for
    the quantitative
    analysis
    is
    explained,
    considering
    the
    uncertainty
    in the
    data
    and
    the suggestive
    nature
    of
    the
    weight
    of evidence.
    These
    analyses
    generally
    would
    not
    be
    considered
    Agency
    consensus
    estimates.
    Dose-response
    assessments
    are
    generally
    not
    done when
    there
    is inadequate
    evidence,
    although
    calculating
    a
    bounding
    estimate
    from
    an
    epidemiologic
    or
    experimental
    study
    that does
    not show
    positive
    results
    can
    indicate
    the study’s
    level
    of sensitivity
    and capacity
    to detect
    risk
    levels
    of concern.
    Cancer
    is a
    collection
    of
    several
    diseases
    that
    develop
    through
    cell and
    tissue
    changes
    over time.
    Dose-response
    assessment
    procedures
    based
    on tumor
    incidence
    have
    seldom
    taken
    into
    account
    the
    effects
    of
    key precursor
    events
    within
    the whole
    biological
    process
    due
    to lack
    of
    empirical
    data
    and
    understanding
    about
    these
    events.
    In
    this
    discussion,
    response
    data
    include
    measures
    of key
    precursor
    events
    considered
    integral
    to
    the carcinogenic
    process
    in addition
    to
    tumor
    incidence.
    These
    responses
    may
    include
    changes
    in DNA,
    chromosomes,
    or other
    key
    macromolecules;
    effects
    on
    growth
    signal transduction,
    including
    induction
    of
    hormonal
    changes;
    or
    physiological
    or toxic
    effects
    that
    include
    proliferative
    events
    diagnosed
    as
    precancerous but
    not
    pathology
    that is
    judged
    to
    be
    cancer.
    Analysis
    of
    such responses
    may
    be
    done
    along
    with
    that
    of tumor
    incidence
    to
    enhance
    the
    tumor dose-response
    analysis.
    If
    dose-
    response
    analysis
    of
    nontumor
    key
    events
    is
    more
    informative
    about
    the carcinogenic
    process
    for
    an
    agent,
    it can
    be used
    in
    lieu
    of,
    or in
    conjunction
    with, tumor
    incidence
    analysis
    for
    the overall
    dose-response assessment.
    As
    understanding
    of mode
    of action
    improves
    and new
    types
    of data
    become
    available,
    dose-response assessment
    will
    continue
    to
    evolve.
    These
    cancer
    guidelines
    encourage
    the
    development
    and
    application
    of
    new methods
    that
    improve
    dose-response
    assessment
    by
    reflecting
    new
    scientific
    understanding
    and
    new sources
    of information.
    3-2

    3.1.
    ANALYSIS
    OF
    DOSE
    For
    each
    effect
    observed,
    dose-response
    assessment
    should
    begin
    by
    determining
    an
    appropriate
    dose
    metric.
    Several
    dose
    metrics
    have
    been
    used,
    e.g.,
    delivered
    dose,
    body
    burden,
    and
    area
    under
    the curve,
    and others
    may be
    appropriate
    depending
    on
    the data
    and
    mode
    of
    action.
    Selection
    of an
    appropriate
    dose
    metric
    considers
    what
    data
    are available
    and
    what
    is
    known
    about
    the
    agent’s
    mode
    of
    action
    at
    the target
    site,
    and
    uncertainties
    involved
    in
    estimation
    and
    application
    of
    alternative
    metrics.
    The
    dose
    metric
    specifies:
    the
    agent
    measured,
    preferably
    the
    active
    agent
    (administered
    agent
    or
    a
    metabolite);
    proximity
    to
    the
    target
    site
    (exposure
    concentration,
    potential
    dose,
    internal
    dose,
    or
    delivered
    dose,
    5
    reflecting
    increasing
    proximity);
    and
    the
    time
    component
    of the
    effective
    dose
    (cumulative
    dose,
    average
    dose,
    peak
    dose,
    or body
    burden).
    Analyses
    can
    be
    based
    on
    estimates
    of
    animal
    dose
    metrics
    or
    human
    dose
    metrics.
    The
    assessment
    should
    describe
    the
    approach
    used
    to
    select
    a
    dose
    metric
    and the
    reasons
    for
    this
    approach.
    The
    final
    analysis,
    however,
    should
    determine
    a human
    equivalent
    dose metric.
    This
    facilitates
    comparing results
    from
    different
    datasets
    and
    effects
    by
    using
    human
    equivalent
    dose/concentrations
    as
    common
    metrics.
    When
    appropriate,
    it may
    be
    necessary
    to convert
    dose
    metrics
    across
    exposure
    routes.
    When
    route-to-route
    extrapolations
    are made,
    the
    underlying
    data,
    algorithms,
    and
    assumptions
    are
    clearly
    described.
    Exposure
    is contact
    of
    an
    agent
    with
    the
    outer
    boundary
    of
    an organism.
    Exposure
    concentration
    is
    the
    concentration
    of
    a
    chemical
    in its
    transport
    or carrier
    medium
    at
    the
    point of
    contact.
    Dose
    is
    the amount
    of
    a
    substance
    available
    for
    interaction
    with
    metabolic
    processes
    or
    biologically
    significant
    receptors
    after crossing
    the
    outer
    boundary
    of
    an organism.
    Potential
    dose
    is
    the
    amount
    ingested,
    inhaled,
    or applied
    to the
    skin.
    Applied
    dose
    is the
    amount
    of
    a substance
    presented
    to an
    absorption
    barrier
    and
    available
    for
    absorption
    (although
    not
    necessarily
    having
    yet
    crossed
    the outer
    boundary
    of the
    organism).
    Absorbed
    dose
    is
    the
    amount
    crossing
    a specific
    absorption
    barrier
    (e.g.,
    the
    exchange
    boundaries
    of
    skin, lung,
    and digestive
    tract)
    through
    uptake
    processes.
    Internal
    dose
    is a
    more
    general
    term,
    used
    without
    respect
    to
    specific
    absorption
    barriers
    or
    exchange
    boundaries.
    Delivered
    dose
    is
    the
    amount
    of
    the
    chemical
    available
    for interaction
    by
    any
    particular
    organ
    or cell
    (U.S. EPA,
    1992a).
    3-3

    Timing
    of exposure
    can
    also
    be
    important.
    When
    there
    is
    a susceptible
    lifestage,
    doses
    during
    the
    susceptible period
    are
    not
    equivalent
    to doses
    at
    other
    times,
    and
    they
    would
    be
    analyzed
    separately.
    3.1.1.
    Standardizing
    Different
    Experimental
    Exposure
    Regimens
    Complex
    exposure
    or dosing
    regimens
    are
    often
    present
    in
    experimental
    and
    epidemiologic
    studies.
    The
    resulting
    internal
    dose
    depends
    on
    many
    variables,
    including
    concentration,
    duration, frequency
    of
    administration,
    and
    duration
    of recovery
    periods
    between
    administrations.
    Internal
    dose also
    depends
    on
    variables
    that
    are intrinsic
    to
    the exposed
    individual,
    such
    as
    lifestage
    and
    rates
    of
    metabolism
    and clearance.
    To
    facilitate
    comparing
    results
    from
    different
    study
    designs
    and
    to
    make
    inferences
    about
    human
    exposures,
    a
    summary
    estimate
    of
    the dose
    metric,
    whether
    the
    administered
    dose
    or inhalation
    exposure
    concentration
    or
    an internal
    metric,
    may be
    derived
    for
    a complex
    exposure
    regimen.
    Toxicokinetic
    modeling
    is the
    preferred
    approach
    for estimating
    dose
    metrics
    from
    exposure.
    Toxicokinetic
    models
    generally
    describe
    the
    relationship
    between
    exposure
    and
    measures
    of
    internal
    dose
    over
    time.
    More
    complex
    models
    can
    reflect
    sources
    of intrinsic
    variation, such
    as polymorphisms
    in metabolism
    and
    clearance
    rates.
    When
    a robust
    model
    is not
    available,
    or
    when
    the
    purpose
    of the
    assessment
    does
    not
    warrant
    developing
    a
    model,
    simpler
    approaches may
    be used.
    For
    chronic
    exposure
    studies,
    the
    cumulative
    exposure
    or
    dose
    administered
    often
    is
    expressed
    as
    an average
    over
    the duration
    of the
    study,
    as
    one consistent
    dose metric.
    This
    approach
    implies
    that
    a
    higher
    dose
    administered
    over
    a short
    duration
    is
    equivalent
    to
    a
    commensurately
    lower
    dose
    administered
    over
    a longer
    duration.
    Uncertainty
    usually
    increases
    as the
    duration
    becomes
    shorter
    relative
    to
    the
    averaging
    duration
    or
    the
    intennittent
    doses
    become
    more
    intense
    than
    the
    averaged
    dose.
    Moreover,
    doses
    during
    any
    specific
    susceptible
    or
    refractory
    period
    would
    not
    be
    equivalent
    to doses
    at
    other times.
    For these
    reasons,
    cumulative
    exposure
    or
    potential
    dose may
    be
    replaced
    by
    a more
    appropriate
    dose
    metric
    when
    indicated
    by
    the
    data.
    3-4

    For
    mode
    of
    action
    studies,
    the
    dose
    metric
    should
    be
    calculated
    over a
    duration
    that
    reflects
    the
    time to
    occurrence
    of the
    key
    precursor
    effects.
    Mode
    of
    action
    studies
    are
    often
    of
    limited
    duration,
    as
    the
    precursors
    can
    be
    observed
    after
    less-than-chronic
    exposures.
    When
    the
    experimental
    exposure
    regimen
    is specified
    on
    a weekly
    basis
    (for
    example,
    4
    hours
    a
    day,
    5 days
    a week),
    the
    daily
    exposure
    may
    be
    averaged
    over
    the week,
    where
    appropriate.
    Doses
    in studies
    at
    the cellular
    or
    molecular
    level
    can
    be difficult
    to relate
    to organ-
    or
    organism-level
    dose
    metrics.
    Toxicokinetic
    modeling
    can
    sometimes
    be
    used
    to
    relate
    doses
    at
    the
    cellular
    or molecular
    level
    to doses
    or
    exposures
    at
    higher
    levels
    of
    organization.
    3.1.2.
    Toxicokinetic
    Data
    and
    Modeling
    In the
    absence
    of
    chemical-specific
    data,
    physiologically
    based
    toxicokinetic
    modeling
    is
    potentially
    the most
    comprehensive
    way to
    account
    for
    biological
    processes
    that determine
    internal
    dose.
    Physiologically
    based
    models
    commonly
    describe
    blood
    flow
    between
    physiological
    compartments
    and
    simulate
    the
    relationship
    between
    applied
    dose
    and internal
    dose.
    Toxicokinetic models
    generally
    need
    data
    on
    absorption,
    distribution,
    metabolism,
    and
    elimination of the
    administered
    agent
    and
    its metabolites.
    Additionally,
    in
    the
    case
    of
    inhalation
    exposures,
    models
    can
    explicitly
    characterize
    the
    geometry
    of
    the
    respiratory
    tract and
    the
    airflow
    through
    it,
    as
    well
    as
    the
    interaction
    of
    this
    airflow
    with
    the
    entrained
    particles
    or
    fibers
    and gases
    (Kimbell
    et
    al., 2001;
    Subramaniam
    et
    al.,
    2003).
    Because
    of
    large
    interspecies
    differences
    in airway
    morphometry
    such
    models
    can
    be
    particularly useful
    in interspecies extrapolations.
    When
    employed,
    however,
    the
    potential
    for
    large
    inter-individual
    differences
    in
    airway
    morphometry,
    are
    considered
    to ensure
    that
    the
    models
    provide
    information
    representative
    of
    human
    populations.
    Toxicokinetic models
    can
    improve
    dose-response
    assessment
    by
    revealing
    and
    describing
    nonlinear relationships between
    applied
    and
    internal
    dose.
    Nonlinearity
    observed
    in a dose
    response
    curve
    often
    can
    be
    attributed
    to toxicokinetics
    (Hoel
    et al.,
    1983;
    Gaylor
    et
    aL, 1994),
    involving, for
    example,
    saturation
    or
    induction
    of
    enzymatic
    processes
    at high
    doses.
    In
    some
    cases,
    toxicokinetic processes
    tend
    to
    become
    linear
    at sufficiently
    low
    doses
    (Hattis,
    1990).
    3-5

    A
    discussion
    of
    confidence
    should
    accompany
    the
    presentation
    of
    model
    results
    and
    include
    consideration
    of model
    validation
    and sensitivity
    analysis,
    stressing
    the predictive
    performance
    of
    the model
    and
    whether
    the
    model
    is
    sufficient
    to support
    decision-making.
    Quantitative uncertainty
    analysis
    is important
    for
    evaluating
    the
    performance
    of
    a
    model,
    whether
    the
    model
    is
    based
    primarily
    on default
    assumptions
    or
    chemical-specific
    data.
    The
    uncertainty
    analysis
    covers
    questions
    of
    model
    uncertainty
    (e.g.,
    Is the
    model
    based
    on the
    appropriate
    biology
    and
    how
    does
    that
    affect
    estimates
    of dose
    metrics?)
    and
    parameter
    uncertainty
    (e.g., Do
    the
    data
    support
    unbiased and
    stable
    estimates
    of the
    model
    parameters?).
    When
    a
    delivered
    dose
    measure
    is
    used
    in animal-to-human
    extrapolation,
    the assessment
    discusses
    the
    confidence
    of
    the
    target
    tissue
    and
    its
    toxicodynamics
    being
    the
    same
    in
    both
    species
    (see
    Section
    3.6).
    Toxicokinetic
    modeling
    results
    may be
    presented
    alone
    as the
    preferred
    method
    of
    estimating
    human
    equivalent
    exposures
    or
    doses,
    or
    these
    results
    may
    be presented
    in
    parallel
    with
    default
    procedures
    (see
    Section
    3.1.3),
    depending on the
    confidence
    in
    the
    modeling.
    3.1.3.
    Cross-species
    Scaling
    Procedures
    Standard
    cross-species
    scaling
    procedures
    are
    available
    when
    the
    data
    are
    not
    sufficient
    to
    support
    a
    toxicokinetic model
    or
    when
    the
    purpose
    of
    the
    assessment
    does
    not
    warrant
    developing one.
    The
    aim
    is to define
    exposure
    levels
    for
    humans
    and animals
    that
    are
    expected
    to produce the same
    degree
    of
    effect
    (U.S.
    EPA,
    1992b),
    taking
    into
    account
    differences
    in
    scale
    between
    test
    animals
    and
    humans,
    such
    as
    size
    and
    lifespan.
    3.1.3.1.
    Oral
    Exposures
    For oral
    exposures,
    administered
    doses
    should
    be
    scaled
    from
    animals
    to humans
    on
    the
    basis
    of
    equivalence
    of
    mg/kg
    314
    -d
    (milligrams
    of the
    agent
    normalized
    by
    the
    3/4 power
    of
    body
    weight
    per
    day)
    (U.S.
    EPA,
    1 992b).
    The
    3/4
    power
    is consistent
    with current
    science,
    including
    empirical
    data
    that
    allow
    comparison
    of
    potencies
    in
    humans
    and
    animals,
    and
    it is also
    supported
    by
    analysis
    of
    the
    allometric
    variation
    of key
    physiological
    parameters
    across
    mammalian
    species.
    It is
    generally
    more
    appropriate
    at low
    doses,
    where
    sources
    of
    nonlinearity
    such
    as
    saturation
    of enzyme activity
    are
    less
    likely
    to occur.
    This scaling
    is
    intended
    as
    an
    3-6

    unbiased
    estimate
    rather
    than
    a conservative
    one.
    Equating
    exposure
    concentrations
    in
    food
    or
    water
    is an
    alternative
    version
    of
    the
    same
    approach,
    because
    daily
    intakes
    of
    food
    or
    water
    are
    approximately
    proportional
    to
    the 3/4
    power
    of body
    weight.
    The
    aim
    of these
    cross-species
    scaling
    procedures
    is
    to
    estimate
    administered
    doses
    in
    animals
    and
    humans
    that
    result
    in equal
    lifetime
    risks.
    It
    is useful
    to
    recognize
    two
    components
    of this
    equivalence:
    toxicokinetic
    equivalence,
    which
    determines
    administered
    doses
    in
    animals
    and
    humans
    that
    yield
    equal
    tissue
    doses,
    and
    toxicodynamic
    equivalence,
    which
    determines
    tissue
    doses
    in
    animals
    and
    humans
    that
    yield
    equal
    lifetime
    risks
    (U.S.
    EPA,
    1 992b).
    Toxicokinetic
    modeling
    (see Section
    3.1.2)
    addresses
    factors
    associated
    with
    toxicokinetic
    equivalence,
    and
    toxicodynamic
    modeling
    (see
    Section
    3.2.2)
    addresses
    factors
    associated
    with
    toxicodynamic
    equivalence.
    When
    toxicokinetic
    modeling
    is used
    without
    toxicodynamic
    modeling,
    the
    dose-response
    assessment
    develops
    and
    supports
    an
    approach
    for
    addressing
    toxicodynamic
    equivalence,
    perhaps
    by
    retaining
    some
    of the
    cross-species
    scaling
    factor
    (e.g.,
    using
    the
    square
    root of
    the
    cross-species
    scaling
    factor
    or
    using
    a factor
    of
    3 to
    cover
    toxicodynamic
    differences
    between
    animals
    and humans,
    as
    is
    currently
    done
    in
    deriving
    inhalation
    reference
    concentrations
    [U.S.
    EPA,
    1994]).
    When
    assessing
    risks
    from
    childhood
    exposure,
    the
    mg/kg
    3
    4
    -d
    scaling
    factor
    does
    not
    use
    the
    child
    T
    s
    body
    weight
    (U.S.
    EPA,
    1 992b).
    This
    reflects
    several
    uncertainties
    in extrapolating
    risks
    to
    children:
    The data
    supporting
    the
    mg/kg
    314
    -d
    scaling
    factor
    were
    derived
    for
    differences
    across
    species
    and
    may
    not apply
    as
    well
    to differently
    sized
    individuals
    of
    the same
    species
    or
    to
    different
    lifestages.
    In addition
    to
    metabolic
    differences,
    there
    are also
    important
    toxicodynamic
    differences; for
    example,
    children
    have
    faster
    rates
    of
    cell
    division
    than
    do
    adults,
    so
    scaling
    across
    different
    lifestages
    and
    species
    simultaneously
    may
    be
    particularly
    uncertain.
    3-7

    3.1.3.2.
    Inhalation
    Exposures
    For inhalation
    exposures
    experimental
    exposure
    concentrations
    are
    replaced
    with
    human
    equivalent
    concentrations
    calculated
    using
    EPA’s
    methods
    for
    deriving
    inhalation
    reference
    concentrations
    (U.S.
    EPA,
    1994),
    which
    give
    preference
    to
    the
    use
    of
    toxicokinetic
    modeling.
    When
    toxicokinetic
    models
    are unavailable,
    default
    dosimetry
    models
    are
    employed
    to
    extrapolate
    from
    experimental
    exposure
    concentrations
    to human
    equivalent
    concentrations.
    When
    toxicokinetic
    modeling
    or
    dosimetry
    modeling
    is used
    without
    toxicodynamic
    modeling,
    the dose-response
    assessment
    develops
    and supports
    an approach
    for
    addressing
    toxicodynamic
    equivalence.
    The
    default
    dosimetry
    models
    typically
    involve
    the use
    of species-specific
    physiologic
    and
    anatomic
    factors
    relevant
    to the
    form
    of the
    agent
    (e.g.,
    particle
    or
    gas)
    and
    categorized
    with
    regard
    to
    whether
    the response
    occurs
    either
    locally
    (i.e., within
    the
    respiratory
    tract)
    or
    remotely.
    For
    example,
    cunent
    default
    models
    (U.S.
    EPA,
    1994)
    use parameters
    such
    as:
    inhalation
    rate
    and
    surface
    area
    of the
    affected
    part
    of
    the respiratory
    tract
    for
    gases
    eliciting
    the
    response
    locally,
    blood:gas
    partition
    coefficients
    for remote
    acting
    gases,
    fractional deposition
    with
    inhalation
    rate
    and surface
    area
    of
    the
    affected
    part
    of
    the
    respiratory
    tract for
    particles
    eliciting
    the
    response
    locally,
    and
    fractional
    deposition
    with
    inhalation
    rate
    and
    body
    weight
    for particles
    eliciting
    the
    response
    remotely.
    The
    current
    default
    values
    for
    some
    parameters
    used
    in
    the default
    models
    (e.g.,
    breathing
    rate
    and
    respiratory
    tract
    surface
    area)
    are
    based
    on
    data
    from
    adults
    (U.S.
    EPA,
    1994).
    The
    human
    respiratory system
    passes
    through
    several
    distinct
    stages
    of
    maturation
    and growth
    during
    the first
    several
    years
    of life
    and
    into adolescence
    (Pinkerton
    and Joad,
    2000),
    during
    which
    3-8

    characteristics
    important
    to disposition
    of
    inhaled
    toxicants
    may
    vary.
    Children
    and
    adults
    breathing
    the
    same
    concentration
    of an
    agent
    may
    receive
    different
    doses
    to
    the body
    or
    lungs
    (U.S.
    EPA,
    2002b).
    Consequently,
    it may
    be appropriate
    to evaluate
    the default
    models
    by
    considering
    physiologic
    and
    anatomic
    factors
    representative
    of
    early
    lifestages,
    for
    example
    through
    the
    substitution
    of
    child-specific
    parameters
    (U.S.
    EPA,
    2002b).
    Such
    evaluation
    uses
    the
    default
    model
    and
    dosimetric
    adjustment
    in
    use
    at
    the
    time
    of the
    assessment
    coupled
    with
    the
    best
    understanding
    of child-specific
    parameters
    at that
    time
    (e.g.,
    drawn
    from the
    scientific
    literature).
    This
    analysis
    is
    undertaken
    with
    caution:
    (I)
    because
    of
    the
    correlations
    between
    activity
    level,
    breathing
    rate,
    respiratory tract
    dimensions,
    and
    body
    weight
    and
    (2) to
    avoid
    the
    possibility
    of
    mismatching
    the
    type
    of agent
    (gas
    or
    particle)
    and
    its
    site
    of
    response
    (within
    the
    respiratory
    tract
    or remote
    from
    the
    respiratory
    tract)
    with
    the relevant
    dosimetry
    factors
    in
    use
    at
    the time
    of
    the
    assessment.
    Analyses
    of
    children’s
    inhalation
    dosimetry
    are
    also considered
    when
    using
    model
    structures
    beyond
    the
    default
    models
    (e.g.,
    physiologically
    based
    toxicokinetic
    models).
    When
    using
    dosimetry
    modeling,
    the
    comparison
    of human-equivalent
    concentrations
    for
    different lifestages
    (e.g.,
    for
    an
    adult
    and
    a
    child)
    can
    indicate
    whether
    it is
    important
    to
    carry
    both
    concentrations
    forward
    in
    the
    dose-response
    assessment
    or
    whether
    a verbal
    characterization
    of
    any findings will
    suffice.
    3.1.4.
    Route
    Extrapolation
    In
    certain
    situations,
    an
    assessment
    based
    on
    studies
    of one
    exposure
    route
    may
    be
    applied
    to
    another
    exposure
    route.
    Route-to-route
    extrapolation
    has both
    qualitative
    and
    quantitative
    aspects.
    For
    the
    qualitative
    aspect,
    the
    assessor
    should
    weigh
    the degree
    to
    which
    positive
    results
    by one
    exposure
    route
    support
    a judgment
    that
    similar
    results
    would
    be
    expected
    by
    another
    route.
    In
    general,
    confidence
    in
    making
    such
    a judgment
    is strengthened
    when
    tumors
    are
    observed
    at a
    site
    distant
    from
    the
    portal
    of
    entry
    and
    when
    absorption
    is similar
    through
    both
    routes.
    In the
    absence
    of
    contrary
    data,
    a qualitative default
    option
    can
    be used:
    if
    the
    agent
    is
    absorbed
    through
    an exposure
    route
    to
    give
    an
    internal
    dose,
    it may
    be
    carcinogenic
    by
    that
    route.
    3-9

    When
    a qualitative
    extrapolation
    can
    be supported,
    quantitative
    extrapolation
    may
    still
    be
    problematic
    due
    to the
    absence
    of adequate
    data.
    The
    differences
    in
    biological
    processes
    among
    routes
    of
    exposure
    (oral,
    inhalation,
    dermal)
    can
    be
    great
    because
    of
    for example,
    first-pass
    effects
    and
    different
    results
    from
    different
    exposure
    patterns.
    There
    is
    no
    generally
    applicable
    method
    for
    accounting
    for
    these differences
    in uptake
    processes
    in
    a
    quantitative
    route-to-route
    extrapolation
    of dose-response
    data
    in the
    absence
    of
    good data
    on
    the
    agent
    of interest.
    Therefore,
    route-to-route
    extrapolation
    of dose
    data
    relies
    on
    a case-by-case
    analysis
    of
    available
    data.
    When
    good
    data
    on the
    agent itself
    are
    limited,
    an extrapolation
    analysis
    can
    be based
    on
    expectations
    from
    physical
    and
    chemical
    properties
    of the
    agent,
    properties
    and
    route-specific
    data
    on structurally
    analogous
    compounds,
    or in
    vitro
    or in
    vivo
    uptake
    data
    on
    the agent.
    Route-to-route
    uptake
    models
    may be
    applied
    if model
    parameters
    are
    suitable
    for the
    compound
    of
    interest.
    Such
    models
    are currently
    considered
    interim
    methods;
    further
    model
    development and validation
    is
    awaiting
    the
    development
    of more
    extensive
    data.
    For screening
    or hazard
    ranking,
    route-to-route
    extrapolation
    may
    be
    based
    on assumed
    quantitative
    comparability
    as a
    default,
    as long
    as it is
    reasonable
    to assume
    absorption
    by compared
    routes.
    When
    route-to-route
    extrapolation
    is used,
    the
    assessor’s
    degree
    of
    confidence
    in
    both
    the
    qualitative
    and
    quantitative
    extrapolation
    is
    discussed
    in
    the
    assessment
    and
    highlighted
    in
    the
    dose-response
    characterization.
    Toxicokinetic
    modeling
    can
    be used
    to
    compare
    results
    of
    studies
    by
    different
    exposure
    routes.
    Results
    can
    also
    be
    compared
    on
    the
    basis
    of internal
    dose
    for
    effects
    distant
    from
    the
    point
    of
    contact.
    Route
    extrapolation
    can
    be
    used
    to
    understand
    how
    internal
    dose
    and
    subsequent
    effects
    depend
    on
    exposure
    route.
    If
    testing
    by
    different
    exposure
    routes
    is
    available,
    the
    observation
    of
    similar
    or
    dissimilar
    internal
    doses
    can
    be
    important
    in
    determining
    whether
    and
    what
    conclusions
    can
    be made
    concerning
    the dose-response
    function(s)
    for
    different
    routes
    of
    exposure.
    3-10

    3.2.
    ANALYSIS
    IN
    THE RANGE
    OF OBSERVATION
    The
    principle
    underlying
    these
    cancer
    guidelines
    is
    to
    use
    approaches
    that
    include
    as
    much
    information
    as possible.
    Quantitative
    information
    about
    key precursor
    events
    can be
    used
    to
    develop
    a
    toxicodynamic
    model.
    Alternatively,
    such
    information
    can
    be fitted
    by empirical
    models
    to
    extend
    the
    dose-response
    analysis
    of
    tumor
    incidence
    to
    lower
    doses
    and
    response
    levels.
    The
    analysis
    in the
    range
    of observation
    is
    used
    to establish
    a
    POD near
    the
    lower
    end
    of
    the observed
    range
    (see
    Section
    3.3).
    3.2.1.
    Epidemiologic
    Studies
    Ideally,
    epidemiologic
    data
    would
    be
    used
    to select
    the
    dose-response
    function
    for
    human
    exposures.
    Because
    epidemiologic
    data
    are
    usually
    limited
    and
    many
    models
    may
    fit the
    data
    (Samet
    et al.,1998),
    other
    factors
    may
    influence
    model
    choice.
    For
    epidemiologic
    studies,
    including
    those
    with
    grouped
    data,
    analysis
    by
    linear
    models
    in
    the
    range
    of
    observation
    is
    generally
    appropriate
    unless
    the
    fit
    is poor.
    The
    relatively
    small
    exposure
    range
    observed
    in
    many
    epidemiologic
    studies,
    for example,
    makes
    it
    difficult
    to
    discern
    the
    shape
    of the
    exposure-
    or
    dose-response
    curve.
    Exposure
    misclassification
    and errors
    in exposure
    estimation
    also
    obscure
    the
    shape
    of the
    dose-response
    curve.
    ‘When
    these errors
    are
    unsystematic
    or random,
    the
    result is
    frequently
    to bias
    the
    risk
    estimates
    toward
    zero.
    When
    a linear
    model
    fits
    poorly,
    more
    flexible
    models
    that
    allow
    for
    low-dose
    linearity,
    for example,
    a
    linear-quadratic
    model
    or
    a
    Hill
    model
    (Murrell
    et
    al., 1998),
    are
    often
    considered
    next.
    Analysis
    of epidemiologic
    studies
    depends
    on
    the
    type
    of
    study and
    quality
    of
    the
    data,
    particularly
    the availability
    of
    quantitative
    measures
    of
    exposure.
    The
    objective
    is
    to develop
    a
    dose-response
    curve
    that estimates
    the incidence
    of
    cancer
    attributable
    to the
    dose
    (as estimated
    from
    the
    exposure)
    to
    the agent.
    In
    some
    cases,
    e.g.,
    tobacco
    smoke
    or
    occupational
    exposures,
    the
    data are
    in
    the range
    of the
    exposures
    of
    interest.
    In other
    cases,
    as
    with
    data
    from
    animal
    experiments,
    information
    from
    the observable
    range
    is
    extrapolated
    to
    exposures
    of interest.
    Analysis
    of effects
    raises
    additional
    issues:
    3-li

    Many
    studies
    collect
    information
    from
    death
    certificates,
    which
    leads
    to
    estimates
    of
    mortality
    rather
    than
    incidence.
    Because
    survival
    rates
    vary
    for
    different
    cancers,
    the
    analysis
    may
    be
    improved
    by
    adjusting
    mortality
    figures
    to reflect
    the relationship
    between
    incidence
    and mortality.
    Epidemiologic
    studies,
    by
    their
    nature,
    are
    limited
    in
    the
    extent
    to which
    they
    can
    control
    for effects
    due to
    exposures
    from other
    agents.
    In
    some
    cases,
    the
    agent
    can
    have
    discernible
    interactive
    effects
    with
    another
    agent,
    making
    it
    possible
    to
    estimate
    the
    contribution
    of
    each
    agent
    as
    a
    risk
    factor
    for
    the
    effects
    of
    the
    other.
    For example,
    competing
    risks
    in
    a study
    population
    can
    limit
    the
    observed
    occurrence
    of
    cancer,
    while
    additive
    effects
    may
    lead
    to an
    increase
    occurrence
    of
    cancer.
    In
    the
    case
    of rates
    not
    already
    so
    adjusted,
    the
    analysis
    can
    be
    improved
    by correcting
    for
    competing
    or
    additive
    risks
    that
    are
    not
    similar
    in
    exposed
    and
    comparison
    groups.
    Comparison groups
    that
    are
    not
    free from
    exposure
    to
    the
    agent
    can bias
    the
    risk
    estimates
    toward
    zero.
    The
    analysis
    can
    be
    improved
    by
    considering
    background
    exposures
    in the
    exposed
    and
    comparison
    groups.
    The
    latent
    period
    for most
    cancers
    implies
    that
    exposures
    immediately
    preceding
    the
    detection
    of a
    tumor
    would
    be less
    likely
    to
    have
    contributed
    to its
    development
    and,
    therefore,
    may
    count
    less
    in
    the
    analysis.
    Study
    subjects
    who
    were
    first exposed
    near
    the
    end
    of
    the
    study
    may
    not
    have
    had
    adequate
    time
    since
    exposure
    for
    cancer
    to
    develop;
    therefore, analysis
    of their
    data
    may
    be
    similar
    to
    analysis
    of
    data
    for
    those
    who were
    not
    exposed. However,
    for
    carcinogens
    that act
    on
    multiple
    stages
    of the
    carcinogenic
    process,
    especially
    the
    later
    stages,
    all periods
    of exposure.
    including
    recent
    exposures,
    may
    be important.
    Some
    study
    designs
    can
    yield
    only
    a
    partial
    characterization
    of the
    overall
    hazard
    and
    therefore
    risk
    as,
    for
    example,
    in
    studies
    that:
    (1)
    investigate
    only
    one
    effect
    (typical
    of many
    3-12

    case-control
    studies),
    (2)
    include
    only
    one
    population segment
    (e.g., male
    workers
    or
    workers
    of
    one socioeconomic
    class),
    or
    (3)
    include
    only
    one
    lifestage
    (e.g.,
    childhood
    leukemia
    following
    maternal
    exposure
    to
    contaminated
    drinking
    water).
    To obtain
    a
    more
    complete
    characterization
    that includes
    risks
    of other
    cancers,
    estimates
    from these
    studies
    can
    be
    supplemented
    with
    estimates
    from
    other
    studies
    that
    investigated
    other
    cancers,
    population
    segments,
    or
    lifestages
    (see
    Section
    3.5).
    When
    several
    studies
    are available
    for
    dose-response
    analysis,
    ineta-analysis
    can
    provide
    a systematic
    approach
    to weighing
    positive
    studies
    and those
    studies
    that
    do not
    show
    positive
    results,
    and
    calculating
    an
    overall
    risk
    estimate
    with
    greater
    precision.
    Issues
    considered
    include
    the
    comparability
    of
    studies,
    heterogeneity
    across
    studies,
    and the
    potential
    for a
    single
    large
    study
    to
    dominate
    the analysis.
    Confidence
    in a
    meta-analysis
    is
    increased
    when
    it
    considers
    study
    quality,
    including
    definition
    of the
    study
    population
    and comparison
    group,
    measurement
    of
    exposure,
    potential
    for exposure
    misclassification,
    adequacy
    of
    follow-up
    period,
    and
    analysis
    of
    confounders
    (see
    Section
    2.2.1.3).
    3.2.2.
    Toxicodynamic
    (“Biologically
    Based”)
    Modeling
    Toxicodynamic modeling
    can be
    used
    when
    there
    are sufficient
    data
    to ascertain
    the
    mode
    of
    action
    (see
    Section
    2.4)
    and quantitatively
    support
    model
    parameters
    that
    represent
    rates
    and
    other
    quantities
    associated with
    the
    key
    precursor
    events
    of
    the
    mode
    of action.
    Toxicodynamic
    modeling
    is
    potentially
    the
    most
    comprehensive
    way
    to account
    for
    the
    biological
    processes
    involved
    in a
    response.
    Such
    models
    seek
    to
    reflect
    the
    sequence
    of
    key precursor
    events
    that
    lead
    to
    cancer.
    Toxicodynamic
    models
    can
    contribute
    to dose-response
    assessment
    by
    revealing
    and describing nonlinear
    relationships
    between
    internal
    dose
    and
    cancer
    response.
    Such
    models
    may
    provide
    a useful
    approach
    for
    analysis
    in
    the
    range
    of
    observation,
    provided
    the
    purpose
    of
    the
    assessment
    justifies
    the
    effort
    involved.
    If
    a
    new
    model
    is
    developed
    for
    a
    specific
    agent,
    extensive
    data
    on
    the
    agent
    are
    important
    for
    identifying
    the
    form
    of the
    model,
    estimating
    its
    parameters,
    and
    building
    confidence
    in its
    results.
    Conformance to
    the
    observed
    tumor
    incidence
    data alone
    does
    not
    establish
    a
    model’s
    validity,
    as a
    model
    can
    be
    designed
    with
    a sufficiently
    large
    number
    of parameters
    so as to
    fit
    3-13

    any given
    dataset.
    Peer
    review,
    including
    both
    an
    examination
    of
    the
    scientific
    basis
    supporting
    the
    model
    and
    an
    independent
    evaluation
    of
    the
    model’s
    performance,
    is
    an
    essential
    part
    of
    evaluating
    the
    new
    model.
    If
    a
    standard
    model
    already
    exists
    for
    the
    agent’c
    mode
    of
    action,
    the
    model
    can
    be
    adapted
    for
    the agent
    by
    using
    agent-specific
    data
    to
    estimate
    the
    model’s
    parameters.
    An
    example
    is
    the two-stage
    clonal
    expansion
    model
    developed
    by
    Moolgavkar
    and
    Knudson
    (1981)
    and
    Chen
    and
    Farland
    (1991).
    These
    models
    continue
    to be
    improved
    as
    more
    information
    becomes available.
    It
    is
    possible
    for
    different
    models
    to provide
    equivalent
    fits
    to
    the
    observed
    data
    but to
    diverge
    substantially
    in their
    projections
    at lower
    doses.
    When
    model
    parameters
    are
    estimated
    from
    tumor
    incidence
    data,
    it
    is
    often
    the case
    that
    different
    combinations
    of
    parameter
    estimates
    can yield
    similar
    results
    in the
    observed
    range.
    For this
    reason,
    critical
    parameters
    (e.g.,
    mutation
    rates
    and
    cell
    birth
    and
    death
    rates)
    are estimated
    from
    laboratory
    studies
    and
    not
    by
    curve-fitting
    to
    tumor
    incidence
    data
    (Portier,
    1987).
    This
    approach
    reduces
    model
    uncertainty
    (see
    Section
    3.6)
    and
    ensures
    that the
    model
    does
    not
    give
    answers
    that
    are
    biologically
    unrealistic.
    This
    approach
    also
    provides
    a
    robustness
    of
    results,
    where
    the
    results
    are
    not
    likely
    to
    change
    substantially if fitted
    to
    slightly
    different
    data.
    Toxicodynamic
    modeling
    can
    provide
    insight
    into
    the
    relationship
    between
    tumors
    and
    key precursor events.
    For
    example,
    a
    model
    that
    includes
    cell
    proliferation
    can
    be
    used
    to
    explore
    the
    extent
    to which
    small
    increases
    in
    the
    cell proliferation
    rate can
    lead
    to
    large
    lifetime
    tumor
    incidences
    (Gaylor
    and
    Zheng,
    1996).
    In this
    way,
    toxicodynamic
    modeling
    can
    be
    used
    to
    select
    and
    characterize
    an
    appropriate
    precursor
    response
    level
    (see Section
    3.2.2,
    3.2.5).
    3.2.3.
    Empirical
    Modeling
    (“Curve Fitting”)
    When
    a toxicodynamic
    model
    is not
    available
    or when
    the
    purpose
    of the
    assessment
    does
    not
    warrant
    developing such
    a
    model,
    empirical
    modeling
    (sometimes called
    “curve
    fitting”)
    should
    be
    used
    in
    the
    range
    of observation.
    A
    model
    can be
    fitted
    to
    data
    on either
    tumor
    incidence
    or a
    key
    precursor
    event.
    Goodness-of-fit
    to
    the
    experimental
    observations
    is
    not
    by
    itself
    an
    effective
    means
    of discriminating
    among
    models
    that adequately
    fit
    the
    data
    (OSTP,
    3-14

    1985).
    Many
    different
    curve-fitting
    models
    have
    been
    developed,
    and those
    that
    fit
    the
    observed
    data
    reasonably
    well
    may lead
    to
    several-fold
    differences
    in estimated
    risk
    at the lower
    end of
    the
    observed
    range.
    Another
    problem
    occurs
    when
    a multitude
    of
    alternatives
    are
    presented
    without
    sufficient
    context
    to
    make
    a
    reasoned
    judgment
    about
    the
    alternatives.
    This
    form
    of model
    uncertainty
    reflects
    primarily
    the
    availability
    of
    different
    computer
    models
    and
    not biological
    information
    about
    the
    agent being
    assessed
    or
    about
    carcinogenesis
    in general.
    In cases
    where
    curve-fitting
    models
    are used
    because
    the data
    are
    not adequate
    to
    support
    a
    toxicodynamic
    model,
    there
    generally
    would
    be
    no
    biological
    basis
    to
    choose
    among
    alternative
    curve-fitting
    models.
    However,
    in situations
    where
    there
    are
    alternative
    models
    with
    significant
    biological
    support,
    the
    decisionmaker
    can
    be informed
    by the presentation
    of
    these
    alternatives
    along with
    their strengths
    and uncertainties.
    Quantitative
    data
    on
    precursors
    can
    be used
    in
    conjunction
    with,
    or
    in
    lieu
    of,
    data
    on
    tumor
    incidence
    to
    extend
    the
    dose-response
    curve
    to lower
    doses.
    Caution
    is used
    with
    rates
    of
    molecular
    events
    such
    as mutation
    or
    cell proliferation
    or
    signal
    transduction.
    Such rates
    can
    be
    difficult
    to
    relate to
    cell or
    tissue
    changes
    overall.
    The timing
    of
    observations
    of these
    phenomena,
    as
    well
    as the
    cell
    type
    involved,
    is
    linked
    to
    other
    precursor
    events
    to ensure
    that
    the
    measurement
    is truly
    a key
    event (Section
    2.4).
    For
    incidence
    data
    on either
    tumors
    or
    a
    precursor,
    an
    established
    empirical
    procedure
    is
    used to
    provide
    objectivity
    and
    consistency
    among assessments.
    The
    procedure
    models
    incidence,
    corrected
    for
    background,
    as
    an
    increasing
    function
    of dose.
    The
    models
    are
    sufficiently
    flexible
    in the
    observed
    range
    to
    fit
    linear
    and
    nonlinear
    datasets.
    Additional
    judgments
    and
    perhaps
    alternative
    analyses
    are
    used
    when
    the
    procedure
    fails
    to
    yield reliable
    results.
    For
    example,
    when
    a model’s
    fit is
    poor, the
    highest
    dose
    is often
    omitted
    in cases
    where
    it is
    judged
    that
    the highest
    dose
    reflects
    competing
    toxicity
    that
    is more
    relevant
    at high
    doses
    than at
    lower
    doses.
    Another
    example
    is
    when
    there are
    large differences
    in
    survival
    across
    dose
    groups;
    here,
    models
    that
    includes
    time-to-tumor
    or
    time-to-event
    information
    may
    be
    useful.
    For
    continuous
    data
    on key
    precursor
    effects,
    empirical
    models
    can
    be
    chosen
    on
    the
    basis of
    the
    structure
    of the
    data.
    The rationale
    for the
    choice
    of model,
    the
    alternatives
    3-15

    considered
    and
    rejected,
    and a
    discussion
    of model
    uncertainty
    are
    included
    in
    the
    dose-response
    characterization.
    3.2.4.
    Point
    of
    Departure
    (POD)
    For
    each
    tumor
    response,
    a
    POD
    from the
    observed
    data
    should
    be
    estimated
    to
    mark
    the
    beginning
    of
    extrapolation
    to
    lower
    doses.
    The
    POD
    is
    an
    estimated
    dose
    (expressed
    in
    human-
    equivalent
    tenns)
    near
    the lower
    end
    of
    the
    observed
    range
    without
    significant
    extrapolation
    to
    lower
    doses.
    The POD
    is used as
    the starting
    point
    for subsequent
    extrapolations
    and
    analyses.
    For
    linear
    extrapolation,
    the
    POD is
    used to
    calculate
    a
    slopefactor
    (see Section
    3.3.3),
    and for
    nonlinear
    extrapolation
    the
    POD
    is used
    in
    the calculation
    of a
    reference
    dose
    or reference
    concentration
    (see
    Section
    3.3.4).
    In a risk
    characterization,
    the
    POD
    is part
    of the
    determination
    of
    a margin
    of
    exposure
    (see Section
    5.4).
    With
    appropriate
    adjustments,
    it can
    also
    be used
    as
    the basis
    for
    hazard
    rankings
    that compare
    different
    agents
    or
    health effects.
    The
    lowest
    POD is
    used that
    is adequately
    supported
    by the
    data.
    If the POD
    is above
    some
    data points,
    it can
    fail to
    reflect
    the shape
    of
    the dose-response
    curve
    at
    the lowest
    doses
    and
    can introduce
    bias into
    subsequent
    extrapolations
    (see Figure
    3-1).
    On the
    other hand,
    if
    the
    POD
    is far
    below
    all observed
    data points,
    it
    can introduce
    model
    uncertainty
    and
    parameter
    uncertainty
    (see Section
    3.6)
    that
    increase
    with
    the
    distance
    between
    the
    data
    and
    the
    POD.
    Use
    of a POD
    at the
    lowest
    level
    supported
    by
    the
    data
    seeks
    to
    balance
    these
    considerations.
    It
    uses
    information
    from
    the
    model(s)
    a
    small
    distance
    below
    the
    observed
    range
    rather
    than
    discarding
    this
    information
    and using
    extrapolation
    procedures
    in a
    range
    where
    the model(s)
    can provide
    some
    useful
    information.
    Statistical
    tests
    involving
    the
    ratio
    of
    the
    central
    estimate
    and
    its
    lower
    bound
    (i.e.,
    ED/LED)
    can
    be
    useful
    for
    evaluating
    how
    well
    the data
    support
    a model’s
    estimates
    at
    a
    particular
    response
    level.
    (Note
    that
    the ability
    to model
    at a
    particular
    response
    level is
    not the
    same
    as
    the study’s
    ability
    to
    identify
    an increase
    at that response
    level
    as
    statistically
    significant.)
    The POD
    for
    extrapolating
    the
    relationship
    to
    environmental
    exposure
    levels
    of interest,
    when the
    latter
    are
    outside
    the range
    of observed
    data, is
    generally
    the
    lower
    95%
    confidence
    3-16

    limit
    on the
    lowest
    dose level
    that
    can be
    supported
    for
    modeling
    by the
    data.
    SAB (1997)
    suggested
    that,
    “it
    may
    be
    appropriate
    to emphasize
    lower
    statistical
    bounds
    in screening
    analyses
    and
    in
    activities
    designed
    to
    develop
    an appropriate
    human
    exposure
    value,
    since
    such
    activities
    require
    accounting
    for various
    types
    of
    uncertainties
    and
    a
    lower
    bound
    on
    the
    central
    estimate
    is
    a scientifically-based
    approach
    accounting
    for the
    uncertainty
    in
    the
    true
    value
    of the
    ED
    10
    [or
    central
    estimate].”
    However,
    the
    consensus
    of the
    SAB
    (1997)
    was
    that,
    “both
    point
    estimates
    and
    statistical
    bounds
    can
    be
    useful
    in different
    circumstances,
    and
    recommended
    that the
    Agency
    routinely
    calculate
    and
    present
    the point
    estimate
    of
    the
    ED
    10
    [or central
    estimate]
    and
    the corresponding
    upper
    and
    lower
    95%
    statistical
    bounds.”
    For
    example,
    it
    may
    be appropriate
    to emphasize
    the central
    estimate
    in
    activities
    that
    involve
    fonnal
    uncertainty
    analysis
    that are
    required
    by
    0MB
    Circular
    A-4
    (0MB,
    2003)
    as
    well as
    ranking
    agents
    as to their
    carcinogenic
    hazard.
    Thus,
    risk
    assessors
    should
    calculate,
    to
    the extent
    practicable,
    and
    present
    the central
    estimate
    and
    the
    corresponding
    upper
    and lower
    statistical
    bounds
    (such
    as
    confidence
    limits)
    to
    inform
    decisionmakers.
    When
    tumor
    data
    are
    used,
    a POD
    is obtained
    from
    the
    modeled
    tumor
    incidences.
    Conventional
    cancer
    bioassays,
    with approximately
    50 animals
    per
    group,
    generally
    can
    support
    modeling
    down to
    an increased
    incidence
    of 1—10%;
    epidemiologic
    studies,
    with larger
    sample
    sizes,
    below 1%.
    Various
    models
    commonly
    used
    for
    carcinogens
    yield similar
    estimates
    of the
    POD
    at
    response
    levels
    as low
    as
    1%
    (Krewski
    and
    Van
    Ryzin,
    1981;
    Gaylor
    et al., 1994).
    Consequently,
    response
    levels
    at
    or
    below
    10%
    can
    often
    be
    used as
    the POD.
    As
    a
    modeling
    convention,
    the
    lower
    bound
    on
    the
    doses
    associated
    with standard
    response
    levels
    of 1,
    5,
    and
    10%
    can
    be
    analyzed,
    presented,
    and
    considered.
    For
    making
    comparisons
    at
    doses within
    the
    observed
    range,
    the
    ED
    10
    and
    LED
    10
    are
    also
    reported
    and
    can
    be used,
    with
    appropriate
    adjustments,
    in
    hazard
    rankings
    that compare
    different
    agents
    or health
    effects
    (U.S.
    EPA,
    2002c).
    A
    no-observed-adverse-effect
    level (NOAEL)
    generally
    is
    not used
    for assessing
    the
    potential
    for
    carcinogenic
    response
    when
    one or
    more
    models
    can be
    fitted to
    the data.
    When
    good quality
    precursor
    data
    are
    available
    and
    are
    clearly
    tied
    to the
    mode
    of
    action
    of
    the
    compound
    ofinterest,
    models
    that include
    both
    tumors
    and
    their precursors
    may
    be
    advantageous
    for
    deriving
    a POD.
    Such
    models
    can provide
    insight
    into quantitative
    3-17

    relationships
    between
    tumors
    and
    precursors
    (see
    Section
    3.2.2),
    possibly
    suggesting
    the
    precursor
    response
    level
    that
    is
    associated
    with
    a
    particular
    tumor
    response
    level.
    The
    goal
    is
    to
    use
    precursor
    data
    to
    extend
    the
    observed
    range
    below
    what
    can
    be
    observed
    in
    tumor
    studies.
    EPA
    is
    continuing
    to
    examine
    this
    issue
    and
    anticipates
    that
    findings
    and
    conclusions
    may
    result
    in
    supplemental
    guidance
    to
    these
    cancer
    guidelines.
    If
    the
    precursor
    data
    are
    drawn
    from
    small
    samples
    or
    if
    the
    quantitative
    relationship
    between
    tumors
    and
    precursors
    is
    not
    well
    defined,
    then
    the
    tumor
    data
    will
    provide
    a
    more
    reliable
    POD.
    Precursor
    effects
    may
    or
    may
    not
    be
    biologically
    adverse
    in
    themselves;
    the
    intent
    is
    to
    consider
    not
    only
    tumors
    but
    also
    damage
    that
    can
    lead
    to
    subsequent
    tumor
    development
    by
    the
    agent.
    Analysis
    of
    continuous
    data
    may
    differ
    from
    discrete
    data;
    Murrell
    et
    al.
    (1998)
    discuss
    alternative
    approaches
    to
    deriving
    a
    POD
    from
    continuous
    data.
    3.2.5.
    Characterizing
    the
    POD:
    The
    POD
    Narrative
    As
    a
    single-point
    summary
    of
    a
    single
    dose-response
    curve,
    the
    POD
    alone
    does
    not
    convey
    all
    the
    critical
    information
    present
    in
    the
    data
    from
    which
    it
    is
    derived.
    To
    convey
    a
    measure
    of
    uncertainty,
    the
    POD
    should
    be
    presented
    as
    a
    central
    estimate
    with
    upper
    and
    lower
    bounds.
    A
    POD
    narrative
    summarizes
    other
    important
    features
    of
    the
    database
    and
    the
    POD
    that
    are
    important
    to
    account
    for
    in
    low-dose
    extrapolations
    or
    other
    analyses.
    (a)
    Nature
    of
    the
    response.
    Is
    the
    POD
    based
    on
    tumors
    or
    a
    precursor?
    If
    on
    tumors,
    does
    the
    POD
    measure
    incidence
    or
    mortality?
    Is
    it
    a
    lifetime
    measure
    or
    was
    the
    study
    terminated
    early?
    The
    relationships
    between
    precursors
    and
    tumors,
    incidence
    and
    mortality,
    and
    lifetime
    and
    early-termination
    results
    vary
    from
    case
    to
    case.
    Modeling
    can
    provide
    quantitative
    insight
    into
    these
    relationships,
    for
    example,
    linking
    a
    change
    in
    a
    precursor
    response
    to
    a
    tumor
    incidence
    (see
    Section
    3.2.2).
    This
    can
    aid
    in
    evaluating
    the
    significance
    of
    the
    response
    at
    the
    POD
    and
    adjusting
    different
    PODs
    to
    make
    them
    comparable.
    (b)
    Level
    of
    the
    response.
    What
    level
    of
    response
    is
    associated
    with
    the
    POD,
    for
    example,
    1%
    cancer
    risk,
    10%
    cancer
    risk,
    or
    10%
    change
    in
    a
    precursor
    measure?
    3-18

    (c) Nature
    of
    the
    study
    population.
    Is
    the
    POD
    based
    on
    humans
    or animals?
    How
    large
    is the
    effective
    sample
    size?
    Is the
    study
    group representative
    of
    the
    general
    population,
    of
    healthy
    adult
    workers,
    or
    of a susceptible
    group?
    Are
    both
    sexes
    represented?
    Did
    exposure
    occur
    during
    a
    susceptible
    lifestage?
    (d)
    Slope
    ofthe
    dose-response
    curve
    at the
    POD.
    How
    does
    response
    change
    as
    dose
    is
    reduced
    below
    the POD?
    A
    steep
    slope indicates
    that risk
    decreases
    rapidly
    as
    dose decreases.
    On the
    other
    hand,
    a
    steep
    slope
    also
    indicates
    that
    errors
    in an exposure
    assessment
    can
    lead
    to
    large
    errors
    in
    estimating
    risk.
    Both
    aspects
    of
    the slope
    are important.
    The slope
    also
    indicates
    whether
    dose-response
    curves
    for different
    effects
    are
    likely
    to
    cross
    below the
    POD.
    For
    example,
    in the
    ED
    01
    study
    where
    2-acetylaminofluorene
    caused
    bladder
    carcinomas
    and
    liver
    carcinomas
    in
    mice
    (Littlefield
    et
    al.,
    1980),
    the dose-response
    curves
    for
    these
    tumors
    cross
    between
    10%
    and
    1% response
    (see
    Figure
    3-2).
    This crossing,
    which
    can
    be inferred
    from
    the
    slopes
    of the
    curves
    at a
    10% response,
    shows
    how
    considering
    the
    slope can
    lead
    to better
    inferences
    about
    the
    predominant
    effects
    expected
    at lower
    doses.
    Mode
    of action
    data
    can
    also
    be useful;
    quantitative
    information
    about
    key precursor
    events
    can be
    used to
    describe
    how
    risk
    decreases
    as
    dose
    decreases
    below
    the
    POD.
    (e)
    Relationship
    ofthe
    POD with
    other
    cancers.
    How
    does
    the
    POD
    for
    this cancer
    relate
    to PODs
    for other
    cancers
    observed
    in
    the
    database?
    For example,
    a
    POD
    based
    on male
    workers
    would
    not reflect
    the
    implications
    of
    mammary
    tumors
    in female
    rats
    or mice.
    (1)
    Extent
    ofthe
    overall
    cancer
    database.
    Have
    potential
    cancer
    responses
    been
    adequately
    studied
    (e.g.,
    were
    all
    tissues
    examined),
    or is the
    database
    limited
    to particular
    effects,
    population
    segments,
    or life
    stages?
    Do the
    mode
    of
    action
    data
    suggest
    a potential
    for
    cancers
    not
    observed
    in the
    database
    (e.g.,
    disruption
    of
    particular
    endocrine
    pathways
    leading
    to
    related
    cancers)?
    3-19

    3.2.6.
    Relative
    Potency
    Factors
    Relative
    potency
    factors
    (of
    which
    toxicity
    equivalence
    factors
    are
    a special
    case)
    can
    be
    used
    for
    a well-defined
    class
    of
    agents
    that
    operate
    through
    a common
    mode
    of
    action
    for
    the
    same
    toxic
    endpoint.
    A
    complete
    dose-response
    assessment
    is
    conducted
    for
    one well-studied
    member
    of the
    class
    that
    serves
    as
    the
    index
    chemical
    for
    the
    class.
    The
    other
    members
    of
    the
    class are
    tied
    to the
    index
    chemical
    by
    relative
    potency
    factors
    that
    are
    based
    on
    characteristics
    such
    as
    relative
    toxicological
    outcomes,
    relative
    metabolic
    rates,
    relative
    absorption
    rates,
    quantitative
    SARs,
    or
    receptor
    binding
    characteristics
    (U.S.
    EPA,
    2000c).
    Examples
    of
    this
    approach
    are
    the
    toxicity
    equivalence
    factors
    for
    dioxin-like
    compounds
    and
    the
    relative
    potency
    factors
    for
    some
    carcinogenic
    polycyclic
    aromatic
    hydrocarbons.
    Whenever
    practicable,
    toxicity
    equivalence
    factors
    should
    be
    validated
    and
    accompanied
    by quantitative
    uncertainty
    analysis.
    3.3.
    EXTRAPOLATION
    TO
    LOWER DOSES
    The
    purpose
    of
    low-dose
    extrapolation
    is
    to
    provide
    as
    much
    information
    as
    possible
    about
    risk in
    the
    range
    of
    doses
    below
    the observed
    data.
    The
    most
    versatile
    forms
    of
    low-dose
    extrapolation
    are
    dose-response
    models
    that
    characterize
    risk
    as
    a probability
    over
    a
    range
    of
    environmental
    exposure
    levels.
    These
    risk
    probabilities
    allow
    estimates
    of the
    risk
    reduction
    under
    different
    decision
    options
    and
    estimates
    of the
    risk
    remaining
    after
    an
    action
    is
    taken
    and
    provide
    the
    risk
    information
    needed
    for
    benefit-cost
    analyses
    of different
    decision
    options.
    When
    a dose-response
    model
    is not
    developed
    for
    lower
    doses,
    another
    form
    of
    low-dose
    extrapolation is a
    safety
    assessment
    that
    characterizes
    the
    safety
    of
    one
    lower
    dose,
    with
    no
    explicit
    characterization
    of
    risks
    above
    or
    below
    that
    dose.
    Although
    this
    type
    of
    extrapolation
    may be
    adequate
    for
    evaluation
    of some
    decision
    options,
    it
    may
    not be
    adequate
    for
    other
    purposes
    (e.g.,
    benefit-cost
    analyses)
    that
    require
    a quantitative
    characterization
    of risks
    across
    a
    range
    of
    doses.
    At
    this
    time,
    safety
    assessment
    is the
    default
    approach
    for
    tumors
    that
    arise
    through
    a
    nonlinear
    mode
    of action;
    however,
    EPA
    continues
    to explore
    methods
    for
    quantifying
    dose-response
    relationships
    over
    a range
    of environmental
    exposure
    levels
    for
    tumors
    that
    arise
    through
    a
    nonlinear
    mode
    of action
    (U.S.
    EPA,
    2002c).
    EPA
    program
    offices
    that
    need
    this
    more
    3-20

    explicit
    dose-response
    information
    may
    develop
    and
    apply
    methods
    that
    are
    informed
    by the
    methods
    described
    in
    these
    cancer
    guidelines.
    3.3.1.
    Choosing
    an
    Extrapolation
    Approach
    The
    approach
    for
    extrapolation
    below
    the
    observed
    data
    considers
    the
    understanding
    of
    the
    agent’s
    mode
    of
    action
    at
    each
    tumor
    site
    (see
    Section
    2.4).
    Mode
    of
    action
    information
    can
    suggest
    the
    likely
    shape
    of
    the
    dose-response
    curve
    at
    lower
    doses.
    The
    extent
    of
    inter-individual
    variation
    is
    also
    considered,
    with
    greater
    variation
    spreading
    the
    response
    over
    a
    wider
    range
    of
    doses.
    Linear
    extrapolation
    should
    be
    used
    when
    there
    are
    MOA
    data
    to indicate
    that the
    dose-
    response
    curve
    is expected
    to
    have
    a linear
    component
    below
    the POD.
    Agents
    that
    are
    generally
    considered
    to
    be linear
    in
    this
    region
    include:
    agents
    that
    are
    DNA-reactive
    and
    have
    direct
    mutagenic
    activity,
    or
    agents
    for
    which
    human
    exposures
    or
    body
    burdens
    are
    high
    and near
    doses
    associated
    with
    key
    precursor
    events
    in the
    carcinogenic
    process,
    so
    that
    background exposures
    to this
    and
    other
    agents
    operating
    through
    a
    common
    mode
    of
    action
    are in
    the increasing,
    approximately
    linear,
    portion
    of
    the
    dose-response
    curve.
    When
    the
    weight
    of
    evidence
    evaluation
    of
    all
    available
    data
    are insufficient
    to
    establish
    the
    mode
    of
    action
    for
    a
    tumor
    site
    and when
    scientifically
    plausible
    based
    on
    the
    available
    data,
    linear
    extrapolation
    is used
    as a
    default
    approach,
    because
    linear
    extrapolation
    generally
    is
    considered
    to
    be a
    health-protective
    approach.
    Nonlinear
    approaches
    generally
    should
    not
    be
    used
    in
    cases
    where
    the mode
    of
    action
    has not
    been
    ascertained.
    Where
    alternative
    approaches
    with
    significant
    biological support
    are
    available
    for
    the
    same
    tumor
    response
    and
    no
    scientific
    consensus favors
    a single
    approach,
    an
    assessment
    may
    present
    results
    based
    on more
    than
    one
    approach.
    3-21

    A
    nonlinear
    approach
    should
    be selected
    when
    there
    are
    sufficient
    data
    to
    ascertain
    the
    mode
    of
    action
    and
    conclude
    that it
    is not
    linear
    at low
    doses
    j
    the
    agent
    does
    not
    demonstrate
    mutagenic
    or
    other
    activity
    consistent
    with
    linearity
    at low
    doses.
    Special
    attention
    is
    important
    when
    the
    data
    support
    a
    nonlinear
    mode
    of
    action
    but
    there
    is
    also a
    suggestion
    of
    mutagenicity.
    Depending
    on the
    strength
    of the
    suggestion
    of mutagenicity,
    the
    assessment
    may
    justify
    a
    conclusion
    that
    mutagenicity
    is
    not operative
    at
    low doses
    and
    focus
    on a
    nonlinear
    approach,
    or
    alternatively,
    the
    assessment
    may
    use
    both
    linear
    and
    nonlinear
    approaches.
    Both
    linear
    and
    nonlinear
    approaches
    may
    be
    used
    when
    there
    are
    multiple
    modes
    of
    action.
    If
    there
    are
    multiple
    tumor
    sites,
    one
    with
    a linear
    and
    another
    with
    a
    nonlinear
    mode
    of
    action,
    then
    the
    corresponding
    approach
    is
    used
    at each
    site.
    If
    there
    are
    multiple modes
    of action
    at a
    single
    tumor
    site, one
    linear
    and
    another
    nonlinear,
    then
    both
    approaches
    are
    used
    to
    decouple
    and
    consider
    the
    respective
    contributions
    of
    each
    mode
    of
    action
    in
    different
    dose
    ranges.
    For example,
    an
    agent
    can
    act
    predominantly
    through
    cytotoxicity
    at
    high
    doses
    and
    through
    mutagenicity
    at
    lower
    doses
    where
    cytotoxicity
    does
    not
    occur.
    Modeling
    to
    a low
    response level
    can be
    useful
    for
    estimating
    the response
    at doses
    where
    the
    high-dose
    mode
    of
    action
    would
    be
    less
    important.
    3.3.2.
    Extrapolation
    Using
    a Toxicodynamic
    Model
    The
    preferred
    approach
    is
    to develop
    a
    toxicodynamic
    model
    of
    the agent’s
    mode
    of
    action
    and
    use
    that
    model
    for
    extrapolation
    to
    lower
    doses
    (see
    Section
    3.2.2).
    The
    extent
    of
    extrapolation is governed
    by
    an analysis
    of
    model
    uncertainty,
    where
    alternative
    models
    that
    fit
    similarly
    in
    the
    observed
    range
    can
    diverge
    below
    that
    range
    (see
    Section
    3.6).
    Substantial
    divergence
    is
    likely
    when
    model
    parameters
    are estimated
    from
    tumor
    incidence
    data,
    so that
    different
    combinations
    of
    parameter
    estimates
    yield
    similar
    fits
    in the
    observed
    range
    but
    have
    different
    implications
    at
    lower
    doses.
    An
    analysis
    of
    model
    uncertainty
    can be
    used
    to
    determine
    the range
    where
    extrapolation
    using
    the
    toxicodynamic
    model
    is
    supported
    and where
    further
    extrapolation would
    be
    based
    on
    either
    a
    linear
    or
    a nonlinear
    default,
    as
    appropriate
    (see
    Sections
    3.3.3,
    3.3.4).
    3-22

    3.3.3.
    Extrapolation
    Using
    a Low-dose,
    Linear
    Model
    Linear
    extrapolation
    should
    be
    used
    in two
    distinct
    circumstances:
    (1)
    when
    there
    are
    data
    to indicate
    that
    the
    dose-response
    curve
    has
    a linear
    component
    below
    the POD,
    or
    (2)
    as a
    default
    for
    a
    tumor
    site
    where
    the
    mode
    of action
    is
    not established
    (see
    Section
    3.3.1).
    For
    linear
    extrapolation,
    a line
    should
    be
    drawn
    from
    the
    POD
    to the
    origin,
    corrected
    for
    background.
    This
    implies
    a proportional
    (linear)
    relationship
    between
    risk
    and dose
    at
    low
    doses.
    (Note
    that
    the
    dose-response
    curve
    generally
    is not
    linear
    at
    higher
    doses.)
    The slope
    of
    this
    line,
    known
    as
    the slope
    factor,
    is an
    upper-bound
    estimate
    of risk
    per
    increment
    of
    dose
    that can
    be used
    to
    estimate
    risk
    probabilities
    for
    different
    exposure
    levels.
    The slope
    factor
    is equal
    to
    0.0
    1/LED
    01
    if
    the
    LED
    01
    is
    used
    as
    the
    POD.
    Unit
    risk estimates
    express
    the slope
    in
    terms
    of
    g/L
    drinking
    water
    or
    g/m
    3
    or
    ppm
    air.
    In
    general,
    the
    drinking
    water
    unit
    risk is
    derived
    by
    converting
    a
    slope
    factor
    from
    units
    of
    mg/kg-d
    to units
    of
    ig/L,
    whereas
    an inhalation
    unit
    risk
    is developed
    directly
    from
    a dose-
    response
    analysis
    using
    equivalent
    human
    concentrations
    already
    expressed
    in
    units
    of
    ig/m
    3
    .
    Unit
    risk
    estimates
    often
    assume
    a
    standard
    intake
    rate
    (L/day
    drinking
    water
    or
    m
    3
    /day
    air)
    and
    body
    weight
    (kg), which
    may need
    to
    be
    reconciled
    with
    the
    exposure
    factors
    for
    the
    population
    of
    interest
    in
    an
    exposure
    assessment
    (see
    Section
    4.4).
    Alternatively,
    when
    the
    slope
    factor
    for
    inhalation
    is
    in
    units
    of ppm,
    it may
    sometimes
    be
    termed
    the
    inhalation
    unit risk.
    Although
    unit
    risks
    have
    not
    been
    calculated
    in the
    past
    for
    dermal
    exposures,
    both
    exposures
    that
    are
    absorbed
    into
    the
    systemic
    circulation
    and
    those
    that
    remain
    in
    contact
    with
    the
    skin
    are
    also important.
    Risk-specific
    doses
    are derived
    from
    the slope
    factor
    or unit
    risk
    to estimate
    the dose
    associated with a
    specific
    risk
    level,
    for example,
    a one-in-a-million
    increased
    lifetime
    risk.
    3.3.4.
    Nonlinear
    Extrapolation
    to Lower
    Doses
    A
    nonlinear
    extrapolation
    method
    can
    be used
    for
    cases
    with
    sufficient
    data
    to
    ascertain
    the
    mode
    of action
    and
    to
    conclude
    that it
    is not
    linear
    at low
    doses
    but
    with
    not enough
    data
    to
    support
    a
    toxicodynamic model
    that may
    be
    either
    nonlinear
    or linear
    at
    low doses.
    Nonlinear
    extrapolation
    having
    a
    significant
    biological
    support
    may
    be
    presented
    in addition
    to a linear
    approach
    when
    the available
    data
    and
    a
    weight
    of
    evidence
    evaluation
    support
    a
    nonlinear
    3-23

    approach, but the data are not strong
    enough to ascertain the mode of action
    applying the
    Agency’s mode of action
    framework. If the mode of action and other information
    can support
    chemical-specific
    modeling at low doses, it is preferable to default
    procedures.
    For cases where the tumors arise
    through
    a
    nonlinear
    mode
    of action,
    an oral reference
    dose or an inhalation reference
    concentration, or both, should be developed in
    accordance
    with
    EPA’s
    established practice for developing
    such values, taking into consideration
    the factors
    summarized in the
    characterization of the POD (see Section 3.2.5). This approach expands
    the
    past focus of such
    reference values (previously reserved for effects other than cancer)
    to include
    carcinogenic effects
    determined to have a nonlinear mode of action. As with other
    health
    effects
    of concern, it is important to put
    cancer in perspective with the overall health
    impact of an
    exposure by
    comparing reference
    value calculations for cancer with those for
    other health
    effects.
    For effects other than cancer, reference values have been
    described
    as being based
    on the
    assumption of biological thresholds. The Agency’s more current
    guidelines
    for these effects
    (U.S.
    EPA, 1996a, l998b),
    however,
    do
    not use this assumption, citing the
    difficulty of
    empirically
    distinguishing a true threshold from a dose-response curve that is nonlinear
    at low
    doses.
    Economic and policy
    analysts need
    to
    know how
    the
    probability
    of cancer varies
    at
    exposures
    above
    the reference value and whether, and to what extent, there are health
    benefits
    from
    reducing exposures below the reference value.
    The
    risk assessment community is
    working
    to develop
    better methods to provide more useful information to economic and policy
    analysts.
    3.3.5.
    Comparing and
    Combining Multiple
    Extrapolations
    When multiple estimates can be
    developed, all
    datasets should be considered and
    a
    judgment made
    about how best to represent the human cancer risk. Some options
    for presenting
    results
    include:
    adding risk estimates derived from different tumor sites (NRC, 1994),
    3-24

    combining
    data
    from
    different
    datasets
    in
    a
    joint
    analysis
    (Putzrath
    and
    Ginevan,
    1991;
    Stiteler
    et
    al.,
    1993;
    Vater
    et
    al.,
    1993),
    combining
    responses
    that
    operate
    through
    a
    common
    mode
    of
    action,
    representing
    the
    overall
    response
    in
    each
    experiment
    by
    counting
    animals
    with
    any
    tumor
    showing
    a
    statistically
    significant
    increase,
    presenting
    a
    range
    of
    results
    from
    multiple
    datasets
    (in
    this
    case,
    the
    dose-response
    assessment
    includes
    guidance
    on
    how
    to
    choose
    an
    appropriate
    value
    from
    the
    range),
    choosing
    a
    single
    dataset
    if
    it
    can
    be
    justified
    as
    most
    representative
    of
    the
    overall
    response
    in
    humans,
    or
    a
    combination
    of
    these
    options.
    Cross-comparison
    of
    estimates
    from
    human
    and
    animal
    studies
    can
    provide
    a
    valuable
    risk
    perspective.
    Calculating
    an
    animal-derived
    slope
    factor
    and
    using
    it
    to
    estimate
    the
    risk
    expected
    in
    a
    human
    study
    can
    provide
    information
    with
    which
    to
    evaluate
    the
    human
    study
    design,
    for
    example,
    adequacy
    of
    exposure
    level
    and
    sample
    size.
    Calculating
    an
    upper-bound
    slope
    factor
    from
    a
    human
    study
    that
    does
    not
    show
    positive
    results
    but
    that
    has
    good
    exposure
    information,
    and
    comparing
    it
    to
    an
    animal-derived
    slope
    factor
    can
    indicate
    whether
    the
    animal
    and
    humans
    studies
    are
    consistent.
    3-25

    3.4.
    EXTRAPOLATION
    TO DIFFERENT
    HUMAN
    EXPOSURE
    SCENARIOS
    As
    described
    in
    the
    previous
    cancer
    guidelines,
    special
    problems
    arise
    when
    the
    human
    exposure
    situation
    of
    concern
    suggests
    exposure
    regimens,
    e.g.,
    route
    and
    dosing
    schedule,
    that
    are
    substantially
    different
    from
    those
    used
    in
    the
    relevant
    animal
    studies.
    Unless
    there
    is
    evidence
    to
    the
    contrary
    in a particular
    case,
    the
    cumulative
    dose
    received
    over
    a
    lifetime,
    expressed
    as average
    daily
    exposure
    prorated
    over
    a
    lifetime,
    is recommended
    as
    an
    appropriate
    measure
    of
    exposure
    to a
    carcinogen.
    That
    is, the
    assumption
    is made
    that
    a high
    dose
    of
    a
    carcinogen
    received
    over
    a short
    period
    of
    time
    is equivalent
    to a
    corresponding
    low dose
    spread
    over
    a
    lifetime.
    This
    approach
    becomes
    more
    problematical
    as
    the
    exposures
    in
    question
    become
    more
    intense
    but
    less
    frequent,
    especially
    when
    there
    is evidence
    that
    the
    agent
    has
    shown
    dose-
    rate
    effects
    (U.S.
    EPA
    l986a).
    Accordingly,
    for
    lfetime
    human
    exposure
    scenarios
    that
    involve
    intermittent
    or varying
    levels
    of
    exposure,
    the
    prevailing
    practice
    has
    been
    to
    assess
    exposure
    by
    calculating
    a lifetime
    average
    daily
    exposure
    or
    dose
    (U.S.
    EPA,
    1992a).
    For
    less-than-lifetime
    human
    exposure
    scenarios,
    too,
    the
    lifetime
    average
    daily
    exposure
    or
    dose
    has
    often
    been
    used.
    The
    use
    of
    these
    lifetime
    average
    exposure
    metrics
    was
    adopted
    with
    low-dose
    linear
    cancer
    assessments
    in
    mind.
    The
    lifetime
    averaging
    implies
    that
    less-than-
    lifetime
    exposure
    is associated
    with
    a linearly
    proportional
    reduction
    of the
    lifetime
    risk,
    regardless
    of
    when
    exposures
    occur.
    Such
    averaging
    may
    be
    problematic
    in
    some
    situations.
    This
    can
    be
    illustrated
    using
    both
    the
    multistage
    model
    and
    the
    two-stage
    clonal
    expansion
    model
    that
    predict
    that
    short-duration
    risks
    are
    not necessarily
    proportional
    to
    exposure
    duration
    and
    can
    depend
    on
    the
    nature
    of
    the
    carcinogen
    and
    the
    timing
    of exposure
    (Goddard
    et
    al.,
    1995;
    Murdoch
    et
    al., 1992).
    These
    examples
    indicate
    some
    circumstances
    in which
    use of
    a
    lifetime
    average
    daily
    dose
    (LADD)
    would
    underestimate
    cancer
    risk
    by two-
    to
    fivefold,
    and
    others
    in
    which
    it
    might
    overestimate
    risk
    (Murdoch
    et al.,
    1992).
    Thus,
    averaging
    over
    the
    duration
    of
    a
    lifestage
    or a
    critical
    window
    of exposure
    may
    be
    appropriate.
    As
    methodological
    research
    focuses
    on
    new
    approaches
    for
    estimating
    risks
    from
    less-than-lifetime
    exposures,
    methods
    and
    defaults
    can
    be
    expected
    to
    change.
    3-26

    This
    highlights
    the
    importance
    for
    each
    dose-response
    assessment
    to
    critically
    evaluate
    all
    information
    pertaining
    to
    less-than-lifetime
    exposure.
    For
    example,
    detailed
    stop-exposure
    studies
    can
    provide
    information
    about
    the
    relationship
    between
    exposure
    duration,
    precursor
    effects,
    potential
    for
    reversibility,
    and
    tumor
    development.
    Toxicokinetic
    modeling
    can
    investigate
    differences
    in internal
    dose
    between
    short-term
    and
    long-term
    exposure
    or
    between
    intermittent
    and
    constant
    exposure.
    Persistence
    in
    the body
    can
    be
    useful
    in
    explaining
    long-term
    effects
    resulting
    from
    shorter-term
    exposures.
    For
    nonlinear
    cancer
    analyses,
    it may
    be
    appropriate
    to
    assess
    exposure
    by
    calculating
    a
    daily
    dose
    that
    is
    averaged
    over
    the
    exposure
    duration
    for the
    study
    (see
    Section
    3.1.1).
    For
    example,
    when
    the
    analysis
    is
    based
    on
    precursor
    effects
    that
    result
    from
    less than
    a
    lifetime
    exposure,
    that
    exposure
    period
    may
    be used.
    This
    reflects
    an expectation
    that
    the
    precursor
    effects
    on which
    the
    analysis
    is based
    can result
    from
    less-than-lifetime
    exposure,
    bringing
    consistency
    to the
    methods
    used
    for dose-response
    assessment
    and
    exposure
    assessment
    in
    such
    cases.
    The
    dose-response
    assessment
    can
    provide
    a
    recommendation
    to exposure
    assessors
    about
    the
    averaging time
    that is
    appropriate
    to
    the
    mode
    of
    action
    and to
    the exposure
    duration
    of
    the
    scenario.
    3.5.
    EXTRAPOLATION
    TO
    SUSCEPTIBLE
    POPULATIONS
    AND
    LIFESTAGES
    The
    dose-response assessment
    strives
    to derive
    separate
    estimates
    for susceptible
    populations and
    lifestages
    so
    that these
    risks can
    be
    explicitly
    characterized.
    For
    a
    susceptible
    population,
    higher
    risks
    can
    be
    expected
    from
    exposures
    anytime
    during
    life,
    but
    this
    applies
    to
    only
    a
    portion
    of
    the
    general
    population
    (e.g.,
    those
    bearing
    a particular
    genetic
    susceptibility).
    In contrast, for a
    susceptible
    lifestage,
    higher
    risks can
    be
    expected
    from
    exposures
    during
    only
    a
    portion
    of a
    lifetime,
    but
    everyone
    in the
    population
    may
    pass
    through
    those
    lifestages.
    Effects
    of
    exposures
    during
    a
    susceptible
    period
    are
    not
    equivalent
    to effects
    of
    exposures
    at
    other
    times;
    consequently,
    it is useful
    to
    estimate
    the
    risk attributable
    to exposures
    during
    each
    period.
    Depending
    on the
    data
    available,
    a
    tiered
    approach
    should
    be
    used
    to
    address
    susceptible
    populations and
    lifestages.
    3-27

    When
    there
    is an
    epidemiologic
    study
    or
    an animal
    bioassay
    that
    reports
    quantitative
    results
    for
    susceptible
    individuals,
    the
    data
    should
    be
    analyzed
    to
    provide
    a
    separate
    risk
    estimate
    for those
    who
    are
    susceptible.
    If susceptibility
    pertains
    to a
    lifestage,
    it
    is
    useful
    to
    characterize
    the
    portion
    of
    the lifetime
    risk
    that
    can
    be
    attributed
    to
    the
    susceptible
    lifestage.
    When
    there are
    data
    on
    some
    risk-related
    parameters
    that allow
    comparison
    of
    the
    general
    population
    and
    susceptible
    individuals,
    the
    data should
    be
    analyzed
    with
    an
    eye toward
    adjusting
    the general
    population
    estimate
    for
    susceptible
    individuals.
    This
    analysis
    can
    range
    from
    toxicokinetic
    modeling
    that
    uses
    parameter
    values
    representative
    of susceptible
    individuals
    to
    more
    simply
    adjusting
    a
    general
    population
    estimate
    to
    reflect
    differences
    in important
    rate-governing
    parameters.
    Care
    is taken
    to not
    make
    parameter
    adjustments
    in isolation,
    as the
    appropriate
    adjustment
    can
    depend
    on
    the
    interactions
    of
    several
    parameters;
    for
    example,
    the
    ratio
    of
    metabolic
    activation
    and
    clearance
    rates
    can be
    more
    appropriate
    than
    the
    activation
    rate
    alone
    (U.S.
    EPA,
    1
    992b).
    In the
    absence
    of
    such
    agent-specific
    data,
    there
    is
    some
    general
    information
    to
    indicate
    that
    childhood
    can
    be
    a
    susceptible
    lifestage
    for
    exposure
    to
    some
    carcinogens
    (U.S.
    EPA,
    2005);
    this
    warrants
    explicit
    consideration
    in
    each
    assessment. The
    potential
    for
    susceptibility
    from
    early-life
    exposure
    is
    expected
    to
    vary
    among
    specific
    agents
    and
    chemical
    classes.
    In
    addition,
    the
    concern
    that
    the
    dose-averaging
    generally used
    for
    assessing
    less-than-lifetime
    exposure
    is
    more
    likely
    to
    understate
    than
    overstate
    risk
    (see
    Section
    3.4)
    contributes
    to the
    suggestion that
    alternative
    approaches
    be
    considered
    for
    assessing
    risks
    from
    less
    than-lifetime exposure
    that
    occurs
    during
    childhood.
    Accompanying
    these
    cancer
    guidelines
    is
    the
    Supplemental
    Guidance
    that
    the
    Agency
    will
    use
    to assess
    risks
    from
    early-life
    exposure
    to potential
    carcinogens
    (U.S.
    EPA,
    2005).
    The
    Supplemental Guidance
    may
    be updated
    to
    reflect
    new
    data
    and
    new
    understanding
    that
    may
    become
    available
    in the
    future.
    3-28

    3.6. UNCERTAINTY
    The
    NRC
    (1983,
    1994,
    1996,
    2002)
    has
    repeatedly
    advised
    that
    proper
    characterization
    of
    uncertainty
    is
    essential
    in risk
    assessment.
    An
    assessment
    that
    omits
    or
    underestimates
    uncertainty
    can
    leave
    decisionmakers
    with
    a false
    sense
    of confidence
    in
    estimates
    of
    risk.
    On
    the
    other
    hand,
    a
    high level
    of uncertainty
    does
    not
    imply
    that
    a risk
    assessment
    or a risk
    management
    action
    should
    be
    delayed
    (NRC,
    2002).
    Uncertainty
    in dose-response
    assessment
    can
    be
    classified
    as either
    model
    uncertainty
    orparanzeter
    uncertainty.
    A related
    concept,
    human
    variation,
    is
    discussed
    below.
    Assessments
    should
    discuss
    the
    significant
    uncertainties
    encountered
    in
    the
    analysis,
    distinguishing,
    if
    possible,
    between
    model
    uncertainty,
    parameter
    uncertainty,
    and
    human
    variation.
    Origins
    of
    these
    uncertainties
    can
    span
    a
    range,
    from
    a
    single
    causal
    thread
    supported
    by
    sparse
    data,
    to
    abundant
    information
    that
    presents
    multiple
    possible
    conclusions
    or
    that
    does not
    coalesce.
    As
    described
    in Section
    2.6
    and
    in
    Section
    5.1,
    all
    contributing features
    should
    be
    noted.
    Model
    uncertainty
    refers
    to a lack
    of
    knowledge
    needed
    to
    determine
    which
    is
    the
    correct
    scientific
    theory
    on
    which
    to base
    a model.
    In
    risk
    assessment,
    model
    uncertainty
    is
    reflected
    in
    alternative
    choices
    for model
    structure,
    dose
    metrics,
    and
    extrapolation
    approaches.
    Other
    sources
    of
    model
    uncertainty
    concern
    whether
    surrogate
    data are
    appropriate,
    for example,
    using
    data on
    adults
    to make
    inferences
    about children.
    The
    full extent
    of model
    uncertainty
    usually
    cannot
    be quantified;
    a partial
    characterization
    can be
    obtained
    by
    comparing
    the
    results
    of
    alternative
    models.
    Model
    uncertainty
    is expressed
    through
    comparison
    of
    separate
    analyses
    from each
    model,
    coupled
    with
    a
    subjective
    probability
    statement,
    where
    feasible
    and
    appropriate,
    of
    the
    likelihood
    that
    each
    model
    might
    be correct
    (NRC,
    1994).
    Some
    aspects
    of model
    uncertainty
    that
    should
    be addressed
    in an
    assessment
    include
    the
    use
    of
    animal
    models
    as a
    surrogate
    for humans,
    the influence
    of cross-species
    differences
    in
    metabolism
    and
    physiology,
    the
    use of effects
    observed
    at high
    doses
    as
    an
    indicator
    of the
    potential
    for
    effects
    at
    lower doses,
    the
    effect
    of using
    linear
    or nonlinear
    extrapolation
    to
    estimate
    risks,
    the
    use of using
    small
    samples
    and subgroups
    to make
    inferences
    about
    entire
    human
    populations
    or
    subpopulations
    with differential
    susceptibilities,
    and
    the
    use
    of
    3-29

    experimental
    exposure
    regimens
    to
    make
    inferences
    about
    different
    human
    exposure
    scenarios
    (NRC,
    2002).
    Toxicokinetic
    and
    toxicodynamic
    models
    are
    generally
    premised
    on site
    concordance
    across
    species,
    modeling,
    for example,
    the
    relationship
    between
    administered
    dose
    and
    liver
    tissue
    concentrations
    to
    predict
    increased incidences
    of
    liver
    cancer.
    This
    relationship,
    which
    can
    be observed in
    animals,
    is
    typically
    only
    inferred
    for humans.
    There
    are,
    however,
    numerous
    examples
    of
    an
    agent
    causing
    different
    cancers
    in
    different
    species.
    The
    assessment
    should
    discuss
    the
    relevant
    data
    that bear
    on
    this
    form
    of
    model
    uncertainty.
    Parameter
    uncertainty
    refers
    to
    a
    lack
    of
    knowledge
    about
    the
    values
    of a
    model’s
    parameters.
    This
    leads
    to
    a distribution of
    values
    for each
    parameter.
    Common
    sources
    of
    parameter uncertainty
    include
    random
    measurement
    errors,
    systematic
    measurement
    errors,
    use
    of
    surrogate
    data instead
    of direct
    measurements,
    misclassification
    of
    exposure
    status,
    random
    sampling
    errors,
    and use
    of an
    unrepresentative
    sample.
    Most
    types
    of parameter
    uncertainty
    can
    be
    quantified
    by statistical analysis.
    Human
    variation
    refers
    to
    person-to-person
    differences
    in biological
    susceptibility
    or
    in
    exposure.
    Although
    both
    human
    variation
    and uncertainty
    can
    be
    characterized
    as
    ranges
    or
    distributions,
    they
    are
    fundamentally
    different
    concepts.
    Uncertainty
    can
    be reduced
    by
    further
    research
    that
    supports
    a model
    or
    improves
    a
    parameter
    estimate,
    but
    human
    variation
    is
    a reality
    that
    can be
    better
    characterized,
    but
    not reduced,
    by
    further
    research.
    Fields
    other
    than
    risk
    assessment use “variation”
    or
    “variability”
    to
    mean
    dispersion
    about
    a
    central
    value,
    including
    measurement errors
    and
    other
    random
    errors
    that
    risk
    assessors
    address
    as uncertainty.
    Probabilistic
    risk
    assessment,
    informed
    by
    expert
    judgment,
    has
    been
    used
    in
    exposure
    assessment
    to
    estimate
    human
    variation
    and uncertainty
    in
    lifetime
    average
    daily
    exposure
    concentration or
    dose.
    Probabilistic
    methods
    can
    be used
    in
    this exposure
    assessment
    application
    because
    the pertinent variables
    (for
    example,
    concentration,
    intake
    rate,
    exposure
    duration,
    and
    body
    weight)
    have
    been
    identified,
    their
    distributions
    can
    be
    observed,
    and
    the
    formula
    for
    combining
    the
    variables
    to
    estimate
    the
    lifetime
    average
    daily
    dose
    is
    well
    defined
    (see
    U.S.
    EPA,
    1 992a).
    Similarly,
    probabilistic methods
    can
    be
    applied
    in
    dose-response
    assessment
    when
    there
    is an
    understanding
    of
    the
    important
    parameters
    and their
    relationships,
    such
    as
    3-30

    identification
    of
    the
    key
    determinants
    of human
    variation
    (for example,
    metabolic
    polymorphisms,
    hormone
    levels,
    and cell
    replication
    rates),
    observation
    of the
    distributions
    of
    these
    variables,
    and
    valid models
    for
    combining
    these
    variables.
    With
    appropriate
    data
    and
    expert
    judgment,
    formal
    approaches
    to
    probabilistic
    risk assessment
    can
    be
    applied
    to
    provide
    insight
    into
    the
    overall
    extent
    and
    dominant
    sources
    of
    human
    variation
    and
    uncertainty.
    In
    doing
    this,
    it is
    important
    to
    note that
    analyses
    that
    omit or
    underestimate
    some
    principal
    sources
    of
    variation
    or
    uncertainty
    could
    provide
    a
    misleadingly
    narrow
    description
    of
    the true
    extent
    of
    variation
    and
    uncertainty
    and give
    decisionmakers
    a
    false
    sense
    of
    confidence
    in estimates
    of
    risk.
    Specification
    ofjoint
    probability
    distributions
    is
    appropriate
    when
    variables
    are not
    independent
    of
    each other.
    In
    each case,
    the
    assessment
    should
    carefully
    consider
    the questions
    of
    uncertainty
    and human
    variation
    and
    discuss
    the
    extent to
    which
    there are
    data
    to address
    them.
    Probabilistic
    risk
    assessment
    has
    also
    been
    used
    in
    dose-response
    assessment
    to
    determine
    and
    distinguish
    the
    degree
    of uncertainty
    and variability
    in
    toxicokinetic
    and
    toxicodynamic
    modeling.
    Although
    this
    field
    is
    less
    advanced
    that probabilistic
    exposure
    assessment,
    progress
    is
    being
    made and
    these
    cancer
    guidelines
    are flexible
    enough
    to
    accommodate
    continuing
    advances
    in these
    approaches.
    Advances
    in uncertainty
    analysis
    are expected
    as
    the field
    develops.
    The
    cancer
    guidelines
    are
    intended
    to be
    flexible
    enough
    to
    incorporate
    additional
    approaches
    for
    characterizing
    uncertainty
    that have
    less
    commonly
    been
    used by
    regulatory
    agencies.
    In
    all
    scientific
    and
    engineering
    fields,
    data and
    research
    limitations
    often
    limit
    the application
    of
    established
    methods.
    A
    dearth
    of
    data
    is
    a
    particular
    problem
    when quantifying
    the
    probability
    distribution
    of
    model
    outputs.
    In
    many
    of these
    scientific
    and
    engineering
    disciplines,
    researchers
    have used
    rigorous
    expert
    elicitation
    methods
    to
    overcome
    the
    lack of
    peer-reviewed
    methods
    and
    data.
    Although
    expert
    elicitation
    has
    not been
    widely
    used
    in
    environmental
    risk
    assessment,
    several
    studies
    have applied
    this
    methodology
    as
    a
    tool
    for understanding
    quantitative
    risk.
    For
    example,
    expert
    elicitation
    has been
    used
    in chemical
    risk
    assessment
    and its associated
    uncertainty
    (e.g.,
    Richmond,
    1981;
    Renn,
    1999;
    Florig
    et al.,
    2001;
    Morgan
    et al.,
    2001; Willis
    et
    al., 2004),
    components
    of
    risk
    assessment
    such
    as
    hazard
    assessment
    and
    dose-response
    3-31

    evaluation
    (e.g.,
    Hawkins
    and Graham
    1988; Jelovsek
    et
    al.,
    1990;
    Evans
    et al.,
    1994;
    lEe, 2004;
    U.S.
    EPA
    2004)
    and
    exposure
    assessment
    (e.g., Whiffield
    and
    Wallsten,
    1989;
    Hawkins
    and
    Evans,
    1989;
    Winkler
    et
    al., 1995;
    Stiber
    et al.,
    1999;
    Walker
    et al.,
    2001, 2003;
    Van Der
    Fels
    Klerx
    et al.,
    2002),
    and
    for
    evaluating
    other
    types of
    risks
    (e.g.,
    North
    and
    Merkhofer,
    1976;
    Fos
    and
    McLin,
    1990).
    These
    cancer
    guidelines
    are
    flexible
    enough
    to
    accommodate
    the use
    of
    expert
    elicitation
    to
    characterize
    cancer
    risks,
    as a complement
    to
    the methods
    presented
    in the
    cancer
    guidelines.
    According
    to
    NRC
    (NRC,
    2002),
    the
    rigorous
    use
    of expert
    elicitation
    for
    the
    analyses
    of
    risks is
    considered
    to
    be
    quality
    science.
    3.7. DOSE-RESPONSE
    CHARACTERIZATION
    A dose-response characterization
    extracts
    the dose-response
    information
    needed
    in
    a full
    risk
    characterization
    (US.
    EPA, 2000b),
    including:
    presentation
    of
    the recommended
    estimates
    (slope
    factors,
    reference
    doses,
    reference
    concentrations)
    and alternatives
    with
    significant
    biological
    support,
    a
    summary
    of the data
    supporting
    these
    estimates,
    a
    summary
    and
    explanation
    of the modeling
    approaches
    used,
    a
    description
    of
    any special
    features
    such
    as the
    development
    and
    consolidation
    of
    multiple
    estimates
    as
    detailed
    in
    Section
    3.3.5,
    the
    POD narrative
    (see
    Section
    3.2.5),
    a
    summary
    of the
    key defaults
    invoked,
    identification
    of susceptible
    populations
    or
    lifestages
    and
    quantification
    of their
    differential
    susceptibility,
    and
    3-32

    a
    discussion
    of
    the
    strengths
    and
    limitations
    of the
    dose-response
    assessment,
    highlighting
    significant
    issues
    in
    developing
    risk
    estimates,
    alternative
    approaches
    considered equally
    plausible,
    and
    how
    these
    issues
    were resolved.
    All
    estimates
    should
    be
    accompanied
    by the
    weight
    of
    evidence
    descriptor and
    its
    narrative
    (see Section
    2.5)
    to
    convey
    a
    sense
    of
    the qualitative uncertainty
    about
    whether
    the
    agent
    may
    or may
    not
    be
    carcinogenic.
    Slope
    factors
    generally
    represent
    an
    upper
    bound
    on the
    average
    risk
    in
    a
    population
    or
    the
    risk for
    a
    randomly
    selected
    individual
    but
    not
    the
    risk
    for
    a
    highly
    susceptible
    individual
    or
    group.
    Some
    individuals face
    a
    higher
    risk
    and
    some
    face
    a lower
    risk.
    The use
    of
    upper
    bounds
    generally
    is
    considered
    to
    be
    a health-protective
    approach
    for
    covering
    the risk
    to
    susceptible
    individuals,
    although
    the
    calculation
    of upper
    bounds
    is
    not
    based
    on
    susceptibility
    data.
    Similarly,
    exposure
    during
    some
    lifestages
    can
    contribute
    more
    or
    less
    to
    the total
    lifetime
    risk
    than
    do
    similar
    exposures
    at
    other
    times.
    The
    dose-response
    assessment
    characterizes,
    to the
    extent
    possible,
    the
    extent
    of
    these
    variations.
    Depending
    on
    the
    supporting
    data
    and
    modeling
    approach,
    a
    slope
    factor
    can
    have
    a
    mix
    of
    traits
    that tend
    to
    either
    estimate,
    overestimate,
    or underestimate
    risk.
    Some
    examples
    of
    traits
    that
    tend
    to overestimate
    risk
    include
    the
    following.
    The slope
    factor
    is
    derived
    from
    data
    on
    a highly
    susceptible
    animal
    strain.
    Linear
    extrapolation
    is used
    as
    a
    default
    and
    extends
    over
    several
    orders
    of
    magnitude.
    The
    largest
    of
    several
    slope
    factors
    is chosen.
    Some
    examples
    of
    traits
    that
    tend
    to underestimate
    risk
    include
    the
    following.
    3-33

    Several
    tumor
    types
    were
    observed,
    but
    the
    slope
    factor
    is
    based
    on
    a
    subset
    of
    them.
    The
    study
    design
    does
    not
    include
    exposure
    during
    a
    susceptible
    lifestage,
    for
    example,
    perinatal
    exposure.
    The
    study
    population
    is
    of
    less-than-average
    susceptibility,
    for
    example,
    healthy
    adult
    workers.
    There
    is
    random
    exposure
    misclassification
    or
    random
    exposure
    measurement
    error
    in
    the
    study
    from
    which
    the
    slope
    factor
    is
    derived.
    Some
    examples
    of
    traits
    that
    inherently
    neither
    overestimate
    nor
    underestimate
    risk
    include
    the
    following.
    The
    slope
    factor
    is
    derived
    from
    data
    in
    humans
    or
    in
    an
    animal
    strain
    that
    responds
    like
    humans.
    Linear
    extrapolation
    is
    appropriate
    for
    the
    agent’s
    mode
    of
    action.
    Environmental
    exposures
    are
    close
    to
    the
    observed
    data.
    Several
    slope
    factors
    for
    the
    same
    tumor
    are
    averaged
    or
    a
    slope
    factor
    is
    derived
    from
    pooled
    data
    from
    several
    studies.
    The
    slope
    factor
    is
    derived
    from
    the
    only
    suitable
    study.
    3-34

    Figure
    3-1.
    Compatibility
    of alternative
    points
    of
    departure
    with
    observed
    and modeled
    tumor
    incidences
    15%-
    X
    Observed
    tumor
    incidence
    Modeled
    tumor
    incidence
    Extrapolations
    from
    LED
    10 and
    LEDO1
    10%-
    5%-
    -
    0
    0%-
    “..
    0
    5
    10
    15
    Figure 3-2.
    Crossing--between 10%
    and 1%--of
    dose-response
    curves
    for
    bladder
    carcinomas
    and
    liver
    carcinomas
    induced
    by
    2-AAF
    X
    Observed
    bladder
    tumors
    10%
    bladder
    Extrapolations
    Modeled
    tumorsbladder
    from
    tumors
    LED1O
    and
    LEDO1
    for
    /
    /
    Observed
    liver
    tumors
    Modeled
    liver
    tumors
    Extrapolation
    from LED1O
    and LEDO)
    ftr
    liver
    tumors
    5%
    ——
    _
    0%
    .
    .
    .
    -..
    0
    50
    100
    150
    3-35

    4.
    EXPOSURE
    ASSESSfVEENT
    Exposure
    assessment
    is the
    determination
    (qualitative
    and quantitative)
    of
    the magnitude,
    frequency,
    and
    duration
    of exposure
    and
    internal
    dose
    (U.S.
    EPA,
    1
    992a).
    This
    section
    provides
    a brief
    overview
    of exposure
    assessment
    principles,
    with
    an emphasis
    on
    issues
    related
    to
    carcinogenic
    risk assessment.
    The
    information
    presented
    here
    should
    be
    used
    in conjunction
    with other
    guidance
    documents,
    including
    Guidelines
    for Exposure
    Assessment
    (U.S.
    EPA,
    1992a),
    Science
    Policy
    Council
    Handbook:
    Risk Characterization
    (U.S.
    EPA,
    2000b),
    Exposure
    Factors
    Handbook
    (U.S.
    EPA,
    1997c),
    the
    1997 Policy
    for
    Use
    ofProbabilistic
    Analysis
    in
    Risk
    Assessments
    (U.S.
    EPA, 1997d),
    and the
    1997 Guiding
    Principles
    for
    Monte
    Carlo
    Analysis
    (U.S.
    EPA,
    1997e).
    In addition,
    program-specific
    guidelines
    for exposure
    assessment
    should
    be
    consulted.
    Exposure
    assessment
    generally
    consists
    of
    four major
    steps: defining
    the assessment
    questions,
    selecting
    or
    developing
    the conceptual
    and
    mathematical
    models,
    collecting
    data
    or
    selecting
    and
    evaluating
    available
    data,
    and
    exposure
    characterization.
    Each
    of these
    steps
    is
    briefly
    described
    below.
    4.1. DEFINING
    THE
    ASSESSMENT
    QUESTIONS
    In providing
    a clear
    and
    unambiguous
    statement
    of
    the
    purpose
    and
    scope
    of
    the
    exposure
    assessment
    (U.S.
    EPA,
    1997e),
    consider
    the
    following.
    The
    management
    objectives
    of
    the assessment
    will
    determine
    whether
    deterministic
    screening
    level
    analyses
    are
    adequate
    or whether
    full
    probabilistic
    exposure
    characterization
    is
    needed.
    Identify
    and
    include
    all important
    sources
    (e.g.,
    pesticide
    applications),
    pathways
    (e.g.,
    food
    or water),
    and
    routes
    (e.g.,
    ingestion,
    inhalation,
    and
    derrnal)
    of
    exposure
    in
    the
    assessment.
    If
    a
    particular
    source,
    pathway,
    or
    route
    is
    omitted,
    a clear
    and
    transparent
    explanation
    should
    be
    provided.
    4-1

    Separate
    analyses
    should
    be
    conducted
    for
    each definable
    subgroup
    within
    the
    population
    of
    interest.
    In
    particular,
    subpopulations
    or
    life
    stages
    that
    are
    believed
    to
    be
    highly
    exposed
    or
    susceptible
    to a
    particular
    health
    effect
    should
    be studied.
    These
    include
    people
    with
    certain
    diseases
    or
    genetic
    susceptibilities
    and
    others
    whose
    behavior
    or
    physiology
    may
    lead
    to higher
    exposure
    or
    susceptibility.
    Consider
    the
    following
    examples:
    Physiological
    differences
    between
    men
    and
    women
    (e.g.,
    body
    weight
    and
    inhalation
    rate)
    may
    lead
    to
    important
    differences
    in
    exposures.
    See,
    for
    example,
    the
    discussion
    in
    Exposure
    Factors
    Handbook
    (U.S.
    EPA,
    1997c,
    Appendix
    1A).
    Pregnant
    and
    lactating
    women
    may
    have
    exposures
    that
    differ
    from
    the
    general
    population
    (e.g.,
    slightly
    higher
    water
    consumption)
    (U.S.
    EPA,
    1 997c).
    Further, exposure
    to
    pregnant
    women
    may
    result
    in
    exposure
    to
    the
    developing
    fetus
    (NRC,
    1993b).
    Children
    consume
    more
    food
    per
    body
    weight
    than
    do adults
    while
    consuming
    fewer
    types
    of foods,
    i.e.,
    have
    a more
    limited
    diet (ILSI,
    1992;
    NRC,
    l993b;
    U.S.
    EPA,
    1997c).
    In
    addition,
    children
    engage
    in
    crawling
    and
    mouthing
    (i.e.,
    putting
    hands
    and
    objects
    in the
    mouth)
    behaviors,
    which
    can
    increase
    their exposures.
    The
    elderly
    and
    disabled
    may
    have
    important
    differences
    in their
    exposures
    due
    to a
    more
    sedentary
    lifestyle
    (U.S.
    EPA,
    1997c).
    In
    addition,
    the
    health
    status
    of
    this
    group
    may
    affect
    their susceptibility
    to
    the
    detrimental
    effects
    of exposure.
    For
    further
    guidance,
    see
    Guidelines
    for
    Exposure
    Assessment
    (U.S.
    EPA,
    1992a,
    §
    3).
    4-2

    4.2.
    SELECTING
    OR
    DEVELOPING
    THE
    CONCEPTUAL
    AND
    MATHEMATICAL
    MODELS
    Carcinogen
    risk
    assessment
    models
    have
    generally
    been
    based
    on
    the
    premise
    that
    risk
    is
    proportional
    to
    cumulative
    lifetime
    dose.
    For
    lifetime
    human
    exposure
    scenarios,
    therefore,
    the
    exposure
    metric
    used
    for
    carcinogenic
    risk
    assessment
    has
    been
    the
    lifetime
    average
    daily
    dose
    (LADD)
    or,
    in
    the
    case
    of
    inhalation
    exposure,
    the
    lifetime
    average
    exposure
    concentration.
    These
    metrics
    are
    typically
    used
    in
    conjunction
    with
    the
    corresponding
    slope
    factor
    to
    calculate
    individual
    excess
    cancer
    risk.
    The
    LADD
    is
    typically
    an
    estimate
    of
    the
    daily
    intake
    of
    a
    carcinogenic
    agent
    throughout
    the
    entire
    life
    of
    an
    individual,
    while
    the
    lifetime
    average
    exposure
    concentration
    is
    the
    corresponding
    estimate
    of
    average
    exposure
    concentration
    for
    the
    carcinogenic
    agent
    over
    the
    entire
    life
    of
    an
    individual.
    Depending
    on
    the
    objectives
    of
    the
    assessment,
    the
    LADD
    or
    lifetime
    average
    exposure
    concentration
    may
    be
    calculated
    deterministically
    (using
    point
    estimates
    for
    each
    factor
    to
    derive
    a
    point
    estimate
    of
    the
    exposure)
    or
    stochastically
    (using
    probability
    distributions
    to
    represent
    each
    factor
    and
    such
    techniques
    as
    Monte
    Carlo
    analysis
    to
    derive
    a
    distribution
    of
    the
    LADD)
    (U.S.
    EPA,
    1997e).
    Stochastic
    analyses
    may
    help
    to
    identify
    certain
    population
    segments
    or
    lifestages
    that
    are
    highly
    exposed
    and
    may
    need
    to
    be
    assessed
    as a
    special
    subgroup.
    For
    further
    guidance,
    see
    Guidelines
    for
    Exposure
    Assessment
    (U.S.
    EPA,
    l992a,
    §
    5.3.5.2).
    As
    methodological
    research
    focuses
    on
    new
    approaches
    for
    estimating
    risks
    from
    less-than-lifetime
    exposures,
    methods
    and
    defaults
    can
    be
    expected
    to
    change.
    There
    may
    be
    cases
    where
    the
    mode
    of
    action
    indicates
    that
    dose
    rates
    are
    important
    in
    the
    carcinogenic
    process.
    In
    these
    cases,
    short-term,
    less-than-lifetime
    exposure
    estimates
    may
    be
    more
    appropriate
    than
    the
    LADD
    for
    risk
    assessment.
    This
    may
    be
    the
    case
    when
    a
    nonlinear
    dose-response
    approach
    is
    used
    (see
    Section
    3.3.4).
    4.3.
    COLLECTING
    DATA
    OR
    SELECTING
    AND
    EVALUATING
    AVAILABLE
    DATA
    After
    the
    assessment
    questions
    have
    been
    defined
    and
    the
    conceptual
    and
    mathematical
    models
    have
    been
    developed,
    it
    is
    important
    to
    compile
    and
    evaluate
    existing
    data
    or,
    if
    necessary,
    to
    collect
    new
    data.
    Depending
    on
    the
    exposure
    scenario
    under
    consideration,
    data
    on
    4-3

    a
    wide
    variety
    of
    exposure
    factors
    may
    be
    needed.
    EPA’s
    Exposure
    Factors
    Handbook
    (U.S.
    EPA,
    1 997c)
    contains
    a
    large
    compilation
    of exposure data,
    with
    some
    analysis
    and
    recommendations.
    Some
    of these
    data
    are
    organized
    by
    age groups
    to assist
    with
    assessing
    such
    subgroups
    as
    children.
    See,
    for
    example,
    Exposure
    Factors
    Handbook
    (U.S.
    EPA,
    1997c,
    Volume
    1,
    Chapter
    3).
    When
    using
    these
    existing
    data,
    it
    is important
    to evaluate
    the
    quality
    of
    the data
    and
    the
    extent
    to
    which
    the
    data
    are representative
    of
    the
    population
    under
    consideration.
    EPA’s
    (U.S.
    EPA,
    2000d)
    and OMB’s
    (0MB
    2002)
    guidance
    on
    information
    quality,
    as
    well
    as
    program-specific
    guidances
    can
    provide
    further
    assistance
    for
    evaluating
    existing
    data.
    When
    existing
    data
    fail
    to provide
    an adequate
    surrogate
    for
    the
    needs
    of
    a particular
    assessment,
    it
    is important
    to
    collect
    new
    data.
    Such
    data
    collection
    efforts
    should
    be
    guided
    by
    the
    references
    listed
    above
    (e.g.,
    Guidance
    for
    Data
    Quality
    Assessment
    and program-specific
    guidance).
    Once
    again,
    subpopulations
    or lifestages
    of
    concern
    are
    an
    important
    consideration
    in
    any
    data
    collection
    effort.
    4.3.1.
    Adjusting
    Unit
    Risks
    for
    Highly
    Exposed
    Populations
    and
    Lifestages
    Unit
    risk estimates that
    have
    been
    developed
    in the
    dose-response
    assessment
    often
    assumed standard
    adult
    intake
    rates.
    When
    an
    exposure
    assessment
    focuses
    on
    a population
    or
    lifestage
    with
    differential
    exposure,
    good
    exposure
    assessment
    practice
    would
    replace
    the
    standard
    intake
    rates
    with
    values
    representative
    of
    the
    exposed
    population.
    Small
    changes
    in
    exposure assessments
    can
    be
    approximated
    by using
    linearly
    proportional
    adjustments
    of
    exposure
    parameters,
    but
    a more
    accurate
    integrative
    analysis
    may
    require
    an
    analysis
    stratified
    by
    exposure
    duration
    (see
    Section
    5.1).
    For
    example, to adjust
    the
    drinking
    water
    unit
    risk for
    an
    active
    population
    that
    drinks
    4
    L/day
    (instead
    of
    2 Llday),
    multiply
    the
    unit
    riskby2.
    4-4

    Because
    children
    drink more
    water
    relative
    to
    their body
    weight
    than
    do
    adults
    (U.S.
    EPA,
    2002d),
    adjustments
    to
    unit
    risk
    estimates
    are warranted
    whenever
    they
    are applied
    in
    an
    assessment
    of
    childhood
    exposure.
    For
    example,
    to
    adjust
    the drinking
    water
    unit risk
    for
    a
    9-kg infant
    who
    drinks
    1
    L/day
    (instead
    of
    a 70-kg
    adult who
    drinks
    2 L/day),
    multiply
    the unit
    risk
    by [(1 L/day)
    / (9
    kg)]
    /
    [(2
    L/day)
    / (70 kg)]
    =
    3.9.
    Inhalation
    dosimetry
    is
    employed
    to
    derive
    the
    human
    equivalent
    exposure
    concentrations
    on which
    inhalation
    unit
    risks,
    and
    reference
    concentrations,
    are
    based
    (U.S.
    EPA, 1994).
    As
    described
    previously
    (see
    Sections
    3.1.2,
    3.1.3),
    different
    dosimetry
    methods
    may
    be employed
    depending
    on
    the
    availability
    of
    relevant
    data
    and
    chemical-specific
    characteristics
    of
    the
    pollutant.
    Consideration
    of
    lifestage-particular
    physiological
    characteristics
    in the
    dosimetry
    analysis
    may
    result
    in a
    refinement
    to the
    human
    equivalent
    concentration
    (HEC)
    to insure
    relevance
    in
    risk
    assessment
    across
    lifestages,
    or might
    conceivably
    conclude
    with
    multiple
    HECs,
    and
    corresponding
    inhalation
    unit
    risk
    values (e.g.,
    separate
    for childhood
    and
    adulthood).
    The
    dose-response
    assessment
    discusses
    the
    key sources
    of uncertainty
    in
    estimating
    dosimetry,
    including
    any
    related
    to
    lifestage.
    Review
    of
    this discussion
    and
    of the
    dosimetric
    analysis
    performed
    in
    deriving
    the
    HEC
    and resultant
    unit risk
    will
    assist
    in the appropriate
    application
    of
    inhalation
    unit
    risk
    values
    to
    exposure
    across
    lifestages.
    4.4.
    EXPOSURE
    CHARACTERIZATION
    The
    exposure
    characterization
    is a technical
    characterization
    that
    presents
    the
    assessment
    results
    and
    supports
    the risk
    characterization.
    It
    provides
    a statement
    of
    the
    purpose,
    scope,
    and
    approach
    used
    in
    the assessment,
    identifying
    the exposure
    scenarios
    and
    population
    subgroups
    covered.
    It
    provides
    estimates
    of
    the magnitude,
    frequency,
    duration,
    and distribution
    of
    exposures
    among
    members
    of
    the
    exposed
    population
    as the
    data
    permit.
    It identifies
    and
    compares
    the
    contribution
    of
    different
    sources,
    pathways,
    and routes
    of
    exposure.
    In particular,
    a
    4-5

    qualitative
    discussion
    of
    the strengths
    and
    limitations
    (uncertainties)
    of the
    data and
    models
    are
    presented.
    The discussion
    of uncertainties
    is a
    critical
    component
    of
    the exposure
    characterization.
    Uncertainties
    can arise
    out of problems
    with
    the conceptual
    and
    mathematical
    models.
    Uncertainties
    can
    also
    arise
    from poor
    data quality
    and
    data
    that are
    not quite
    representative
    of
    the
    population
    or scenario
    of interest.
    Consider
    the
    following
    examples
    of uncertainties.
    National
    data (i.e.,
    data
    collected
    to represent
    the
    entire
    U.S.
    population)
    may not
    be
    representative
    of
    exposures
    occurring
    within
    a regional
    or
    local
    population.
    Use
    of short-term
    data
    to infer
    chronic,
    lifetime
    exposures
    should
    be done
    with
    caution.
    Use
    of
    short-term
    data to
    estimate
    long-term
    exposures
    has
    the
    tendency
    to
    underestimate
    the
    number
    of
    people
    exposed while
    overestimating
    the
    exposure
    levels
    experienced
    by
    those in
    the
    upper
    end (i.e., above
    the
    9O
    percentile)
    of
    the
    exposure
    distribution.
    For
    further
    guidance,
    refer to Guidelines
    for
    Exposure
    Assessment
    (U.S.
    EPA,
    1992a,
    §
    5.3.1).
    Children’s
    behavior,
    including
    their
    more
    limited
    diet, may
    lead to
    relatively
    high
    but
    intermittent
    exposures.
    This
    pattern of
    exposure,
    “one that
    gradually
    declines
    over
    the
    developmental
    period
    and which
    remains
    relatively
    constant
    thereafter”
    is
    not
    accounted
    for in the LADD
    model
    (ILSI,
    1992). Further,
    the
    physiological
    characteristics
    of
    children
    may
    lead
    to
    important
    differences
    in exposure.
    Some
    of
    these
    differences
    can
    be
    accounted
    for in
    the LADD
    model.
    For
    further
    guidance,
    see
    Guidelines
    for Exposure
    Assessment
    (U.S.
    EPA,
    l992a,
    §
    5.3.5.2).
    Overall, the
    exposure
    characterization
    should
    provide a
    full
    description
    of the
    sources,
    pathways,
    and routes
    of exposure.
    The
    characterization
    also
    should include
    a full
    description
    of
    the populations
    assessed.
    In
    particular,
    highly
    exposed
    or susceptible
    subpopulation
    or
    lifestage
    should
    be
    discussed.
    For further
    guidance
    on
    the exposure
    characterization,
    consult
    Guidelines
    4-6

    for
    Exposure
    Assessment
    (U.S.
    EPA,
    1
    992a),
    the
    Policy
    and
    Guidance
    for
    Risk
    Characterization
    (U.S.
    EPA,
    2000b,1995)
    and
    EPA’s
    Rule
    Writer’s’
    Guide
    to
    Executive
    Order
    13045
    (especially
    Attachment
    C:
    Technical
    Support
    for
    Risk
    Assessors—Suggestions
    for
    Characterizing
    Risks
    to
    Children
    [U.S.
    EPA,
    1998d]).
    4-7

    5. RISK
    CHARACTERIZATION
    5.1. PURPOSE
    EPA has
    developed
    general
    guidance
    on risk
    characterization
    for
    use in its
    risk
    assessment
    activities.
    The
    core of EPA’s
    risk
    characterization
    policy
    (U.S.
    EPA,
    2000b,
    1995)
    includes
    the
    following.
    Each
    risk
    assessment
    prepared
    in support
    of
    decision making
    at EPA
    should
    include
    a
    risk
    characterization
    that
    follows
    the principles
    and
    reflects
    the
    values
    outlined
    in this
    policy.
    A
    risk
    characterization
    should
    be
    prepared
    in
    a
    manner that
    is clear,
    transparent,
    reasonable,
    and
    consistent
    with other
    risk
    characterizations
    of similar scope
    prepared
    across
    programs
    in
    the Agency.
    Further,
    discussion
    of risk
    in all EPA
    reports,
    presentations,
    decision
    packages,
    and
    other
    documents
    should
    be
    substantively
    consistent
    with the
    risk
    characterization.
    The
    nature
    of the
    risk characterization
    will
    depend
    upon
    the information
    available,
    the
    regulatory
    application
    of the
    risk
    information,
    and the
    resources
    (including
    time) available.
    In
    all
    cases,
    however,
    the
    assessment
    should identif,
    and discuss
    all
    the major
    issues
    associated
    with
    determining
    the
    nature
    and
    extent of
    the risk
    and
    provide
    commentary
    on any
    constraints
    limiting
    fuller
    exposition.
    Risk
    characterization
    should
    be carried
    out in accordance
    with
    the
    EPA
    (U.S.
    EPA,
    2002a) and
    0MB (2002)
    information
    quality
    guidelines.
    EPA’s
    risk characterization
    handbook
    (U.S.
    EPA,
    2000b)
    provides detailed
    guidance
    to Agency
    staff.
    The discussion
    below
    does
    not
    attempt
    to duplicate
    this material,
    but it
    summarizes
    its applicability
    to
    carcinogen
    risk
    assessment.
    The risk
    characterization
    includes
    a summary
    for
    the risk manager
    in a
    nonteclmical
    discussion
    that
    minimizes
    the use of
    technical
    terms. It
    is an appraisal
    of
    the
    science
    that
    informs
    the
    risk
    manager
    in public health
    decisions,
    as do other
    decision-making
    analyses
    of
    economic,
    5-1

    social,
    or
    technology
    issues.
    It also
    serves
    the
    needs
    of other
    interested
    readers.
    The
    summary
    is
    an information
    resource
    for
    preparing
    risk
    communication
    information,
    but
    being
    somewhat
    more
    technical
    than
    desired
    for
    communication
    with
    the
    general
    public,
    is
    not
    itself
    the
    usual
    vehicle
    for
    communication
    with
    every
    audience.
    The
    risk
    characterization
    also
    brings
    together
    the
    assessments
    of hazard,
    dose
    response,
    and
    exposure
    to
    make
    risk
    estimates
    for
    the
    exposure
    scenarios
    of
    interest.
    This
    analysis
    that
    follows
    the
    summary
    is generally
    much
    more
    extensive.
    It
    typically
    will
    identify
    exposure
    scenarios
    of
    interest
    in decision
    making
    and
    present
    risk
    analyses
    associated
    with
    them.
    Some
    of
    the
    analyses
    may
    concern
    scenarios
    in
    several
    media;
    others
    may
    examine,
    for
    example,
    only
    drinking
    water
    risks.
    As these
    cancer
    guidelines
    allow
    different
    hazard
    characterizations
    and
    different
    potencies
    for
    specified
    conditions,
    e.g.,
    exposure
    level,
    route
    of exposure,
    or
    lifestage,
    some
    of the
    integrative
    analyses
    may
    need
    to be
    stratified
    to accommodate
    the
    appropriate
    combinations
    of
    parameters
    across
    relevant
    exposure
    durations.
    In
    constructing
    high
    end
    estimates
    of risk,
    the
    assessor
    should
    bear
    in
    mind
    that
    the
    high-
    end
    risk is
    a
    plausible
    estimate
    of
    the risk
    for
    those
    persons
    at
    the upper
    end
    of the
    risk
    distribution
    (U.S.
    EPA,
    1992a).
    The intent
    of this
    approach
    is
    to
    convey
    an
    estimate
    of
    risk
    in
    the
    upper
    range
    of the
    distribution,
    but
    to avoid
    estimates
    that
    are beyond
    the
    true
    distribution.
    Overly
    conservative
    assumptions,
    when
    combined,
    can
    lead
    to unrealistic
    estimates
    of
    risk.
    This
    means
    that
    when
    constructing
    estimates
    from
    a
    series
    of factors
    (e.g.,
    emissions,
    exposure,
    and
    unit
    risk
    estimates)
    not
    all factors
    should
    be set
    to values
    that maximize
    exposure,
    dose,
    or effect,
    since
    this
    will
    almost
    always
    lead
    to
    an
    estimate
    that is
    above
    the
    99th-percentile
    confidence
    level
    and
    may
    be of
    limited
    use
    to decisionmakers.
    This
    is
    particularly
    problematic
    when
    using
    unbounded lognormal
    factor
    distributions.
    While
    it is an
    appropriate
    aim
    to
    assure
    protection
    of
    health
    and
    the environment
    in
    the
    face
    of
    scientific
    uncertainty,
    common
    sense,
    reasonable
    applications
    of
    assumptions
    and
    policy,
    and
    transparency
    are
    essential
    to
    avoid
    unrealistically
    high
    estimates.
    It
    is
    also
    important
    to
    inform
    risk
    managers
    of
    the
    final
    distribution
    of risk
    estimates
    (U.S.
    EPA,
    2000b;
    1995).
    Otherwise, risk
    management
    decisions
    may
    be
    made
    on
    varying
    levels
    of conservatism,
    leading
    5-2

    to
    misplaced
    risk
    priorities and
    potentially
    higher
    overall
    risks.
    (Nichols
    and
    Zeckhauser,
    1986;
    Zeckhauser
    and
    Viscusi,1990).
    The
    risk characterization
    presents
    an
    integrated
    and balanced
    picture
    of the
    analysis
    of
    the
    hazard,
    dose-response,
    and
    exposure.
    The
    risk
    analyst
    should
    provide
    summaries
    of
    the
    evidence
    and results
    and describe
    the
    quality
    of
    available
    data
    and
    the
    degree
    of confidence
    to
    be
    placed
    in
    the
    risk estimates.
    Important
    features
    include
    the
    constraints
    of available
    data
    and
    the
    state
    of
    knowledge, significant
    scientific
    issues,
    and significant
    science
    and
    science
    policy
    choices
    that
    were
    made
    when
    alternative
    interpretations
    of
    data
    exist
    (U.S.
    EPA,
    1995,
    2000b).
    Choices
    made
    about
    using
    data
    or
    default
    options
    in
    the
    assessment
    are
    explicitly
    discussed
    in
    the
    course
    of
    analysis,
    and
    if a
    choice
    is a
    significant
    issue,
    it
    is
    highlighted
    in
    the
    summary.
    In
    situations
    where
    there
    are
    alternative approaches
    for
    a risk
    assessment
    that
    have
    significant
    biological
    support,
    the
    decisionmaker
    can
    be
    informed
    by
    the presentation
    of
    these
    alternatives
    along
    with
    their
    strengths
    and
    uncertainties.
    5.2.
    APPLICATION
    Risk
    characterization
    is
    a
    necessary
    part
    of
    generating
    any
    Agency
    report
    on
    risk,
    whether
    the report
    is
    preliminary
    — to
    support
    allocation
    of
    resources
    toward
    further
    study
    or
    comprehensive
    — to
    support
    regulatory
    decisions.
    In
    the
    former
    case,
    the
    detail
    and
    sophistication
    of the
    characterization
    are
    appropriately
    small
    in scale;
    in
    the
    latter
    case,
    appropriately extensive.
    Even
    if a document
    covers
    only
    parts
    of a
    risk
    assessment
    (hazard
    and
    dose-response analyses,
    for
    instance),
    the
    results
    of
    these
    are
    characterized.
    Risk
    assessment
    is
    an
    iterative
    process
    that
    grows
    in
    depth
    and scope
    in
    stages
    from
    screening
    for
    priority
    making
    to
    preliminary
    estimation
    to fuller
    examination
    in
    support
    of
    complex
    regulatory
    decision
    making.
    Default
    options
    may
    be used
    at
    any
    stage,
    but they
    are
    predominant at screening
    stages
    and
    are
    used
    less as
    more
    data
    are gathered
    and
    incorporated
    at
    later
    stages.
    Various
    provisions
    in EPA-administered
    statutes
    require
    decisions
    based
    on
    differing
    findings
    for
    which
    differing
    degrees
    of
    analysis
    are
    appropriate.
    There
    are
    close
    to
    30
    provisions
    within
    the
    major
    statutes
    that
    require
    decisions
    based
    on
    risk,
    hazard,
    or
    exposure
    assessment.
    For
    example,
    Agency
    review
    of
    pre-manufacture
    notices
    under
    Section
    5 of
    the Toxic
    Substances
    5-3

    Control
    Act
    relies
    on
    screening
    analyses,
    whereas
    requirements
    for
    industry
    testing
    under
    Section
    4 of
    that
    Act
    rely
    on
    preliminary
    analyses
    of
    risk
    or
    simply
    of exposure.
    In
    comparison,
    air
    quality
    criteria
    under
    the
    Clean
    Air
    Act
    rest
    on
    a rich
    data
    collection
    and are
    required
    by
    statute
    to undergo
    periodic
    reassessment.
    There
    are
    provisions
    that
    require
    ranking
    of
    hazards
    of
    numerous
    pollutants
    which
    may
    be addressed
    through
    a screening level
    of analysis
    and
    other
    provisions
    for which
    a
    full assessment
    of risk
    is
    more
    appropriate.
    Given
    this
    range
    in the
    scope
    and
    depth
    of analyses,
    not all
    risk
    characterizations
    can
    or
    should
    be equal
    in
    coverage
    or
    depth.
    The
    risk
    assessor
    should
    carefully
    decide
    which
    issues
    in a
    particular
    assessment
    are important
    to present,
    choosing
    those
    that
    are
    noteworthy
    in
    their
    impact
    on results.
    For
    example,
    health
    effect
    assessments
    typically
    rely
    on animal
    data
    because
    human
    data
    are
    rarely
    available.
    The objective
    of
    characterization
    of the
    use
    of animal
    data
    is
    not
    to
    recount
    generic
    issues
    about
    interpreting
    and
    using
    animal
    data;
    Agency
    guidance
    documents
    cover
    these
    issues.
    Rather,
    the
    objective is to
    highlight
    any significant
    issues
    that
    arose
    within
    the
    particular
    assessment
    being
    characterized
    and
    inform
    the
    reader
    about
    significant
    uncertainties
    that
    affect
    conclusions.
    5.3.
    PRESENTATION
    OF
    THE
    RISK
    CHARACTERIZATION
    SUMMARY
    The
    presentation
    is
    a
    nontechnical
    discussion
    of
    important
    conclusions,
    issues,
    and
    uncertainties that
    uses
    the
    hazard,
    dose
    response,
    exposure,
    and
    integrative
    analyses
    for
    technical
    support.
    The
    primary
    technical
    supports within
    the
    risk
    assessment
    are the
    hazard
    characterization,
    dose-response
    characterization,
    and
    exposure
    characterization
    described
    in
    these
    cancer
    guidelines.
    The
    risk
    characterization
    is
    derived
    from
    these.
    The
    presentation
    should
    fulfill
    the
    aims
    outlined
    in
    the
    purpose
    section
    above.
    5.4.
    CONTENT OF THE
    RISK
    CHARACTERIZATION
    SUMMARY
    Specific
    guidance
    on
    hazard,
    dose-response,
    and
    exposure
    characterization
    appears
    in
    previous
    sections.
    Overall,
    the
    risk
    characterization
    routinely
    includes
    the
    following,
    capturing
    the
    important
    items
    covered
    in hazard,
    dose
    response,
    and
    exposure
    characterization:
    5-4

    primary
    conclusions
    about
    hazard,
    dose
    response,
    and exposure,
    including
    alternatives
    with significant
    biological
    support;
    nature
    of
    key
    supporting
    information
    and analytic
    methods;
    risk estimates
    and their
    attendant
    uncertainties,
    including
    key
    uses
    of default
    options
    when
    data are
    missing
    or uncertain.
    With
    linear
    extrapolations,
    risk
    below
    the POD
    is
    typically
    approximated
    by
    multiplying
    the
    slope
    factor
    by
    an
    estimate
    of
    exposure,
    i.e.,
    Risk
    =
    Slope
    Factor
    x Exposure.
    For
    exposure
    levels
    above
    the
    POD,
    the dose-
    response
    model
    is
    used
    instead
    of
    this approximation.
    With
    nonlinear
    extrapolations,
    the method
    of
    risk assessment
    depends
    on
    the
    procedure
    used.
    If
    a
    nonlinear
    dose-response
    function
    has
    been
    determined,
    it
    can be
    used with
    the expected
    exposure
    to
    estimate
    a risk.
    If
    an RID
    or
    RfC
    was calculated,
    the hazard
    can
    be expressed
    as a hazard
    quotient
    (HQ),
    defined
    as the
    ratio
    of an
    exposure
    estimate
    over the
    reference
    dose
    (RID)
    or
    reference
    concentration
    (RIO),
    i.e.,
    HQ =
    Exposure
    /
    (RID
    or RfC).
    From
    the
    hazard
    quotient,
    it
    can generally
    be
    inferred
    whether
    the nonlinear
    mode of
    action
    is
    relevant
    at
    the
    environmental
    exposure
    level
    in question;
    statement
    of the
    extent
    of extrapolation
    of risk
    estimates
    from observed
    data
    to
    exposure
    levels
    of
    interest
    and
    its
    implications
    for certainty
    or
    uncertainty
    in
    quantifying
    risk.
    The
    extent of
    extrapolation
    can
    be
    expressed
    as
    a margin
    of
    exposure
    (MOE),
    defined
    as the
    ratio of
    the POD
    over
    an
    exposure
    estimate
    (MOE
    =
    POD
    / Exposure);
    5-5

    significant
    strengths
    and
    limitations
    of
    the
    data
    and
    analyses,
    including
    any
    major
    peer
    review
    issues;
    appropriate
    comparison
    with
    similar
    EPA
    risk
    analyses
    or
    common
    risks
    with
    which
    people
    may
    be
    familiar; and
    comparison
    with
    all
    appropriate
    assessments
    of
    the
    same
    problem
    by
    others.
    It is
    often
    difficult
    to know
    a
    priori
    when
    or
    how
    different
    results
    of a
    cancer
    risk
    assessment
    are
    likely
    to be
    used
    by Agency
    economists,
    policy
    analysts,
    and
    decisionmakers,
    so
    it
    is important
    that
    the
    resulting
    characterizations
    include
    the necessary
    infonnation
    for these
    analyses
    to
    the
    extent
    practicable.
    0MB
    and
    EPA
    guidelines
    for
    benefit-cost
    analysis
    require
    expected
    or
    central
    estimates
    of risk
    and
    information
    on
    the
    uncertainty
    of
    the
    estimate
    when
    it is
    possible
    or
    practicable.
    The
    extent
    of
    the uncertainty
    information
    needed
    for
    analysis
    depends,
    in
    part,
    on the
    scale
    of the
    policy
    being
    considered,
    with
    formal
    quantitative
    analysis
    of
    uncertainty
    being
    required
    in
    some
    cases.
    6
    0MB
    Circular
    A-4
    (0MB,
    2003)
    emphasizes
    that
    agencies
    “should
    try
    to
    provide
    some
    estimate
    of the
    probability
    distribution
    of regulatory
    benefits
    and
    costs.”
    These
    0MB
    guidelines
    note,
    “Whenever
    it is possible
    to characterize
    quantitatively
    the
    probability
    distribution,
    some
    estimates
    of
    expected
    value
    ... must
    be
    provided
    in
    addition
    to
    ranges,
    variances,
    specified
    low-end
    and
    high-end
    percentile
    estimates,
    and
    other
    characteristics
    of
    the
    distribution.”
    The risk
    characterization
    should
    therefore
    include,
    where
    practicable,
    expected
    or
    central
    estimates
    of
    risk,
    as
    well
    as
    upper
    and
    lower
    bounds,
    e.g.,
    confidence
    limits,
    based
    on the
    POD,
    if not
    a
    full
    characterization
    of uncertainty
    of the
    risk.
    As discussed
    in
    EPA’s
    Guidelines
    for
    Ensuring
    and
    Maximizing the
    Quality,
    Objectivity,
    Utility,
    and
    Integrity
    of
    Information
    Disseminated
    by the
    Environmental
    Protection
    Agency
    (Appendix
    B),
    statutory
    mandates, such
    as the
    Safe
    Drinking
    Water
    Act,
    the
    Food
    Quality
    Protection
    Act, and
    the
    Clean
    6
    Specifically,
    0MB
    guidelines
    state:
    “For rules
    that
    exceed
    the
    $1
    billion
    annual
    [economic
    effects]
    threshold,
    a
    formal
    quantitative
    analysis
    of
    uncertainty
    is required.
    For rules
    with
    annual
    benefits
    and/or
    costs
    in
    the
    range from
    100
    million
    to
    $1
    billion,
    you should
    seek
    to use
    more
    rigorous
    approaches
    with
    higher
    consequence
    rules”
    (0MB,
    2003,
    page 158)
    5-6

    Air
    Act, call
    for
    the
    Agency
    to generate
    specific
    kinds
    of
    risk information,
    and thus
    these
    updated
    cancer
    assessment
    guidelines
    should
    be read
    in
    conjunction
    with
    the
    Agency’s statutory
    mandates
    regarding
    risk
    assessment.
    5-7

    APPENDIX
    A:
    MAJOR
    DEFAULT
    OPTIONS
    This
    discussion
    covers
    the
    major
    default
    options
    commonly
    employed
    when
    data
    are
    missing
    or
    sufficiently
    uncertain
    in
    a
    cancer
    risk
    assessment,
    as
    adopted
    in
    these
    cancer
    guidelines.
    These
    options
    are
    predominantly
    inferences
    that
    help
    use
    the
    data
    observed
    under
    empirical
    conditions
    in
    order
    to
    estimate
    events
    and
    outcomes
    under
    environmental
    conditions.
    Several
    inferential
    issues
    arise
    when
    effects
    seen
    in
    a
    subpopulation
    of
    humans
    or
    animals
    are
    used
    to
    infer
    potential
    effects
    in
    the
    population
    of
    environmentally
    exposed
    humans.Several
    more
    inferential
    issues
    arise
    in
    extrapolating
    the
    exposure-effect
    relationship
    observed
    empirically
    to
    lower-exposure
    environmental
    conditions.
    The
    following
    issues
    cover
    the
    major
    default
    areas.
    Is
    the
    presence
    or
    absence
    of
    effects
    observed
    in
    a
    human
    population
    predictive
    of
    effects
    in
    another
    exposed
    human
    population?
    Is
    the
    presence
    or
    absence
    of
    effects
    observed
    in
    an
    animal
    population
    predictive
    of
    effects
    in
    exposed
    humans?
    How
    do
    metabolic
    pathways
    relate
    across
    species
    and
    among
    different
    age
    groups
    and
    between
    sexes
    in
    humans?
    How
    do
    toxicokinetic
    processes
    relate
    across
    species
    and
    among
    different
    age
    groups
    and
    between
    sexes
    in
    humans?
    V/hat
    is
    the
    relationship
    between
    the
    observed
    dose-response
    relationship
    to
    the
    relationship
    at
    lower
    doses?
    A-i

    Is the
    Presence
    or Absence
    of
    Effects
    Observed
    in a Human
    Population
    Predictive
    of
    Effects
    in Another
    Exposed
    Human
    Population?
    When
    cancer
    effects
    in exposed
    humans
    are
    attributed
    to
    exposure
    to
    an agent,
    the
    default
    option
    is
    that
    the resulting
    data
    are predictive
    of
    cancer
    in
    any
    other
    exposed
    human
    population.
    Most
    studies
    investigating
    cancer
    outcomes
    in
    humans
    from
    exposure
    to
    agents
    are
    often
    studies
    of occupationally
    exposed
    humans.
    By
    sex,
    age,
    and
    general
    health,
    workers
    may
    not
    be
    representative
    of the
    general
    population
    exposed
    environmentally
    to the
    same
    agents.
    In
    such
    studies
    there
    is no
    opportunity
    to
    observe
    subpopulations
    who
    are
    likely
    to be
    under
    represented,
    such as
    fetuses,
    infants
    and children,
    women,
    or people
    in
    poor
    health,
    who
    may
    respond
    differently
    from
    healthy
    workers.
    Therefore,
    it is
    understood
    that
    this
    option
    could
    still
    underestimate
    the
    response of certain
    human
    subpopulations
    (NRC,
    1
    993b,
    1994).
    When
    cancer
    effects
    are not
    found
    in
    an exposed
    human
    population,
    this information
    by
    itself
    is
    not generally
    sufficient
    to
    conclude
    that
    the
    agent
    poses
    no carcinogenic
    hazard
    to
    this
    or other
    populations
    ofpotentially
    exposed
    humans,
    including
    susceptible
    subpopulations
    or
    lifestages. This
    is because epidemiologic
    studies
    often
    have
    low
    power
    to detect
    and
    attribute
    responses
    and
    typically
    evaluate
    cancer
    potential
    in
    a restricted
    population
    (e.g.,
    by
    age,
    healthy
    workers).
    The
    topic
    of
    susceptibility
    and
    variation
    is addressed
    further
    in
    the
    discussion
    below
    of
    quantitative
    default
    options
    about
    dose-response
    relationships.
    Well-conducted
    studies
    that
    fail
    to detect
    a
    statistically
    significant
    positive
    association,
    however,
    may
    have
    value
    and
    should
    be
    judged
    on
    their
    merits,
    including
    population
    size,
    duration
    of
    the study,
    the
    quality
    of
    the
    exposure
    characterization and
    measures
    of
    outcome,
    and
    the
    magnitude
    and duration
    of
    the
    exposure.
    There
    is not
    yet
    enough
    knowledge
    to
    form
    a
    basis
    for
    any
    generally
    applicable
    qualitative
    or
    quantitative
    inference
    to
    compensate
    for the
    gap
    in
    knowledge
    concerning
    other
    populations.
    In these
    cancer
    guidelines,
    this
    problem
    is
    left
    to analysis
    in
    individual
    cases,
    to
    be attended
    to
    with
    further
    general
    guidance
    as future
    research
    and
    information
    allow.
    When
    information
    on
    a
    susceptible
    subpopulation
    or
    lifestage
    exists,
    it will
    be
    used.
    For
    example,
    an
    agent
    such
    as
    diethylstilbestrol
    (DES)
    causes
    a
    rare
    form
    of
    vaginal
    cancer
    (clear-cell
    adenocarcinoma)
    (Herbst
    A-2

    et
    al., 1971)
    in about
    1 per
    1000
    of
    adult
    women
    whose
    mothers
    were
    exposed
    during
    pregnancy
    (Hatchet
    al.,
    1998).
    Is the
    Presence
    or
    Absence
    ofEffects
    Observed
    in
    an
    Animal
    Population
    Predictive
    of
    Effects
    in Exposed
    Humans?
    The default
    option
    is that
    positive
    effects
    in animal
    cancer
    studies
    indicate
    that
    the
    agent
    under
    study
    can
    have
    carcinogenic
    potential
    in humans.
    Thus,
    if
    no
    adequate
    human
    or
    mode
    of action
    data
    are
    present,
    positive
    effects
    in
    animal
    cancer
    studies
    are
    a
    basis
    for
    assessing
    the
    carcinogenic
    hazard
    to
    humans.
    This
    option
    is
    a public
    health-protective
    policy,
    and
    it is both
    appropriate
    and
    necessary,
    given
    that
    we
    do not
    test
    for carcinogenicity
    in
    humans.
    The
    option
    is
    supported
    by
    the
    fact
    that
    nearly
    all of
    the agents
    known
    to
    cause
    cancer
    in
    humans
    are
    carcinogenic
    in animals
    in
    tests
    that
    have
    adequate
    protocols
    (IARC,
    1994;
    Tomatis
    et
    al., 1989;
    Huff,
    1994).
    Moreover,
    almost
    one-third
    of
    human
    carcinogens
    were
    identified subsequent
    to animal
    testing
    (Huff,
    1993).
    Further
    support
    is provided
    by
    research
    on
    the
    molecular
    biology
    of
    cancer
    processes,
    which
    has shown
    that the
    mechanisms
    of
    control
    of
    cell
    growth
    and differentiation
    are
    remarkably
    homologous
    among
    species
    and highly
    conserved
    in
    evolution.
    Nevertheless, the same
    research
    tools
    that
    have
    enabled
    recognition
    of the
    nature
    and
    commonality
    of cancer
    processes
    at
    the molecular
    level
    also
    have
    the
    power
    to reveal
    differences and
    instances
    in which
    animal
    responses
    are not
    relevant
    to
    humans
    (Lijinsky,
    1993;
    U.S.
    EPA,
    1991 b).
    Under
    these
    cancer
    guidelines,
    available
    mode
    of action
    information
    is
    studied
    for
    its
    implications
    in both
    hazard
    and
    dose-response
    assessment
    and
    its
    ability
    to
    obviate
    default
    options.
    There
    may
    be
    instances
    in
    which
    the
    use
    of
    an
    animal
    model
    would
    identify
    a
    hazard
    in
    animals
    that
    is not
    truly
    a
    hazard
    in
    humans
    (e.g.,
    the
    alpha-2u-globulin
    association
    with
    renal
    neoplasia
    in
    male
    rats
    [U.S.
    EPA,
    1991
    bJ).
    The extent
    to which
    animal
    studies
    may
    yield
    false
    positive
    indications
    for
    humans
    is
    a
    matter
    of scientific
    debate.
    To demonstrate
    that
    a
    response
    in
    animals
    is
    not
    relevant
    to
    any human
    situation,
    adequate
    data
    to assess
    the
    relevancy
    issue
    are
    important.
    In
    general,
    while
    effects
    seen
    at
    the highest
    dose
    tested
    are
    assumed
    to
    be
    appropriate
    for
    assessment, it
    is
    necessary
    that the
    experimental
    conditions
    be
    scrutinized.
    Animal
    studies
    A-3

    are
    conducted
    at high
    doses in
    order
    to
    provide
    statistical
    power,
    the
    highest
    dose
    being
    one
    that
    is minimally
    toxic (maximum
    tolerated
    dose
    or MTD).
    Consequently,
    the
    question
    often arises
    of whether
    a
    carcinogenic
    effect
    at
    the
    highest
    dose may
    be a consequence
    of cell
    killing with
    compensatory
    cell replication
    or
    of general
    physiological
    disruption
    rather
    than
    inherent
    carcinogenicity
    of
    the tested
    agent.
    There
    is little
    doubt
    that
    this may
    happen
    in
    some cases,
    but
    skepticism
    exists
    among
    some scientists
    that
    it
    is
    a
    pervasive
    problem
    (Ames
    and Gold,
    1990;
    Melnick
    et
    al.,
    1993; Barrett,
    1993).
    If
    adequate
    data
    demonstrate
    that the
    effects
    are
    solely
    the
    result
    of excessive
    toxicity
    rather
    than
    carcinogenicity
    of
    the tested
    agent
    per
    Se, then
    the effects
    may
    be regarded
    as
    not
    appropriate
    to include
    in
    assessment
    of
    the potential
    for human
    carcinogenicity
    of the
    agent.
    This
    is a matter
    of expert
    judgment,
    with
    consideration
    given
    to
    all
    of
    the
    data
    available
    about
    the agent,
    including
    effects
    in
    other
    toxicity
    studies,
    structure-activity
    relationships,
    and
    effects
    on
    growth
    control
    and
    differentiation.
    When
    cancer
    effects
    are
    notfound
    in well-conducted
    animal
    cancer
    studies
    in
    two or
    more
    appropriate
    species
    and
    other
    information
    does
    not
    support
    the
    carcinogenic
    potential
    of
    the agent,
    these
    data
    provide
    a basis
    for concluding
    that the
    agent
    is
    not
    likely
    to possess
    human
    carcinogenic
    potential
    in
    the absence
    of
    human
    data to
    the
    contrary.
    This default
    option
    about
    lack
    of cancer
    effects
    has limitations.
    it is recognized
    that animal
    studies
    (and epidemiologic
    studies
    as
    well)
    have
    very low
    power
    to detect
    cancer
    effects.
    Detection
    of a
    10%
    tumor
    incidence
    is generally
    the
    limit
    of power
    with
    standard
    protocols
    for
    animal
    studies
    (with
    the
    exception
    of
    rare
    tumors
    that
    are
    virtually
    markers
    for
    a particular
    agent,
    e.g.,
    angiosarcoma
    caused
    by
    vinyl
    chloride).
    In some
    situations,
    the
    tested animal
    species
    may
    not
    be
    predictive
    of
    effects
    in humans;
    for example,
    arsenic
    shows
    only
    minimal
    or
    no effect
    in animals,
    whereas
    it is
    clearly
    positive
    in
    humans.
    Therefore,
    it
    is important
    to
    consider
    other
    information
    as well;
    absence
    of
    mutagenic
    activity
    or
    absence
    of
    carcinogenic
    activity
    among
    structural
    analogues
    can
    increase
    the
    confidence
    that
    negative
    results
    in animal
    studies
    indicate
    a
    lack
    of human
    hazard.
    Another
    limitation
    is
    that
    standard
    animal
    study
    protocols
    are
    not yet
    available
    for
    effectively
    studying
    perinatal
    effects.
    The
    potential
    for effects
    on the very
    young
    generally
    should
    be considered
    separately.
    Under
    existing
    Agency
    policy
    (U.S.
    EPA,
    1
    997a,
    b),
    perinatal
    studies
    A-4

    accomplished
    by
    modification
    of
    existing
    adult
    bioassay
    protocols
    are
    important
    in
    special
    circumstances.
    Target
    organ
    concordance
    is
    not
    a
    prerequisite
    for
    evaluating
    the
    implications
    ofanimal
    study
    results
    for
    humans.
    Target
    organs
    of
    carcinogenesis
    for agents
    that
    cause
    cancer
    in
    both
    animals
    and
    humans
    are
    most
    often
    concordant
    at
    one
    or
    more
    sites
    (Tomatis
    et al.,
    1989;
    Huff,
    1994).
    However,
    concordance
    by
    site
    is not
    uniform.
    The
    mechanisms
    of control
    of cell
    growth
    and
    differentiation
    are concordant
    among
    species,
    but
    there
    are
    marked
    differences
    among
    species
    in
    the
    way
    control
    is
    managed
    in
    various
    tissues.
    For example,
    in
    humans,
    mutations
    of
    the
    tumor
    suppressor
    genes
    p53
    and retinoblastoma
    are
    frequently
    observed
    genetic
    changes
    in
    tumors. These
    tumor-suppressor
    genes
    are
    also observed
    to be
    operating
    in
    some
    rodent
    tissues,
    but other
    growth
    control
    mechanisms
    predominate
    in
    other
    rodent
    tissues.
    Thus,
    an
    animal
    response
    may
    be
    due
    to
    changes
    in
    a
    control
    that are
    relevant
    to humans
    but
    appear
    in
    animals
    in
    a different
    way.
    However,
    it
    is
    appropriate
    under
    these
    cancer
    guidelines
    to
    consider
    the
    influences
    of
    route
    of
    exposure,
    metabolism,
    and,
    particularly,
    some
    modes
    of
    action
    that
    may
    either
    support
    or
    not
    support
    target
    organ
    concordance
    between
    animals
    and
    humans.
    When
    data
    allow,
    these
    influences
    are
    considered
    in
    deciding
    whether
    agent-,
    species-,
    or
    organ-specific
    situations
    are
    appropriate
    to
    use in
    preference
    to this
    default
    assumption
    (NRC,
    1994).
    In
    contrast,
    use
    of
    toxicokinetic modeling inherently
    assumes
    site
    concordance,
    as these
    models
    are
    used
    to
    estimate
    delivered dose
    to a
    particular
    tissue
    or
    organ
    in
    humans
    on the
    basis
    of the
    same
    tissue
    or
    organ
    from
    animal
    data.
    The
    default
    is
    to
    include
    benign
    tumors
    observed
    in animal
    studies
    in the
    assessment
    of
    animal
    tumor
    incidence,
    fsuch
    tumors
    have
    the
    capacity
    to
    progress
    to
    the malignancies
    with
    which
    they
    are
    associated.
    This
    default
    is
    consistent
    with
    the
    approach
    of
    the National
    Toxicology
    Program
    and
    the International
    Agency
    for
    Research
    on
    Cancer
    and
    is more
    protective
    of public
    health
    than
    not including
    benign
    tumors
    in the
    assessment;
    benign
    and malignant
    tumors
    are
    treated
    as representative
    of
    related
    responses
    to
    the
    test
    agent
    (McConnell
    et
    al.,
    1986),
    which
    is
    scientifically
    appropriate.
    Nonetheless,
    in assessing
    findings
    from
    animal
    studies,
    a
    greater
    proportion
    of
    malignancy
    is weighed
    more
    heavily
    than
    is a response
    with
    a
    A-S

    greater
    proportion
    of benign
    tumors.
    Greater
    frequency
    of
    malignancy
    of
    a particular
    tumor
    type
    in
    comparison
    with
    other tumor
    responses
    observed
    in an animal
    study
    is
    also a factor
    to be
    considered
    in selecting
    the response
    to be used in
    dose-response
    assessment.
    Benign
    tumors
    that are not
    observed
    to
    progress
    to malignancy
    are
    assessed
    on a case-
    by-case
    basis.
    There
    is a range
    of possibilities
    for
    the overall
    significance
    of benign
    tumors.
    They
    may
    deserve
    attention
    because
    they
    are
    serious
    health
    problems
    even though
    they
    are not
    malignant;
    for instance,
    benign tumors
    may
    be
    a health
    risk because
    of
    their
    effect
    on the
    function
    of a target
    tissue,
    such
    as the
    brain.
    They may
    be significant
    indicators
    of the
    need
    for
    further
    testing
    of
    an
    agent if they
    are
    observed
    in a short-term
    test
    protocol,
    or such
    an
    observation
    may
    add to the
    overall
    weight of
    evidence
    if
    the same
    agent
    causes
    malignancies
    in
    a
    long-term
    study.
    Knowledge
    of the mode
    of
    action
    associated
    with
    a benign tumor
    response
    may
    aid in the interpretation
    of other tumor
    responses
    associated
    with
    the
    same
    agent.
    How
    Do Metabolic
    Pathways
    Relate
    Across Species
    andAinong
    Different
    Age
    Groups
    and
    Between
    Sexes
    in
    Humans?
    The default
    option
    is that
    there is
    a similarity
    ofthe
    basic pathways
    ofmetabolism
    and
    the occurrence
    of
    metabolites
    in
    tissues
    in
    regard
    to the species-to-species
    extrapolation
    of
    cancer
    hazard
    and
    risk.
    If comparative
    metabolism
    studies were
    to
    show
    no
    similarity
    between
    the
    tested species
    and
    humans
    and
    a metabolite(s)
    was the active
    form,
    there would
    be
    less
    support
    for
    an
    inference
    that the animal
    response(s)
    relates
    to humans.
    In other
    cases,
    parameters
    of
    metabolism
    may
    vary
    quantitatively
    between
    species;
    this
    becomes
    a factor
    in deciding
    on
    an
    appropriate
    human-equivalent
    dose
    based
    on
    animal
    studies,
    optimally
    in
    the context
    of a
    toxicokinetic
    model.
    Although
    the
    basic
    pathways
    are assumed
    to
    be the
    same
    among
    humans,
    the presence
    of
    polymorphisms
    in
    the general
    population
    and factors
    such
    as
    the
    maturation
    of
    the
    pathways
    in infants
    should
    be
    considered.
    The active
    form
    of an agent
    may be present
    to
    differing
    degrees,
    or it may
    be completely
    absent, which
    may
    result
    in
    greater or
    lesser
    risk
    for
    subpopulations.
    A-6

    How
    Do
    Toxicokinetic
    Processes Relate
    Across
    Species
    and Among
    Dfferent
    Age
    Groups
    and
    Between
    Sexes
    in Humans?
    A
    major
    issue
    is how
    to
    estimate
    human-equivalent
    doses
    in
    extrapolating
    from
    animal
    studies.
    As
    a
    default
    for
    oral
    exposure
    a
    human
    equivalent
    dose
    for
    adults
    is estimated
    from
    data
    on
    another
    species
    by
    an
    adjustment
    of
    animal
    applied
    oral
    dose
    by
    a scaling
    factor
    based
    on
    body
    weight
    to
    the 3/4
    power.
    The
    same
    factor
    is
    used
    for
    children
    because
    it
    is
    slightly
    more
    protective
    than using
    children’s
    body
    weight
    (see
    Section
    3.1.3).
    This
    adjustment
    factor
    is
    used
    because
    it
    represents
    scaling
    of metabolic
    rate
    across
    animals
    of different
    size.
    Because
    the
    factor
    adjusts
    for a parameter
    that
    can
    be
    improved
    on
    and
    brought
    into
    more
    sophisticated
    toxicokinetic modeling
    when
    such
    data
    become
    available,
    they
    are
    usually
    preferable
    to
    the
    default
    option.
    For
    inhalation exposure,
    a
    human
    equivalent
    dose
    for
    adults
    is estimated
    by
    default
    methodologies
    that
    provide
    estimates
    of
    lung
    deposition
    and
    internal
    dose
    (U.S.
    EPA,
    1994).
    The
    methodologies
    can
    be
    refined
    to
    more
    sophisticated
    forms
    with
    data
    on
    toxicokinetic
    and
    metabolic parameters
    of
    the
    specific
    agent.
    This
    default
    option,
    like
    the
    one for
    oral
    exposure,
    is
    selected
    in
    part because
    it
    lays
    a foundation
    for
    incorporating
    better
    data.
    The
    use
    of
    information
    to
    improve
    dose
    estimation from
    applied
    to
    internal
    to delivered
    dose
    is encouraged,
    including
    use
    of toxicokinetic modeling
    instead
    of
    any default,
    where
    data
    are
    available.
    There
    are
    important
    differences
    between
    infants,
    adults,
    and
    older
    adults
    in
    the
    processes
    of absorption, distribution,
    and
    elimination;
    for
    example,
    infants
    tend
    to
    absorb
    metals
    through
    the gut
    more
    rapidly
    and
    more
    efficiently
    than
    do older
    children
    or
    adults
    (Calabrese,
    1986).
    Renal
    elimination
    is
    also
    not
    as
    efficient
    in infants.
    Although
    these
    processes
    reach
    adult
    competency
    at
    about
    the
    time
    of
    weaning,
    they may
    have
    important
    implications,
    particularly
    when
    the
    dose-response
    relationship
    for
    an
    agent
    is considered
    to
    be
    nonlinear
    and
    there
    is
    an
    exposure scenario
    disproportionately
    affecting
    infants,
    because
    in
    these
    cases
    the magnitude
    of
    dose
    is
    more
    pertinent
    than
    the
    usual
    approach
    in
    linear
    extrapolation
    of
    averaging
    dose
    across
    a
    lifetime.
    Efficiency
    of
    intestinal
    absorption
    in
    older
    adults
    tends
    to
    be
    generally
    less
    overall
    for
    most
    chemicals.
    Another
    notable
    difference
    is
    that, post-weaning
    (about
    1
    year),
    children
    have
    a
    A-7

    higher
    metabolic
    rate
    than
    do
    adults
    (Renwick,
    1998),
    and
    they
    may toxify
    or detoxify
    agents
    at
    a
    correspondingly
    higher
    rate.
    For a route-to-route exposure
    extrapolation,
    the
    default
    option
    is
    that an
    agent that
    causes
    internal
    tumors
    by
    one route
    of
    exposure
    will
    be
    carcinogenic
    by another
    route
    fit
    is
    absorbed
    by
    the second
    route
    to give
    an
    internal
    dose. This
    is a
    qualitative
    option
    and
    is
    considered
    to
    be
    public-health
    protective.
    The
    rationale
    is that
    for internal
    tumors
    an internal
    dose
    is significant
    no matter
    what
    the
    route
    of
    exposure.
    Additionally,
    the
    metabolism
    of
    the
    agent
    will
    be
    qualitatively
    the same
    for
    an
    internal
    dose.
    The
    issue
    of
    quantitative
    extrapolation
    of the dose-
    response
    relationship
    from
    one
    route
    to another
    is
    addressed
    case
    by
    case.
    Quantitative
    extrapolation
    is complicated
    by
    considerations
    such
    as
    first-pass
    metabolism.
    What
    Is the
    Correlation
    of
    the Observed
    Dose-Response
    Relationship
    to the
    Relationship
    at
    Lower
    Doses?
    If
    sufficient
    data
    are
    available,
    a
    biologically
    based
    model for
    both
    the
    observed
    range
    and
    extrapolation
    below
    that range
    may
    be used.
    Although
    no
    standard
    biologically
    based
    models
    are
    in
    existence,
    an
    agent-specific
    model
    may
    be developed
    if
    extensive
    data exist
    in
    a particular
    case
    and
    the
    purpose
    of the
    assessment
    justifies
    the
    investment
    of the
    resources
    needed.
    The default
    procedure
    for the
    observed
    range
    ofdata
    when
    a biologically
    based
    model
    is
    not used
    is
    to
    use
    a
    curve-fitting
    model
    for
    incidence
    data.
    In
    the
    absence
    of data
    supporting
    a biologically
    based
    model
    for
    extrapolation
    outside
    of
    the
    observed
    range,
    the
    choice
    of
    approach
    is
    based
    on the
    view
    of mode
    of action
    of the agent
    arrived
    at in the
    hazard
    assessment.
    If more
    than
    one approach
    (e.g.,
    both a nonlinear
    and
    linear
    approach)
    are
    supported
    by
    the
    data,
    they should
    be
    used and
    presented
    to the
    decisionmaker.
    A
    linear
    extrapolation approach
    is
    used
    when
    the mode
    of
    action
    information
    is
    supportive
    of
    linearity
    or mode
    of
    action
    is not understood.
    The
    linear
    approach
    is
    used when
    a
    view
    of
    the mode
    of action
    indicates
    a linear
    response,
    for
    example,
    when a
    conclusion
    is made
    that
    an agent
    directly
    causes
    alterations
    in DNA,
    a
    kind of
    interaction
    that
    not
    only
    theoretically
    requires
    one
    reaction
    but
    also is
    likely
    to be additive
    to
    ongoing,
    spontaneous
    gene
    mutation.
    Other
    kinds
    of
    activity
    may
    have
    linear
    implications,
    for
    example,
    linear
    rate-limiting
    steps
    A-8

    would
    also
    support
    a
    linear
    procedure.
    The
    linear
    approach
    is
    to
    draw
    a
    straight
    line
    between
    a
    point
    of
    departure
    from
    observed
    data,
    generally
    as a
    default,
    an
    LED
    chosen
    to
    be
    representative
    of
    the
    lower
    end
    of
    the
    observed
    range,
    and
    the
    origin
    (zero
    incremental
    dose,
    zero
    incremental
    response).
    This
    approach
    is
    generally
    considered
    to
    be
    public-health
    protective.
    The
    linear
    default
    is
    thought
    to
    generally
    provide
    an
    upper-bound
    calculation
    of
    potential
    risk
    at
    low
    doses,
    for
    example,
    a
    1/100,000
    to
    1/1,000,000
    risk.
    This
    upper
    bound
    is
    thought
    to
    be
    public-health
    protective
    at
    low
    doses
    for
    the
    range
    of
    human
    variation,
    considering
    the
    typical
    Agency
    target
    range
    for
    risk
    management
    of
    1/1,000,000
    to
    1/10,000,
    although
    it
    may
    not
    completely
    be
    so
    (Bois
    et
    al.,
    1995)
    if
    pre-existing
    disease
    or
    genetic
    constitution
    place
    a
    percentage
    of
    the
    population
    at
    greater
    risk
    from
    exposure
    to
    carcinogens.
    The
    question
    of
    what
    may
    be
    the
    actual
    variation
    in
    human
    susceptibility
    is
    one
    that
    was
    discussed
    in
    general
    in
    the
    NRC
    (1994)
    report,
    as
    well
    as
    the
    NRC
    report
    on
    pesticides
    in
    children
    and
    infants
    (NRC,
    1
    993b).
    NRC
    has
    recommended
    research
    on
    the
    question,
    and
    EPA
    and
    other
    agencies
    are
    conducting
    such
    research.
    Given
    the
    current
    state
    of
    knowledge,
    EPA
    will
    assume
    that
    the
    linear
    default
    procedure
    adequately
    accounts
    for
    human
    variation
    unless
    there
    is
    case-specific
    information
    for
    a
    given
    agent
    or
    mode
    of
    action
    that
    indicates
    a
    particularly
    susceptible
    subpopulation
    or
    lifestage,
    in
    which
    case
    the
    special
    information
    will
    be
    used.
    When
    adequate
    data
    on
    mode
    of
    action
    provide
    sufficient
    evidence
    to
    support
    a
    nonlinear
    mode
    of
    action
    for
    the
    general
    population
    and/or
    any
    subpopulations
    of
    concern,
    a
    different
    approach
    a
    reference
    dose/reference
    concentration
    that
    assumes
    that
    nonlinearity
    is used.
    The
    POD
    is
    again
    generally
    an
    BMDL
    when
    incidence
    data
    are
    modeled.
    A
    sufficient
    basis
    to
    support
    this
    nonlinear
    procedure
    is
    likely
    to
    include
    data
    on
    responses
    that
    are
    key
    events
    integral
    to
    the
    carcinogenic
    process.
    This
    means
    that
    the
    POD
    may
    be
    based
    on
    these
    precursor
    response
    data,
    for
    example,
    hormone
    levels
    or
    mitogenic
    effects
    rather
    than
    tumor
    incidence
    data.
    When
    the
    mode
    of
    action
    iiformation
    indicates
    that
    the
    dose-response
    function
    may
    be
    adequately
    described
    by
    both
    a
    linear
    and
    a
    nonlinear
    approach,
    then
    the
    results
    of
    both
    the
    linear
    and
    the
    nonlinear
    analyses
    are
    presented.
    An
    assessment
    may
    use
    both
    linear
    and
    nonlinear
    approaches
    if
    different
    responses
    are
    thought
    to
    result
    from
    different
    modes
    of
    action
    or
    a
    response
    appears
    to
    be
    very
    different
    at
    high
    and
    low
    doses
    due
    to
    influence
    of
    separate
    A-9

    modes
    of
    action.
    The results
    may
    be
    needed
    for
    assessment
    of
    combined
    risk
    from
    agents
    that
    have
    common
    modes
    of
    action.
    Absent
    data
    to
    the
    contrary,
    the
    default
    assumption
    is
    that
    the
    cumulative
    dose
    received
    over
    a
    lifetime,
    expressed
    as
    a lifetime
    average
    daily
    dose
    or
    lifetime
    average
    daily
    exposure,
    is
    an appropriate measure
    of
    dose
    or exposure.
    This assumes
    that
    a
    high
    dose
    of
    such
    an
    agent
    received
    over
    a shorter
    period
    of time
    is equivalent
    to a low
    dose
    spread
    over
    a
    lifetime.
    This
    is
    thought
    to be
    a
    relatively
    public-health-protective
    option
    and
    has some
    empirical
    support
    (Monro,
    1992).
    A counter
    example,
    i.e.,
    effects
    of short-term,
    high
    exposure
    levels
    that
    result
    in
    subsequent
    cancer
    development,
    is treatment
    of
    cancer
    patients
    with
    certain
    chemotherapeutic
    agents.
    When
    sufficient
    information
    is available
    to
    support
    a different
    approach,
    it can
    be
    used.
    For
    example,
    short-term
    exposure
    estimates
    (several
    days
    to several
    months)
    may
    be
    more
    appropriate than
    the lifetime
    average
    daily
    dose.
    In these
    cases,
    both
    agent
    concentration
    and
    duration
    are
    likely
    to
    be
    important, because
    such
    effects
    may
    be reversible
    at
    cessation
    of
    very
    short-term exposures.
    A-
    10

    APPENDIX
    B: EPA’s
    GUIDANCE
    FOR
    DATA
    QUALITY
    ASSESSMENT
    U.S.
    EPA
    (U.S.
    Environmental
    Protection
    Agency).
    (2000d)
    Guidance
    for
    data
    quality
    assessment:
    practical
    methods
    for
    data
    analysis.
    Office
    of Environmental
    Information,
    Washington,
    DC.
    EPAI600/R-96/084.
    Available
    from:
    ht://www.epa.gov/gualitv/gs-docsk9-finaI.Ddf
    B-i

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