cation of models that incorporate the ERR projection over time.

  • The choice of models for the transport of cancer risk from Japanese A-bomb survivors to the U.S. population is influenced by mechanistic knowledge and information on the etiology of different cancer types. Where specific epidemiologic evidence is lacking, the committee recommends that the weights attaching to relative and absolute risk transport should be 0.7 and 0.3, respectively.

  • A combined Bayesian analysis of A-bomb epidemiologic information and experimental data has been employed to provide an estimate of the DDREF for cancer risk. The committee found a believable range of DDREF values to be 1.1 to 2.3 and uses a median value of 1.5 to estimate solid cancer risks.

  • Knowledge of adaptive responses that may act to reduce radiation cancer risk was judged to be insufficient to be incorporated in a meaningful way into the modeling of epidemiologic data. The same judgment is made in respect of the possible contribution to cancer risk of postirradiation genomic instability and bystander signaling effects.

  • Genetic variation in the population is a potentially important factor in the estimation of radiation cancer risk. Strongly expressing cancer-predisposing mutations are judged from modeling studies to be too rare to distort population-based estimates of risk appreciably but are a significant issue in some medical irradiation settings. The position regarding potentially more common variant genes that express only weakly remains uncertain.

  • The estimation of the heritable effects of radiation by the committee takes advantage of new information on human genetic disease and on mechanisms of radiation-induced germline mutations. The application of a new approach to genetic risk estimation leads the committee to conclude that low-dose induced genetic risks are very small compared to baseline risks in the population.

  • The committee judges that the balance of evidence from epidemiologic, animal, and mechanistic studies tends to favor a simple proportionate relationship at low doses between radiation dose and cancer risk. Uncertainties in this judgment are recognized and noted.

ANNEX 10A: APPLICATION OF THE MOOLGAVKAR AND KNUDSON TWO-STAGE CLONAL EXPANSION MODEL TO THE TRANSPORT OF RADIATION CANCER RISK

In the case of tumors whose background incidence is strongly influenced by initiating factors, one would expect the EAR to be directly transportable from one population to another. If one considers, for example, the Moolgavkar and Knudson two-stage clonal expansion model (Moolgavkar and Knudson 1981; Moolgavkar and Luebeck 1990) shown in Figure 10A-1, the hazard function h(t) at time t is given approximately by the following formula:

where μ(t) and ν(t) denote, respectively, the first and second mutation rates at time t; α(t) is the rate of division of intermediate (or initiated) cells; and β(t) is the rate of death or differentiation of intermediate cells at time t.

If ionizing radiation and the other main risk factors for the tumor of interest are predominantly cancer initiators, their effect would be modeled additively on the first mutation rate μ, as follows:

The resulting relative risk would then be of the form:

while the absolute risk (AR) would be of the form:

According to this formulation, the effect of radiation would tend to be independent of the other risk factors on the AR scale. The AR per sievert could therefore be transported from one population to another.

FIGURE 10A-1 The two-stage clonal expansion model. SOURCE: Luebeck and others (1999).



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