cancer risk cannot yet be derived from a quantitative analysis of these processes. Before estimates of cancer risk posed by radon in air and drinking water can be based on quantitative models of biologic and molecular processes, these models must incorporate such difficult issues as individual and subpopulation variations in susceptibility. However, because of the large number of variables involved in such models, and the lack of detailed understanding of each step in the process, the models are still far too difficult computationally to be used for radiation risk assessment. For the near future, risk estimates must be based on current quantitative epidemiologic relationships between numbers of cancers and exposure in selected high-exposure populations. Neither this committee nor the BEIR VI committee has made risk estimates based directly on the emerging biophysical and cellular models.
However, the study of molecular and cellular mechanisms of radiation-induced cancer brings to the risk assessment process important insights about the nature and magnitude of the uncertainties associated with the dose-response models discussed in this report. In particular, the introduction of biophysical cellular models to the risk assessment process reveals both the limited reliability and potential bias of the existing risk assessment models. Biophysical models relate the amount and persistence of biological damage to factors such as radiation tracks, total doses and dose rates, damaged sites in DNA, and DNA breaks and their rejoining. These models can be used to explore inverse dose-rate effects and some of the age-variation in effects. Cellular models focus on changes in cell cycles, proliferation kinetics, cell killing, cell regulation, and other processes that alter the path from radiation deposition to cancer incidence. Although still in the early phase of development, these models may eventually be used to explore variations in susceptibility associated with age, gender, and other genetic characteristics. Nevertheless, these emerging models and the mechanisms of action being studied by radiation biophysicists have provided this committee and others guidance for estimating the uncertainties associated with dose-response functions. Perhaps the most important insight is the recognition of the uncertainty regarding the relevance of the population used to develop a dose-response model. Radon risk derived from a particular population, such as survivors of the atomic bombings of Hiroshima and Nagasaki or miners, cannot necessarily be used directly to estimate risk for a different population such as the US population exposed to radon. This inability to transfer the risk estimates occurs because radiation-induced cancer risk is a function of the underlying spontaneous-cancer incidence (see for example National Research Council 1990a). Average risk estimates are obtained from epidemiology studies that can detect radiation-induced effects in large groups. The problem of extrapolating from one population to another is often dealt with by assigning an appropriate uncertainty interval to the risk estimates. To assign appropriate uncertainties, however, there is a need for more detailed data for which the distribution of risks among individuals can be determined.