Cancer risk-assessment models: anticipated contributions from biochemical epidemiology

Uncertainties in quantitative assessment of cancer risk limit the scientific role of this activity in the policy and regulatory debate on cancer control. Risk-assessment strategies and models are highly dependent on the nature and quality of the data available. However, accumulating laboratory and epidemiologic studies that are shedding new light on mechanisms of carcinogenesis have not yet been integrated into current risk-assessment models. Future developments in risk assessment may, therefore, be anticipated by considering the type of epidemiologic data that may soon be generated. Three important areas of epidemiologic and biochemical research should reduce some of the uncertainty in quantitative risk assessment by making it possible to: identify stages of the disease process through precursor lesions, biochemical markers, and to determine at which stage the carcinogen acts; identify subpopulations that are at enhanced or reduced susceptibility to carcinogenic influences; and obtain additional and refined indices of dose. Much of this research is being called "biochemical epidemiology." Strategies for incorporating these newly generated data into regulatory decisions vary from developing new mechanistically based mathematical models to applying existing models to biologically distinct subpopulations.