Fitting cancer mortality data with cumulative damage models

Fitting epidemiologic follow-up studies with cumulative damage models

The use of an extended version of the cumulative damage model to identify and quantify cancer risk arising from a specified exposure is outlined. For this, a strategy to fit the model to individual data coming from epidemiologic follow-up studies is described. Two statistical problems are addressed: first, the regularity of the model has to be ascertained to allow the application of maximum-likelihood and likelihood-ratio methods for parameter estimation and testing. Second, a statistical test has to be found that permits testing goodness of fit in the setting of parameter estimation with individual data. As an example, these methods are applied to the data of a cohort study on mortality among stainless steel welders in the Federal Republic of Germany. The results show that the model fits the data well and confirms a carcinogenic effect of stainless steel welding among welders. Some distinguishing characteristics of the model, especially its prediction of a potentially decreasing relative risk despite ongoing carcinogenic exposure, are discussed.

A stochastic model of hormesis

In order to describe the life-prolonging effect of some agents that are harmful at higher doses, ionizing radiations in particular, a stochastic model is developed in terms of accumulation and progression of intracellular lesions caused by the environment and by the agent itself. The processes of lesion repair, operating at the molecular and cellular level, are assumed to be responsible for this hormesis effect within the framework of the proposed model. Properties of lifetime distributions, derived for analysis of animal experiments with prolonged and acute irradiation, are given special attention. The model provides efficient means of interpreting experimental findings, as evidenced by its application to analysis of some published data on the hormetic effects of prolonged irradiation and of procaine on animal longevity.