The development of the methods of cancer control epidemiology has been focused in three areas: 1) studies in causal and preventive inference, 2) studies in interactions, and 3) studies in selection bias. One inferential issue being examined is the use of inductive and deductive logic in epidemiologic explanation. When four distinct properties of causal and preventive explanations are considered (their origin, consistency, testability, and permanence), deductive logic proves superior except for their origin which is not a logical process. The implications for cancer control epidemiology are important: competing hypotheses should be proposed before any study begins; and the choice of the best hypothesis is equivalent to that which has been most rigorously tested. Another inferential issue is that of the relationship of the current causal criteria to explanatory progress and to public health decisions. For purposes of explanation, two categories of criteria emerge: those dependent upon the form of the hypothesis being tested and those independent of it. Studies of causal, preventive and mixed interactions have revealed that the links between biological and statistical models are necessary for scientific progress. Furthermore, the use of the multiplicative model of preventive interaction (and the use of the additive model of causal interaction) as thresholds for public health action is not justified, primarily due to ethical considerations. Research underway includes: 1) the development of a general method to evaluate methodologic research in cancer control epidemiology, 2) a critical examination of the importance of the magnitude of an association in assessing causality, 3) further testing of a theory for the healthy worker effect, and 4) the development of the conceptual foundations of cancer control epidemiology.
