The focus of this project is development and refinement of statistical procedures for the design and analysis of cancer screening and related studies. Problems under investigation include derivation and comparison of data analysis methods, assessment of case-control studies for screening evaluation, development of models of cancer screening, approaches to the evaluation of diagnostic tests, and estimation and adjustment of lead time in cancer survival data. To assess the case-control design for screening evaluation, the MISCAN microsimulation model is being used to provide population data with and without screening. Case-control studies are then done in the screened populations, and the results are compared with the true effect to assess bias in the case-control approach. Criteria were developed for comparability of the restricted case subgroups used in the Limited Analysis of a cancer screening trial. A method for estimating the effect of starting periodic screening at different ages was developed that uses data from a screened population to estimate the probability of diagnosis in an unscreened group. A new method was derived for estimating the true and false positive rates of multiple diagnostic tests accounting for unrecorded variables that may be related to the decision to verify disease. Methods have been developed for estimating the benefit of screening unaffected by lead time bias and the average lead time by examining the differences in case survival measured both from time of entry and time of diagnosis between screened and control groups. Variance estimators for these estimators were derived. Approaches for estimating the post lead time survival of screen detected cancer cases were developed. Approaches were defined for data monitoring of cancer screening trials, including sequential methods for nonproportional hazards techniques and a Bayesian method.
