Although the study groups were rather small, our findings suggest that the association between CA and cancer is not modified by GSTM1 and GSTT1 polymorphisms, that the association is higher when the evaluation is based on uniform cytogenetic data rather than pooled historical data, and that the use of Bayesian modeling is a credible approach for risk estimation in case of sparse data, a common condition in biomarker validation studies. This evidence concerns the gene GSTM1 and cancer.