Cancer Screening Markers: A Simple Strategy to Substantially Reduce the Sample Size for Validation

Background. Studies to validate a cancer prediction model based on cancer screening markers collected in stored specimens from asymptomatic persons typically require large specimen collection sample sizes. A standard sample size calculation targets a true-positive rate (TPR) of 0.8 with a 2.5% lower bound of 0.7 at a false-positive rate (FPR) of 0.01 with a 5% upper bound of 0.03. If the probability of developing cancer during the study is P = 0.01, the specimen collection sample size based on the standard calculation is 7600. Methods. The strategy to reduce the specimen collection sample size is to decrease both the lower bound of TPR and the upper bound of FPR while keeping a positive lower bound on the anticipated clinical utility. Results. The new sample size calculation targets a TPR of 0.4 with a 2.5% lower bound of 0.10 and an FPR of 0.0 with a 5% upper bound of 0.005. With P = 0.01, the specimen collection sample size based on the new calculation is 1800 instead of 7600. Limitations. The new sample size calculation requires a minimum benefit/cost ratio (number of false positives traded for a true positive). With P = 0.01, the minimum cost-benefit ratio is 5, which is plausible in many studies. Conclusion. In validation studies for cancer screening markers, the strategy can substantially reduce the specimen collection sample size, substantially reducing costs and making some otherwise infeasible studies now feasible