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

Stuart G. Baker

Medical Decision Making, 2019, vol. 39, issue 2, 130-136

Abstract: 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.

Keywords: biomarker; cancer; early detection; sample size; study design (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:39:y:2019:i:2:p:130-136

DOI: 10.1177/0272989X18819792

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