We used a genomic test of prostate cancer risk to stratify men into three classes of prostate cancer risk. Then, we used cost-effectiveness analysis to determine when risk-stratified screening policies were preferable to universal policies. We also provided guidance to developers of future prostate cancer risk biomarkers on how to optimize the stratification of risk.