Improved prostate cancer prediction by combining Prostate-Specific Antigen (PSA) test results with Genetic Risk Scores (GRS/PRS)

Abstract

BackgroundProstate cancer is the second most common cancer in men worldwide. The Prostate Specific Antigen (PSA) blood test is widely used for prostate cancer detection but suffers from high false-positive rates (up to 80%). Genetic risk scores (GRS/PRS) have a similar performance to PSA testing in predicting prostate cancer risk. MethodGRS269 for prostate cancer was derived using 269 known risk variants and applied to UK Biobank participants. We assessed whether GRS269 improved power to predict prostate cancer diagnosis on top of age and pre-prostatectomy PSA level among 17,380 cases. Longitudinal PSA measurements were processed as median, first, last (most recent), and random PSA. All models were adjusted for age. ResultsAcross all PSA measures, the integrated model combining GRS269, PSA, and age consistently outperformed models using GRS269 or PSA alone. The highest predictive performance was observed using the last PSA value combined with GRS269 (AUC = 0.82, 95% CI: 0.81 - 0.82), compared to GRS269 alone (AUC = 0.70, 95% CI: 0.68 - 0.72) or PSA alone (AUC = 0.73, 95% CI: 0.70 - 0.75). ConclusionCombining genetic risk with PSA and age improves prostate cancer risk prediction in a population setting. These findings highlight the potential clinical implications of integrating GRS will enhance early prostate cancer prediction pathways in primary care.