AI Insight
This study investigated whether combining a Genetic Risk Score based on 269 known prostate cancer risk variants (GRS269) with PSA test results and age could improve prostate cancer prediction compared to either measure alone. Using data from 17,380 UK Biobank cases, researchers found that the integrated model consistently outperformed single-measure models across all PSA measurement types. The best predictive performance was achieved by combining the most recent PSA value with GRS269 and age, reaching an AUC of 0.82, compared to 0.70 for GRS269 alone and 0.73 for PSA alone.
Why it matters
Given that PSA testing alone carries a false-positive rate of up to 80%, integrating genetic risk scores into routine screening could meaningfully reduce unnecessary biopsies and improve early detection accuracy, with potential applications in primary care prostate cancer screening pathways.
⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Background: Prostate 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. Method: GRS269 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. Results: Across 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). Conclusion: Combining 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.