Prostate cancer risk-stratification using proteomic estimation of KLK3 improves accuracy in screening applications: a population-based cohort study in the UK Biobank

BackgroundThe prostate specific antigen (PSA) test is the most used clinical tool for prostate cancer risk stratification. PSA-based screening remains controversial due to modest predictive power (ROC AUC<0.75), high false-positive rates and racial disparities. Here, we evaluated the prostate cancer risk-stratification potential for the KLK3 protein, measured by Olink(R) Explore-3072, in the UK Biobank. Methods19,364 men in the UK Biobanks proteomics dataset were cancer-free at assessment centre visit. We used logistic regression to evaluate potential of KLK3 to predict prostate cancer within 2, 5, and 10 years of recording, as an independent predictor and with age and genetic risk score. Prostate cancer cases were classified by severity based on clinical action taken post-diagnosis. All predictive models were performed under 5-fold cross validation, and diagnostic accuracy statistics reported for the test set. FindingsKLK3 was strongly associated with prostate cancer incidence (HR per SD: 3.00 (2.87 - 3.13), p<2e-16). ROC AUC for a 2-year prediction horizon was 0.918 (0.906 - 0.93), reducing to 0.854 (0.848 - 0.86) over 10 years. 10-year ROC AUC was stronger in individuals of European ancestry (0.857 (0.851 - 0.863)) than African (0.801 (0.762 - 0.841)) or South Asian (0.795 (0.727 - 0.862)) ancestry. Power to predict highly aggressive cancer cases within 2 years of recording was strong (ROC AUC 0.928 (0.919 - 0.937)) but weaker for a 10-year period (0.87 (0.865 - 0.876)). Inclusion of age and genetic risk score provided small improvements in individuals of primarily genetic European ancestry, but no improvement in African or South Asian ancestry. InterpretationThe ROCAUC values reported are superior to those seen previously for the PSA test. We demonstrate high predictive accuracy across 2-, 5- and 10-year windows. Findings were consistent for low and high-risk cases. These findings suggest that proteomic PSA measurements may be helpful in prostate cancer risk stratification, while highlighting the need for improved predictive models across diverse ancestral groups. FundingThis study was funded by the University of Exeter. We report no conflicts of interest. Research In ContextO_ST_ABSEvidence before this studyC_ST_ABSOn 4th August 2025 we searched the PubMed database using the search terms [(PSA OR KLK3 OR Prostate Cancer) AND (Risk Prediction OR Screening) OR (UK Biobank AND Proteomics)] to establish predictive power of the PSA test alongside prior work on the UK Biobank Proteomics data and identified a number of relevant studies. Large meta-analyses concerning the PSA test documents moderate predictive accuracy (ROC AUC~0.72), a high false positive rate, and no evidence that PSA screening reduces overall mortality. Studies using the UK Biobank Proteomics dataset have taken a phenome-wide or pan-cancer approach, scanning thousands of potential disease-protein pairs. Added value of this studyWe assessed the predictive value of KLK3 (molecularly equivalent to PSA) measured by Olink(R) high-throughput proteomics in 19,392 cancer-free men from the UK Biobank. We evaluated performance over 2-, 5-, and 10-year prediction horizons and stratified results by ancestry and cancer severity. KLK3 was a strong independent predictor of prostate cancer, particularly in a short window following measurement, and outperformed PSA estimates reported in previous literature. Combining KLK3 with age and a polygenic risk score provided modest benefit in men of European ancestry, but no additional benefit in men of African ancestry. This is the first large-scale study to assess proteomic measurement of KLK3 to stratify prostate cancer risk in a general population cohort. Implications of all the available evidenceProteomic measurement of KLK3 offers improved risk prediction for prostate cancer compared to standard PSA testing over a 2-, 5-, and 10-year period. Our findings suggest that KLK3 could enhance risk stratification in population screening and may be particularly useful for identifying individuals at very high risk. Similar to current technologies, proteomic measurement of KLK3 performs worse in African and South Asian populations than in European populations. While this disparity highlights an urgent need to improve and validate predictive models in non-European populations, our reported predictive power in non-European populations that is stronger than the current PSA test for European populations. These results suggest that proteomic measurement of KLK3 in screening applications will result in improved accuracy across populations and for severe prostate cancer outcomes over previous technology.