Polygenic risk scores for premagnetic resonance imaging risk stratification in men with clinically suspected prostate cancer
Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Men with suspected prostate cancer undergo magnetic resonance imaging (MRI) before biopsy. However, approximately 30%-50% of MRIs are negative (Prostate Imaging-Reporting and Data System [PI-RADS] score 1-2), representing a challenge for MRI resource utilization. This study evaluates prostate cancer polygenic risk scores and clinical markers to optimize MRI utilization. METHODS: In this prospective study, 500 cancer-suspected men of Western European descent scheduled for MRI (September 2017-December 2022) were enrolled. Exclusions included prior prostate cancer diagnosis, missing serum prostate-specific antigen (PSA), or PSA levels of at least 25 ng/mL. Patient-specific prostate cancer polygenic risk scores were calculated using genotype data obtained from saliva-derived DNA samples. Participants were grouped as MRI negative and positive (PI-RADS score 3-5). Logistic regression was used to calculate odds ratios (ORs) and to build multivariable risk models, including age, PSA, and polygenic risk scores for MRI positivity. Clinical utility was tested in a holdout test set using decision curve analysis. RESULTS: A total of 386 men (median age = 65 years, interquartile range [IQR] = 53-77 years) were eligible for analysis, which showed statistically significant associations between prostate cancer polygenic risk scores (OR = 1.56, 95% confidence interval [CI] = 1.23 to 1.98; P < .001) with MRI positivity, while PSA alone did not (OR = 1.17, 95% CI = 0.93 to 1.46; P = .18). The highest net benefit was shown using a multivariable age and prostate cancer polygenic risk score model, increasing the proportion of MRI-positive men by 14% compared with PSA alone (60% and 46%, respectively; P = .011). CONCLUSIONS: Genotype-informed risk stratification using prostate cancer polygenic risk scores could increase the proportion of cancer-suspicious findings at MRI, while identifying those who could safely avoid unnecessary MRI.
DOI: 10.1093/jnci/djag027
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $5,436
Funder: Berlin Institute of Health
OpenAlex ID: W7127433738
