Polygenic risk scores for pre-MRI risk stratification in men with clinically suspected prostate cancer
Menée à partir d'échantillons salivaires prélevés sur 386 hommes avec suspicion de cancer de la prostate (âge médian : 65 ans), cette étude évalue l'association entre un système de score polygénique et le risque de détection d'un cancer de la prostate à l'IRM
Background : Men with suspected prostate cancer (PCa) undergo MRI before biopsy. However, about 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 PCa-polygenic risk scores (PRS) and clinical markers to optimize MRI utilization.
Methods : In this prospective study, 500 cancer-suspected men of Western European descent scheduled for MRI (09/2017-12/2022) were enrolled. Exclusions included prior PCa diagnosis, missing serum prostate-specific antigen (PSA) or PSA levels
≥
25 ng/mL/cc. Patient-specific PCa-PRS 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 (OR) and to build multivariable risk models, including age, PSA, and PRS for MRI-positivity. Clinical utility was tested in a hold-out test set using decision curve analysis.
Results : 386 men (median age: 65, interquartile range: 53-77) were eligible for analysis, which showed highly significant associations between PCa-PRS (OR 1.56 (95% CI: 1.23-1.98); p<.001) with MRI-positivity, while PSA alone did not (OR 1.17 (0.93-1.46); p=.18). The highest net benefit was shown using a multivariable age and PCa-PRS model, increasing the proportion of MRI-positive men by 14% compared to PSA alone (60%/46%; p=.011).
Conclusions : Genotype-informed risk stratification using PCa-PRS could increase the proportion of cancer-suspicious findings at MRI, while identifying those who could safely avoid unnecessary MRI.
Journal of the National Cancer Institute , article en libre accès, 2026