Unified model involving genomics, magnetic resonance imaging and prostate‐specific antigen density outperforms individual co‐variables at predicting biopsy upgrading in patients on active surveillance for low risk prostate cancer

BACKGROUND: Active surveillance (AS) is the reference standard treatment for the management of low risk prostate cancer (PCa). Accurate assessment of tumor aggressiveness guides recruitment to AS programs to avoid conservative treatment of intermediate and higher risk patients. Nevertheless, underestimating the disease risk may occur in some patients recruited, with biopsy upgrading and the concomitant potential for delayed treatment. AIM: To evaluate the accuracy of mpMRI and GPS for the prediction of biopsy upgrading during active surveillance (AS) management of prostate cancer (PCa). METHOD: A retrospective analysis was performed on 144 patients recruited to AS from October 2013 to December 2020. Median follow was 4.8 (IQR 3.6, 6.3) years. Upgrading was defined as upgrading to biopsy grade group ≥2 on follow up biopsies. Cox proportional hazard regression was used to investigate the effect of PSA density (PSAD), baseline Prostate Imaging‐Reporting and Data System (PI‐RADS) v2.1 score and GPS on upgrading. Time‐to‐event outcome, defined as upgrading, was estimated using the Kaplan–Meier method with log‐rank test. RESULTS: Overall rate of upgrading was 31.9% (n = 46). PSAD was higher in the patients who were upgraded (0.12 vs. 0.08 ng/ml(2), p = .005), while no significant difference was present for median GPS in the overall cohort (overall median GPS 21; 22 upgrading vs. 20 no upgrading, p = .2044). On univariable cox proportional hazard regression analysis, the factors associated with increased risk of biopsy upgrading were PSA (HR = 1.30, CI 1.16–1.47, p = <.0001), PSAD (HR = 1.08, CI 1.05–1.12, p = <.0001) and higher PI‐RADS score (HR = 3.51, CI 1.56–7.91, p = .0024). On multivariable cox proportional hazard regression analysis, only PSAD (HR = 1.10, CI 1.06–1.14, p = <.001) and high PI‐RADS score (HR = 4.11, CI 1.79–9.44, p = .0009) were associated with upgrading. A cox regression model combining these three clinical features (PSAD ≥0.15 ng/ml(2) at baseline, PI‐RADS Score and GPS) yielded a concordance index of 0.71 for the prediction of upgrading. CONCLUSION: In this study PSAD has higher accuracy over baseline PI‐RADS score and GPS score for the prediction of PCa upgrading during AS. However, combined use of PSAD, GPS and PI‐RADS Score yielded the highest predictive ability with a concordance index of 0.71.