European urology focus · 2026
External Validation and Comparison of Magnetic Resonance Imaging-based Risk Calculators for Detection of Clinically Significant Prostate Cancer: A Multi-institutional Study Incorporating Transrectal and Transperineal Biopsy Approaches.
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Zlotta Alexandre R, Taborek Afton, Kwong Jethro C C, Wang Alice, Boulakia Noa, Yin Leyi B, Zhang Kevin K, Nguyen David-Dan, Srigley John R, der Kwast Theodorus Van, Prendeville Susan, Booth Ryan, Shahid Aiman, Ringa Maximiliano, Ali Amna, Diamond Ivan, Bruni Sylvio, Klotz Laurence H, Perlis Nathan, Fleshner Neil, Finelli Antonio, Diamand Romain, Ghai Sangeet, Haider Masoom, Buckley Roger, Feifer Andrew, Mian Badar M, Kulkarni Girish S
Аннотация
BACKGROUND AND OBJECTIVE: Magnetic resonance imaging (MRI)-based risk calculators are widely used to inform prostate biopsy decision-making; however, they were predominantly developed for transrectal biopsies. Their performance using the transperineal approach remains unclear. This study externally validated five MRI-based risk calculators across a diverse cohort undergoing either approach.
METHODS: This retrospective cohort study included 4168 men with pre-biopsy MRI followed by prostate biopsy between October 2016 and December 2023 across four Canadian academic and community hospitals. Five MRI-based (Mehralivand, Kinnaird, Patel, Wang, and Peters) and one non-MRI-based (Prostate Biopsy Collaborative Group) risk calculators were compared. The primary outcome was the presence of clinically significant prostate cancer (csPCa; Grade Group ≥ 2). Model performance was characterized using area under the receiver-operating-characteristic curve (AUROC), calibration plots, and net benefit.
KEY FINDINGS AND LIMITATIONS: Overall, 1797 of 4168 men (43%) had csPCa. Seventy-four percent were of Caucasian ancestry. Biopsies were transperineal in 1379 cases (33%); 32% of patients were biopsy-naïve, 30% had a prior negative biopsy, and 38% had prior Grade Group 1 disease. The MRI-based calculators' performance was similar but worse than originally reported (AUROC = 0.78-0.80 vs 0.80-0.89) although better than that of the non-MRI-based model (AUROC = 0.67, p < 0.001). MRI-based models' performance remained consistent across subgroups, including age, ancestry, biopsy approach (transrectal or transperineal), clinical setting (academic or community), Prostate Imaging-Reporting and Data System (PI-RADS; v2.0 or v2.1), and MRI-fusion technique (cognitive or software). The Kinnaird, Patel, and Peters models showed superior calibration and net benefit.
CONCLUSIONS AND CLINICAL IMPLICATIONS: We did not see evidence of a difference in the performance of MRI-based risk calculators regardless of biopsy approach or fusion technique.
METHODS: This retrospective cohort study included 4168 men with pre-biopsy MRI followed by prostate biopsy between October 2016 and December 2023 across four Canadian academic and community hospitals. Five MRI-based (Mehralivand, Kinnaird, Patel, Wang, and Peters) and one non-MRI-based (Prostate Biopsy Collaborative Group) risk calculators were compared. The primary outcome was the presence of clinically significant prostate cancer (csPCa; Grade Group ≥ 2). Model performance was characterized using area under the receiver-operating-characteristic curve (AUROC), calibration plots, and net benefit.
KEY FINDINGS AND LIMITATIONS: Overall, 1797 of 4168 men (43%) had csPCa. Seventy-four percent were of Caucasian ancestry. Biopsies were transperineal in 1379 cases (33%); 32% of patients were biopsy-naïve, 30% had a prior negative biopsy, and 38% had prior Grade Group 1 disease. The MRI-based calculators' performance was similar but worse than originally reported (AUROC = 0.78-0.80 vs 0.80-0.89) although better than that of the non-MRI-based model (AUROC = 0.67, p < 0.001). MRI-based models' performance remained consistent across subgroups, including age, ancestry, biopsy approach (transrectal or transperineal), clinical setting (academic or community), Prostate Imaging-Reporting and Data System (PI-RADS; v2.0 or v2.1), and MRI-fusion technique (cognitive or software). The Kinnaird, Patel, and Peters models showed superior calibration and net benefit.
CONCLUSIONS AND CLINICAL IMPLICATIONS: We did not see evidence of a difference in the performance of MRI-based risk calculators regardless of biopsy approach or fusion technique.