External validation of novel MRI-based models for prostate cancer prediction.

Objectives To validate, in an external cohort, three novel risk models, including the recently updated European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator, that combine multiparametric magnetic resonance imaging (mpMRI) and clinical variables to predict clinically significant prostate cancer (PCa). Patients and Methods We retrospectively analysed 307 men who underwent mpMRI prior to transperineal ultrasound fusion biopsy between October 2015 and July 2018 at two German centres. mpMRI was rated by Prostate Imaging Reporting and Data System (PI-RADS) v2.0 and clinically significant PCa was defined as International Society of Urological Pathology Gleason grade group >= 2. The prediction performance of the three models (MRI-ERSPC-3/4, and two risk models published by Radtke et al. and Distler et al., ModRad and ModDis) were compared using receiver-operating characteristic (ROC) curve analyses, with area under the ROC curve (AUC), calibration curve analyses and decision curves used to assess net benefit. Results The AUCs of the three novel models (MRI-ERSPC-3/4, ModRad and ModDis) were 0.82, 0.85 and 0.83, respectively. Calibration curve analyses showed the best intercept for MRI-ERSPC-3 and -4 of 0.35 and 0.76. Net benefit analyses indicated clear benefit of the MRI-ERSPC-3/4 risk models compared with the other two validated models. The MRI-ERSPC-3/4 risk models demonstrated a discrimination benefit for a risk threshold of up to 15% for clinically significant PCa as compared to the other risk models. Conclusion In our external validation of three novel prostate cancer risk models, which incorporate mpMRI findings, a head-to-head comparison indicated that the MRI-ERSPC-3/4 risk model in particular could help to reduce unnecessary biopsies.