To compare a locally developed risk model based on clinical parameters with previously published models and strategies to reduce MRI-targeted biopsies of indeterminate PI-RADS 3 lesions without missing clinically significant prostate cancer (csPCa) (ISUP ≥ grade 2).
Retrospective, two-center study including 278 patients without prior PCa who underwent multiparametric MRI and MRI-targeted biopsy. For robust parameter estimation, a risk model based on clinical parameters was developed in a high-prevalence cohort (institution 1; n = 202; PI-RADS 3-5) and recalibrated to PI-RADS 3 subgroup (n = 115). The validation cohort (institution 2, same metropolitan area) consisted of 76 men with PI-RADS 3 index lesions. Model performance was compared to previously suggested strategies and risk models using decision curve analysis.
The local risk model provided the highest net benefit across all clinically relevant risk thresholds in the validation cohort. At a 10% risk threshold, the model could safely avoid biopsies in 547 per 1,000 men with PI-RADS 3 index lesions without missing csPCa, outperforming other strategies in number of biopsies avoided: normalized ADC (223), PSA density (210), MRI-ERSPC risk calculator (164), lesion volume (55) and the Radtke risk model (0). At low risk thresholds < 10% both normalized ADC (0.81) and PSA density (0.08 ng/ml/ml) were clinically useful.
A locally fit risk model based on clinical parameters could safely reduce unnecessary biopsies in men with PI-RADS 3 index lesions, with normalized ADC and PSA density providing useful and easy-to-use alternatives.
World journal of urology. 2025 Apr 28*** epublish ***
Dominik Deniffel, Nathan Perlis, Sangeet Ghai, Emmanuel Salinas-Miranda, Khashayar Namdar, Laurence H Klotz, Alexandre Zlotta, Antonio Finelli, Masoom A Haider
Joint Department of Medical Imaging, Princess Margaret Hospital, Sinai Health System, University of Toronto, Toronto, ON, Canada., Division of Urology, Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada., Department of Surgery, Division of Urology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada., Joint Department of Medical Imaging, Princess Margaret Hospital, Sinai Health System, University of Toronto, Toronto, ON, Canada. .
PubMed http://www.ncbi.nlm.nih.gov/pubmed/40293532