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BACKGROUND: Men with prior negative prostate biopsies have a lower risk of being diagnosed with prostate cancer in comparison with biopsy-naive men. However, the relative clinical utility of identified lesions on multiparametric magnetic resonance imaging (mpMRI) is uncertain between the 2 settings. METHODS: Patients from the Prospective Loyola University mpMRI (PLUM) Prostate Biopsy Cohort (January 2015 to June 2020) were examined. The detection of any prostate cancer and clinically significant prostate cancer (Gleason score ≥ 3 + 4) was stratified by Prostate Imaging-Reporting and Data System (PI-RADS) scores in the prior negative and biopsy-naive settings. Multivariable logistic regression models (PLUM models) assessed predictors, and decision curve analyses were used to estimate the clinical utility of PI-RADS cutoffs relative to the models. RESULTS: Nine hundred men (420 prior negative patients and 480 biopsynaive patients) were included. Prior negative patients had lower risks of any prostate cancer (27.9% vs 54.4%) and clinically significant prostate cancer (20.0% vs 38.3%) in comparison with biopsy-naive patients, and this persisted when they were stratified by PI-RADS (eg, PI-RADS 3: 13.6% vs 27.4% [any prostate cancer] and 5.2% vs 15.4% [clinically significant prostate cancer]). The rate of detection of clinically significant prostate cancer was 5.3% among men with prior negative biopsy and PI-RADS ≤ 3. Family history and Asian ancestry were significant predictors among biopsy-naive patients. PLUM models demonstrated a greater net benefit and reduction in biopsies (45.8%) without missing clinically significant cancer in comparison with PI-RADS cutoffs (PI-RADS 4: 34.0%). CONCLUSIONS: Patients with prior negative biopsies had lower prostate cancer detection by PI-RADS score category in comparison with biopsy-naive men. Decision curve analyses suggested that many biopsies could be avoided by the use of the PLUM models or a PI-RADS 4 cutoff without any clinically significant cancer being missed.

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Objectives To develop and validate a prostate cancer (PCa) risk calculator (RC) incorporating multiparametric magnetic resonance imaging (mpMRI) and to compare its performance with that of the Prostate Biopsy Collaborative Group (PBCG) RC. Patients and Methods Men without a PCa diagnosis receiving mpMRI before biopsy in the Prospective Loyola University mpMRI (PLUM) Prostate Biopsy Cohort (2015–2020) were included. Data from a separate institution were used for external validation. The primary outcome was diagnosis of no cancer, grade group (GG)1 PCa, and clinically significant (cs)PCa (≥GG2). Binary logistic regression was used to explore standard clinical and mpMRI variables (prostate volume, Prostate Imaging‐Reporting Data System [PI‐RADS] version 2.0 lesions) with the final PLUM RC, based on a multinomial logistic regression model. Receiver‐operating characteristic curve, calibration curves, and decision‐curve analysis were evaluated in the training and validation cohorts. Results A total of 1010 patients were included for development (N = 674 training [47.8% PCa, 30.9% csPCa], N = 336 internal validation) and 371 for external validation. The PLUM RC outperformed the PBCG RC in the training (area under the curve [AUC] 85.9% vs 66.0%; P < 0.001), internal validation (AUC 88.2% vs 67.8%; P < 0.001) and external validation (AUC 83.9% vs 69.4%; P < 0.001) cohorts for csPCa detection. The PBCG RC was prone to overprediction while the PLUM RC was well calibrated. At a threshold probability of 15%, the PLUM RC vs the PBCG RC could avoid 13.8 vs 2.7 biopsies per 100 patients without missing any csPCa. At a cost level of missing 7.5% of csPCa, the PLUM RC could have avoided 41.0% (566/1381) of biopsies compared to 19.1% (264/1381) for the PBCG RC. The PLUM RC compared favourably with the Stanford Prostate Cancer Calculator (SPCC; AUC 84.1% vs 81.1%; P = 0.002) and the MRI‐European Randomized Study of Screening for Prostate Cancer (ERSPC) RC (AUC 84.5% vs 82.6%; P = 0.05). Conclusions The mpMRI‐based PLUM RC significantly outperformed the PBCG RC and compared favourably with other mpMRI‐based RCs. A large proportion of biopsies could be avoided using the PLUM RC in shared decision making while maintaining optimal detection of csPCa.

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