https://www.selleckchem.com/products/gdc-0068.html The Rotterdam Prostate Cancer Risk calculator (RPCRC) has been validated in the past years. Recently a new version including multiparametric magnetic resonance imaging (mpMRI) data has been released. The aim of our study was to analyze the performance of the mpMRI RPCRC app. A series of men undergoing prostate biopsies were enrolled in eleven Italian centers. Indications for prostate biopsy included abnormal Prostate specific antigen levels (PSA>4ng/ml), abnormal DRE and abnormal mpMRI. Patients' characteristics were recorded. Prostate cancer (PCa) risk and high-grade PCa risk were assessed using the RPCRC app. The performance of the mpMRI RPCRC in the prediction of cancer and high-grade PCa was evaluated using receiver operator characteristics, calibration plots and decision curve analysis. Overall, 580 patients were enrolled 404/580 (70%) presented PCa and out of them 224/404 (55%) presented high-grade PCa. In the prediction of cancer, the RC presented good discrimination (AUC=0.74), poor calibration (p=0.01) and a clinical net benefit in the range of probabilities between 50 and 90% for the prediction of PCa (Fig.1). In the prediction of high-grade PCa, the RC presented good discrimination (AUC=0.79), good calibration (p=0.48) and a clinical net benefit in the range of probabilities between 20 and 80% (Fig.1). The Rotterdam prostate cancer risk App accurately predicts the risk of PCa and particularly high-grade cancer. The clinical net benefit is wide for high-grade cancer and therefore its implementation in clinical practice should be encouraged. Further studies should assess its definitive role in clinical practice. The Rotterdam prostate cancer risk App accurately predicts the risk of PCa and particularly high-grade cancer. The clinical net benefit is wide for high-grade cancer and therefore its implementation in clinical practice should be encouraged. Further studies should assess its definitive role in clini