Development and validation of a visual nomogram for predicting clinically significant prostate cancer in negative...

Multi-parametric magnetic resonance imaging (mpMRI) is a valuable medical technology for detecting clinically significant prostate cancer (csPCa). The diagnostic accuracy of mpMRI for csPCa in negative mpMRI (PI-RADS 1-2) remains suboptimal, underscoring the need for improvements for csPCa. This study aimed to build a visual predictive nomogram for early detection of csPCa in negative mpMRI. We retrospectively reviewed 303 men from our institution who simultaneously underwent ⁶⁸Ga-PSMA-11 PET/CT and mpMRI before a biopsy between March 2020 and July 2022 and 130 men from the outside institution (Nanjing Drum Tower Hospital) as external validation between September 2021 and June 2022. The enrolled patients in our institution were randomly divided into the training set (n = 212) and the internal validation set (n = 91). Multivariate logistic regression was performed to identify independent predictors and establish a nomogram using SUVmax of ⁶⁸Ga-PSMA-11 PET/CT and prostatic specific antigen density (PSAD) to predict the occurrence of csPCa in negative mpMRI. Multivariate logistic regression demonstrated that SUVmax (odds ratio [OR] 5.296, 95% confidence interval [CI] 1.691-23.972), and PSAD (OR 4.867, 95%CI 2.389-10.901) were independent predictors for csPCa in negative mpMRI. The area under the curve (AUC) of the nomogram was 0.819 (95%CI 0.729-0.890). Additionally, both the decision curve analysis (DCA) curve and the net reclassification improvement (NRI) showed significant improvements for csPCa in our model. External validation validated the reliability of the prediction nomogram. The visual interactive web risk calculator PI-RADS/SUVmax/PSAD model (PSP Model, www.cspca.online ) based on the nomogram allows us to assess the risk of having csPCa. The nomogram based on preoperative examination was developed to predict csPCa in negative mpMRI and help reduce unnecessary biopsies. The visual PSP Model is an effective and accurate tool for urologists to use in the early prediction and timely management of csPCa.