We retrospectively analyzed 193 patients with pathologically confirmed prostate disease who underwent MRI examinations at Beijing Electric Power Hospital, Capital Medical University, from January 2014 to December 2023. Images was acquired using a 3.0T MRI scanner, and both multiparametric MRI (mpMRI) and bpMRI results were interpreted based on PI-RADS version 2.1. CsPCa was defined as any core with Gleason grade group ≥ 2 from transperineal biopsies based on the International Society of Urological Pathology Consensus [11, 12].

In total, the following clinical parameters were collected for each patient, tested at the time of the primary diagnosis: age, transperineal biopsy results (CsPCa or non-CsPCa), PSA, free/total PSA (f/tPSA), PSA density (PSAD), bpMRI scores and mpMRI scores.

Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors of CsPCa. A nomogram model for the prediction of CsPCa was established by the independent risk factors. Internal validation was performed using bootstrap resampling as recommended [13]. Diagnostic performance was estimated by analyzing the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) value was reported with corresponding 95% confidence interval. The calibration performances of the model were assessed using Hosmer-Lemeshow goodness-of-fit test and calibration curve analysis. Statistical analysis was performed in R (version 4.3.2; https://www.r-project.org/) environments. A two-sided P < 0.05 was considered statistically significant.