[Developing a Chinese PI-RADS v2-based nomogram for predicting clinically significant prostate cancer in patients...

Objective: To develop a nomogram based on prostate imaging reporting and data system version 2 (PI-RADS v2) to predict clinically significant prostate cancer in patients with a prior negative prostate biopsy. Methods: The clinical and pathological data of 231 patients who underwent repeat prostate biopsy and multiparametric MRI (mpMRI) were reviewed. Based on PI-RADS v2, the mpMRI results were assigned as PI-RADS grade from 0 to 2. A Logistic regression nomogram for predicting the probabilities of clinically significant prostate cancer were constructed. The performances of the nomogram were assessed using area under the receiver operating characteristic (ROC) curve, calibrations and decision curve analysis. Results: Of the total 231 repeat prostate biopsy patients, clinically significant prostate cancer was detected in 59 cases(25.5%). In multivariate Logistic regression analysis, age, prostate specific antigen (PSA), prostate volume (PV), digital rectal examination (DRE) and mpMRI results were significant independent predictors of the diagnosis of clinically significant prostate cancer (P<0.05). The nomogram with super predictive accuracy were constructed (AUC=0.927, P<0.001), and exhibited excellent calibration. Decision curve analysis also demonstrated a high net benefit across a wide range of threshold probabilities . Conclusions: PI-RADS v2 combined with age, PSA, PV and DRE can predict the probability of clinically significant prostate cancer in patients with negative initial biopsies. The nomogram generated may help the decision-making process in patients with prior benign histology before the performance of repeat biopsy.