Development of a Chinese nomogram based on muti-parametric magnetic resonance for predicting the probability of prostate cancer in patients after initial negative biopsy

Abstract

Objective: To develop a predictive nomogram based on multi-parametric magnetic resonance imaging (mpMRI) information to identify men more likely to have a cancer diagnosed on repeat prostate biopsy. Methods: The clinical data of 237 patients who received repeat prostate biopsy after initial negative biopsy from Department of Urology of Peking University First Hospital between January 2001 and August 2016 was reviewed. Patient age, body mass index (BMI), serum total prostate-specific antigen (PSA), percent free PSA (f/t), prostate volume (PV), PSA density (PSAD), PSA velocity (PSAV), digital rectal examination (DRE), transrectal ultrasound (TRUS)and mpMRI results were included in the univariate and multivariate analysis. A nomogram was developed using selected variables and the area under the receiver operating characteristic (ROC) curve was calculated as a measure of discrimination. Results: A total of 76 patients (32.07%) had prostate cancer (PCa) detected on repeat biopsy. Based on univariate and multivariate logistic regression analysis, the patient age, PSA, PV, DRE and mpMRI results were independent predictors for the diagnosis of PCa on repeat biopsy. The current nomogram performed well (AUC=0.910) and showed excellent calibration. Conclusions: Multi-parametric magnetic resonance imaging combined with age, PSA, PV and DRE can predict the probability of PCa in patients with initial negative biopsy. The nomogram might help in decision-making for men with prior benign histology before the performance of repeat biopsy.