ABSTRACT
【Objective】 To establish a nomogram model for predicting the risk of positive prostate biopsy in MRI-negative patients, and to perform the internal validation. 【Methods】 We retrospectively analyzed the clinical data of 197 MRI-negative patients who underwent prostate biopsy at our hospital, analyzed the independent predictors of positive prostate biopsy with univariate and multivariate logistic regression analysis, constructed the nomogram model and conducted internal validation. 【Results】 Multivariate logistic regression analysis showed age (P=0.003), digital rectal examination (DRE)(P=0.005), total prostate-specific antigen (tPSA) (P=0.001) and prostate volume (PV)(P<0.001) were independent risk factors of MRI-negative but prostate biopsy-positive results. The nomogram model based on all variables was established. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.862, which was greater than that of tPSA (AUC=0.739), PV(AUC=0.711) and DRE(AUC=0.666) (all P<0.05). The average absolute error of the model was 1.1% after 500 internal resampling, indicating that the prediction of positive prostate biopsy was consistent with the actual situation. 【Conclusion】 The age, DRE, tPSA and PV were independent predictors of positive prostate biopsy in MRI-negative patients. The nomogram model has a good prediction performance.