Development and validation of a nomogram for predicting prostate cancer in patients with PSA ≤ 20 ng/mL at initial biopsy

The aim of this study was to construct a nomogram for predicting prostate cancer (PCa) in patients with PSA <= 20 ng/mL at initial biopsy. The patients with PSA <= 20 ng/mL who underwent prostate biopsy were retrospectively included in this study. The nomogram was developed based on predictors for PCa, which were assessed by multivariable logistic regression analysis. The receiver operating characteristic curve, calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the nomogram. This retrospective study included 691 patients, who were divided into training set (505 patients) and validation set (186 patients). The nomogram was developed based on the multivariable logistic regression model, including age, total PSA, free PSA, and prostate volume. It had a high area under the curve of 0.857, and was well verified in validation set. Calibration plots and DCA further validated its discrimination and potential clinical benefits. Applying the cut-off value of 15%, our nomogram would avoid 42.5% of unnecessary biopsies while miss only 4.4% of PCa patients. The nomogram provided high predictive accuracy for PCa in patients with PSA <= 20 ng/mL at initial biopsy, which could be used to avoid the unnecessary biopsies in clinical practice.

Automated summary

This study aimed to construct a nomogram for predicting prostate cancer in patients with PSA <= 20 ng/mL at initial biopsy, which was developed based on predictors assessed by multivariable logistic regression analysis and validated through receiver operating characteristic curve, calibration plots, and decision curve analysis. The nomogram showed high predictive accuracy and could avoid unnecessary biopsies for 42.5% of patients while missing only 4.4% of PCa cases.