The role of metabolic syndrome in high grade prostate cancer: development of a clinical nomogram.

Abstract

Background: The aim of our study is to develop a clinical nomogram including metabolic syndrome status for the prediction of high-grade prostate cancer (HG PCa).

Methods: A series of men at increased risk of PCa undergoing prostate biopsies were enrolled in a single center. Demographic and clinical characteristics of the patients were recorded. Metabolic syndrome was defined according to the adult treatment panel III. A nomogram was generated based on the logistic regression model and used to predict high grade prostate cancer defined as grade group ≥3 (ISUP 2014). ROC curves, calibration plots and decision curve analysis were used to evaluate the performance of the nomogram.

Results: Overall, 738 patients were enrolled. Greater than or equal to 294/738 (40%) of the patients presented PCa and of those patients, 84/294 (39%) presented high grade disease (Grade Group ≥3). On multivariate analysis, DRE (OR: 3.24, 95% CI: 1.80-5.84), PSA (OR: 1.10, 95% CI: 1.05-1.16), PV (OR: 0.98, 95% CI: 0.97-0.99) and MetS (OR: 2.02, 95% CI: 1.13-3.59) were predictors of HG PCa. The nomogram based on the model presented good discrimination (AUC: 0.76), good calibration (Hosmer-Lemeshow Test, P>0.05) and a net benefit in the range of probabilities between 10% and 70%.

Conclusions: Metabolic syndrome is highly prevalent in patients at risk of prostate cancer and is particularly associated with high-grade prostate cancer. Our nomogram offers the possibility to include metabolic status in the assessment of patients at risk of prostate cancer to identify men who may have a high-grade form of the disease. External validation is warranted before its clinical implementation.