Here, we developed a prostate cancer (PCa) risk nomogram including lymphocyte-to-monocyte ratio (LMR) for initial prostate biopsy, and internal and external validation were further conducted. A prediction model was developed on a training set. Significant risk factors with P < 0.10 in multivariate logistic regression models were used to generate a nomogram. Discrimination, calibration, and clinical usefulness of the model were assessed using C-index, calibration plot, and decision curve analysis (DCA). The nomogram was re-examined with the internal and external validation set. A nomogram predicting PCa risk in patients with prostate-specific antigen (PSA) 4–10 ng ml−1 was also developed. The model displayed good discrimination with C-index of 0.830 (95% confidence interval [CI]: 0.812–0.852). High C-index of 0.864 (95% CI: 0.840–0.888) and 0.871 (95% CI: 0.861–0.881) was still reached in the internal and external validation sets, respectively. The nomogram exhibited better performance compared to the nomogram with PSA only (C-index: 0.763, 95% CI: 0.746–0.780, P < 0.001) and the nomogram with LMR excluded (C-index: 0.824, 95% CI: 0.804–0.844, P < 0.010). The calibration curve demonstrated good agreement in the internal and external validation sets. DCA showed that the nomogram was useful at the threshold probability of >4% and <99%. The nomogram predicting PCa risk in patients with PSA 4–10 ng ml−1 also displayed good calibration and discrimination performance (C-index: 0.734, 95% CI: 0.708–0.760). This nomogram incorporating age, PSA, digital rectal examination, abnormal imaging signals, PSA density, and LMR could be used to facilitate individual PCa risk prediction in initial prostate biopsy.

Keywords: lymphocyte-to-monocyte ratio; nomogram; prostate biopsy; prostate cancer

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