A new nomogram for the prediction of bone metastasis in patients with prostate cancer

Abstract

Objective This study aimed to establish a new prognostic nomogram for bone metastasis in patients with prostate cancer (PCa). Methods This study retrospectively analyzed clinical data from 332 patients diagnosed with PCa from 2014 to 2019, and patients were randomly divided into a training set (n = 184) and a validation set (n = 148). Multivariate logistic regression analysis was used to establish a prediction model based on the training set, and a nomogram was constructed for visual presentation. The calibration, discrimination and clinical usefulness of the model were evaluated using the validation set. Results Total prostate-specific antigen, clinical tumor stage, Gleason score, prostate volume, red cell distribution width and serum alkaline phosphatase were selected as predictors to develop a prediction model of bone metastasis. After evaluation, the model developed in our study exhibited good discrimination (area under the curve: 0.958; 95% confidence interval: 0.93–0.98), calibration (U = 0.01) and clinical usefulness. Conclusions The new proposed model showed high accuracy for bone metastasis prediction in patients with PCa and good clinical usefulness.