Risk Evaluation of Bone Metastases and a Simple Tool for Detecting Bone Metastases in Prostate Cancer: A Population-Based Study

Abstract

Introduction. Population-based estimates of the incidence and prognosis of bone metastases in prostate cancer (PC) are lacking. We aimed to characterize the incidence and risk of bone metastases and develop a simple tool for the prediction of bone metastases among patients with PC. Methods. Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A total of 75698 patients with PC with confirmed presence or absence of bone metastases at diagnosis between 1975 and 2019 in the United States were used for analysis. Data were stratified by age, race, residence, median income, prostate-specific antigen (PSA) values, tumor size, distant metastatic history, and positive lymph node scores. Multivariable logistic and Cox regressions were performed to identify predictors of bone metastases and factors correlated with all-cause mortality. Classification tree analysis was performed to establish a model. Results. After patients with PC with missing data were excluded, 75698 cases remained. Among these, 3835 patients had bone metastases. Incidence proportions were highest in patients with a high prostate-specific antigen (PSA) value (odds ratio (OR), 2.49; 95% confidence interval (CI), 1.35-4.35; $p<0.002$ ). Multivariable Cox regression and risk analyses indicated that high PSA values (hazards ratio (HR), 19.8; 95% CI, 18.5-21.2; $p<0.001$ ) and high positive lymph node scores (vs. score 0; HR, 8.65; 95% CI, 7.89-9.49; $p<0.001$ ) were significant risk factors for mortality. Meanwhile, in the predication tree analysis, PSA values and lymph node scores were the most significant determining factors in two models. Median survival among the patients with PC was 78 months, but only 31 months among those with bone metastases. Conclusion. Patients with PC with high PSA values or high positive lymph node scores were at a significantly higher risk of bone metastases. Our study may provide a simple and accurate tool to identify patients with PC at high risk of bone metastases based on population-based estimates.