Prognostic Factors, Predictive Modeling, and Treatment Patterns in Breast Cancer Patients with Bone Metastasis Receiving First-Line Chemotherapy: A Population-Based Study

Abstract

Aim: The prognostic factors and a nomogram applicable to breast cancer (BC) patients with bone metastasis (BM) who received first-line chemotherapy have not been extensively studied. This study aimed to identify prognostic factors and construct a prognostic nomogram to predict overall survival (OS) in this population.

Methods: Data for BC patients with BM undergoing first-line chemotherapy were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016. A total of 2996 BC patients with BM undergoing first-line chemotherapy were included. Age, tumor size, race, tumor grade, breast cancer subtype, brain metastasis, liver metastasis, lung metastasis, surgical intervention, and marital status were identified as independent prognostic factors in the training cohort. Patients were randomly assigned into a training cohort (n = 2100) and an internal validation cohort (n = 896). Prognostic variables were identified using univariate and multivariate Cox Proportional Hazards (Cox) regression analysis. A nomogram was constructed and validated in both cohorts. The discrimination and accuracy of the nomogram were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Results: The areas under the curves (AUCs) for 1-, 2- and 3-year OS were 0.803 (95% confidence interval (CI): 0.752-0.854), 0.785 (95% CI: 0.756-0.814), and 0.767 (95% CI: 0.701-0.803), respectively, in the training cohort, and 0.793 (95% CI: 0.756-0.830), 0.791 (95% CI: 0.761-0.821), and 0.756 (95% CI: 0.719-0.793), respectively, in the validation cohort. The nomogram demonstrated excellent discrimination, calibration, and clinical utility.

Conclusions: This study developed and validated a robust survival prediction model for breast cancer patients with bone metastasis receiving first-line chemotherapy. The nomogram demonstrates strong predictive performance and can aid clinicians in formulating individualized treatment strategies, thereby improving patient outcomes.