A nomogram for predicting brain metastasis in patients with de novo stage IV breast cancer

BACKGROUND: stage IV breast cancer. METHODS: We gathered female patients diagnosed with de novo stage IV breast cancer between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. After randomly allocating the patients to the training set and verification set, we used univariate and multivariate logistic regression to analyze the relationship between BM and clinicopathological features. Finally, we developed a nomogram which was validated by the analysis of calibration curve and receiver operating characteristic curve. RESULTS: stage IV breast cancer, 422 developed BM. Age, tumor size, subtype, and the degree of lung involvement were significantly correlated with BM. The nomogram had discriminatory ability with an area under curve (AUC) of 0.640 [95% confidence interval (CI): 0.607 to 0.673] in the training set, and 0.644 (95% CI: 0.595 to 0.693) in the validation set. CONCLUSIONS: Our study developed a nomogram to predict BM for de novo stage IV breast cancer, thus helping clinicians to identify patients at high-risk of BM and implement early preventive interventions to improve their prognoses.