Nomogram-Predicted Survival of Breast Cancer Brain Metastasis: a SEER-Based Population Study

Abstract

The prognosis of patients with breast cancer brain metastasis (BCBM) was dismal and the prognoses varied according to different prognostic factors. In this study, we used the SEER (Surveillance Epidemiology and End Results) database to identify prognostic factors with the BCBMs. We identified and built a robust prognostic model and developed reliable nomograms to estimate the individualized overall survival (OS) and breast cancer-specific survival (BCSS) of patients with BCBM. A total of 789 patients with newly diagnosed BCBM were identified from the SEER database and randomly divided into training (n= 554) and testing (n= 235) cohorts. The log-rank tests and the Cox proportional hazards model were applied to evaluate the prognostic effects of multiple clinicopathologic variables on the survival of training cohorts. Significant prognostic factors were combined to build the nomograms that were evaluated using the concordance index and calibration plots for internal and external validations. Two nomograms shared the common prognostic indicators including age, tumor subtype, chemotherapy, surgery, number of metastatic sites except the brain, and median household income. In the training cohort, the Harrell concordance index for the constructed nomogram to predict OS and BCSS was 0.668 and 0.676, respectively. The calibration plots were consistent between nomogram-predicted survival probability and actual survival probability. These results were reproducible when nomograms were applied to the testing cohort for external validation. Nomograms that predicted 6-month, 1-year, and 2-year OS and BCSS for patients with newly diagnosed BCBM with satisfactory performance were constructed to help physicians in evaluating the high risk of mortality in patients.