A Nomogram for Predicting Survival in Patients With Breast Cancer Liver Metastasis: A Population-Based Study - Xiong, Yu; Shi, Xia; Hu, Qi; Wu, Xingwei; Long, Enwu; Bian, Yuan (Frontiers in Oncology, 2021)
OBJECTIVE: The prognosis of patients with breast cancer liver metastasis (BCLM) was poor. We aimed at constructing a nomogram to predict overall survival (OS) for BCLM patients by SEER (Surveillance Epidemiology and End Results), thus choosing optimized therapeutic regimen to treat. METHODS: We identified 1173 patients with BCLM from the SEER darabase and randomly divided into training (n=824) and testing (n=349) cohorts. The Cox proportional hazards model was applied to identify independent prognostic facors for BCLM, based on which a nomogram was constructed to predict 1-, 2- and 3-year OS. Its discrimination and calibration were evaluated by the Concordance index (C-index) and calibration plots, while the accuracy and benefits were assessed by comparing it to AJCC-TNM sraging system using the decision curve analysis (DCA). Kaplan-Meier survival analyses were applied to test the clinical utility of the risk stratification system. RECULTS: Grande, marital status, surgery, radiation therapy, chemotherapy, CS tumor size, tumor subtypes, bone metastatic, brain metastatic and lung metastatic were identified to be independent prognostic factors of OS. Compare to the AJCC-TNM stage, the C-index (training group: 0.701 vs. 0.557, validation group: 0.634 vs. 0.557). The calibration curves were consistent between nomogram-predicted survival probability and actual survival probability. Additionally, the DCA curves yielded larger net benefits than the AJCC-TNM staging system. Finally, the risk stratification system can significantly distinguish the ones with different survival risk based on the different molecular subtypes. CONCLUSION: We have successfully built an effective nomogram and risk stratification system to predict OS in BCLM patients, which can assist clinicians in choosing the appropriate therapy strategies for individual BCLM patients.