A Predictive Model for the Early Death of Breast Cancer With Synchronous Liver Metastases: A Population-Based Study

Author:

Liu Shaochun1ORCID,Jia Yingxue1,Chai Jiaying1,Ge Han1,Huang Runze1,Li Anlong1,Cheng Huaidong123ORCID

Affiliation:

1. Department of Oncology, The Second Hospital of Anhui Medical University, Hefei, China

2. Shenzhen Clinical Medical School of Southern Medical University

3. Department of Oncology, Shenzhen Hospital of Southern Medical University, Shenzhen, China

Abstract

Background Breast cancer liver metastasis (BCLM) is a severe condition often resulting in early death. The identification of prognostic factors and the construction of accurate predictive models can guide clinical decision-making. Methods A large sample of data from the Surveillance, Epidemiology, and End Results (SEER) database was analyzed, including 3711 patients diagnosed with de novo BCLM between 2010 and 2015. Predictive models were developed using histograms, and stepwise regression addressed variable collinearity. Internal validation was performed, and results were compared to similar studies. Results In this study of 3711 BCLM patients, 2571 didn't have early death. Out of the 1164 who died early, 1086 had cancer-specific early death. Prognostic factors for early death, including age, race, tumor size, and lymph node involvement, were identified. A nomogram based on these factors was constructed, accurately predicting early all-cause and cancer-specific death. Conclusions Valuable insights into the prognosis of BCLM patients were provided, and important prognostic factors for early death were identified. The developed nomogram can assist clinicians in identifying high-risk patients for early death and inform treatment decisions.

Funder

Postgraduate Innovation Research and Practice Program of Anhui Medical University

Publisher

SAGE Publications

Subject

Oncology,Hematology,General Medicine

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