AccScience Publishing / EJMO / Online First / DOI: 10.36922/EJMO025110055
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ORIGINAL RESEARCH ARTICLE

Risk factor analysis for human epidermal growth factor receptor 2-positive breast cancer patients with brain metastasis: A risk prediction model based on the Surveillance, Epidemiology, and End Results database

Xulong Zhu1,2† ,  Xinmiao Liu1† ,  Ziyu Luo1 ,  Shuhan Wu1 ,  Hengtao Song1 ,  Ke Yan1 ,  Yue Wang1 ,  Liping Yang1 ,  Wenjun Shu1 ,  Kenian Pan2 ,  Jianhui Li1,2*
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1 Department of Surgical Oncology, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China
2 Department of First Clinical Medicine, Faculty of Surgery Teaching and Research, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
†These authors contributed equally to this work.
EJMO, 025110055 https://doi.org/10.36922/EJMO025110055
Received: 15 March 2025 | Revised: 12 May 2025 | Accepted: 4 June 2025 | Published online: 11 August 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Introduction: Human epidermal growth factor receptor 2 (HER2)-positive breast cancer is characterized by increased cell proliferation and a high potential for metastasis, resulting in a poorer prognosis–especially when brain metastases occur. At present, no definitive clinical factors or predictive models exist to guide prognosis in this patient group.

Objective: This study aims to identify prognostic factors affecting survival in HER-2 breast cancer patients with brain metastases and to construct a model to assess prognosis based on clinical characteristics.

Methods: Data from female patients diagnosed with breast cancer brain metastases between 2011 and 2020 were extracted from the Surveillance, Epidemiology, and End Results database. Seventeen clinical factors were evaluated for their association with brain metastasis in HER2-positive breast cancer. Univariate and multivariate Cox proportional hazard regression analyses were performed, and Kaplan-Meier survival curves were plotted based on independent risk factors. A nomogram model was then developed to predict survival rates at different time intervals. Model performance was evaluated using calibration curves and the concordance index. Receiver operating characteristic analysis and decision curve analysis (DCA) were also conducted to evaluate predictive accuracy and clinical utility.

Results: Cox regression analyses identified nine clinical characteristics significantly associated with overall survival (OS) and seven factors influencing breast cancer-specific survival: molecular subtype, age, node stage, liver and lung metastases, and estrogen receptor and progesterone receptor status. The models achieved concordance indices of 0.680 (OS) and 0.663 (breast cancer-specific survival). The nomogram demonstrated strong predictive power, with area under the curve values of 0.767 and 0.700, respectively. DCA showed that the model curve significantly outperformed the two extreme curves.

Conclusion: This study identified key prognostic factors and developed a nomogram-based model with strong predictive value for HER2-positive breast cancer patients with brain metastases.

Keywords
Brain metastasis
Human epidermal growth factor receptor 2
Risk prediction model
Surveillance Epidemiology and End Results database
Survival rate
Funding
This research is supported by Shaanxi Provincial Health Breast and Thyroid Disease Medical-Engineering Scientific Research and Innovation Team (2024TD-01) and Shaanxi Provincial Clinical Research Center for Breast Diseases Project (2024SF-LCZX-08).
Conflict of interest
The authors declare that they do not have any competing interests.
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Eurasian Journal of Medicine and Oncology, Electronic ISSN: 2587-196X Print ISSN: 2587-2400, Published by AccScience Publishing
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