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Independent Risk Factors and a New Nomogram for Predicting Breast Cancer Risk for Bone Metastasis in Chinese Women: A
Yunfei Huang1, Tianjiao Ge1, Heng Song1
1Breast Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang 050017, China.
Journal of Clinical Medicine
|March 28, 2026
Summary
This study identifies key predictors for bone metastasis in breast cancer, including histological grade, progesterone receptor (PR) negativity, human epidermal growth factor receptor 2 (HER-2) negativity, and visceral metastasis. A predictive nomogram was developed to aid in identifying high-risk patients for early intervention.
Area of Science:
- Oncology
- Medical Research
- Clinical Pathology
Background:
- Bone metastasis is a frequent complication in advanced breast cancer, significantly impacting patient quality of life and survival.
- Skeletal-related events (SREs) associated with bone metastasis lead to severe clinical deterioration.
- Identifying patients at high risk for bone metastasis is crucial for timely preventive strategies.
Purpose of the Study:
- To investigate independent risk factors for bone metastasis in breast cancer patients.
- To develop and validate a predictive nomogram for identifying individuals at high risk of bone metastasis.
- To improve clinical decision-making and patient prognosis through early risk assessment.
Main Methods:
- Retrospective analysis of 672 breast cancer patients (training set) and external validation using 2814 patients from the SEER database.
- Collection of clinical and pathological data including histological grade, receptor status (PR, HER-2), and visceral metastasis.
- Application of univariate and multivariate logistic regression to identify predictors and construction of a nomogram model.
Main Results:
- Histological grade, progesterone receptor (PR) negativity, human epidermal growth factor receptor 2 (HER-2) negativity, and visceral metastasis were identified as independent predictors of bone metastasis.
- The developed nomogram demonstrated good predictive performance with an Area Under the Curve (AUC) of 0.720 in the training set and 0.701 in the validation set.
- Decision curve analysis confirmed the clinical utility of the nomogram.
Conclusions:
- Histological grade, PR status, HER-2 status, and visceral metastasis are significant independent factors associated with breast cancer bone metastasis.
- The developed nomogram serves as a valuable and practical tool for predicting breast cancer-related bone metastasis.
- This predictive model can facilitate timely interventions and potentially improve clinical outcomes for breast cancer patients.
