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A study on predicting additional axillary lymph node positivity in breast cancer patients with positive sentinel
Xianwei Long1, Linfeng Xin1, Yan Chen1
1Department of Breast and Thyroid Surgery, Liuzhou People's Hospital Affiliated to Guangxi Medical University, Liuzhou, China.
Background:
Currently, there are limited studies on individualized assessment tools for predicting patients with positive sentinel lymph nodes during breast cancer surgery and exempting axillary lymph node dissection (ALND). Constructing a prediction model based on clinical and pathological features to explore the feasibility of exempting ALND for patients with positive sentinel lymph nodes during breast cancer surgery is of great significance. This study aims to guide the management of axillary lymph nodes in breast cancer patients, so as to ensure the treatment effect while minimizing surgical complications and improving the quality of life of patients.
Methods:
We conducted a retrospective study by collecting data from 133 breast cancer patients who were admitted to the Breast and Thyroid Surgery Department of Liuzhou People's Hospital within the time frame spanning from January 2023 to August 2025. Subsequently, we employed both univariate and multivariate Logistic regression analyses to screen for clinical and pathological features that exhibited a significant association with axillary lymph node metastasis. Based on the identified significant features, we constructed a prediction model aimed at forecasting axillary lymph node metastasis in breast cancer patients. To comprehensively evaluate the predictive performance of the developed model, we utilized receiver operating characteristic (ROC) curves to assess its discriminatory ability, and diagnostic calibration curves to evaluate the accuracy of its predicted probabilities.
Results:
Multivariate analysis revealed that age, the number of positive sentinel lymph nodes, vascular tumor thrombus, and preoperative axillary lymph node diameter were significantly associated with axillary lymph node metastasis. The ROC curve of the prediction model constructed based on these 4 features showed an area under the curve (AUC) of 0.760, and the diagnostic calibration curve indicated that the model had good fit.
Conclusions:
The predictive model established based on age, the number of positive sentinel lymph nodes, vascular tumor thrombus, and the preoperative diameter of axillary lymph nodes can preliminarily predict the risk of axillary lymph node metastasis in patients with positive sentinel lymph nodes during breast cancer surgery.
