Evidence map›Paper›PMID 42829717›Full record

ArticleCancer management and research2026

Development and External Validation of a Preoperative Nomogram for Predicting Axillary Lymph Node Metastasis in Breast Cancer Using Routine Ultrasound and Core Needle Biopsy Variables.

Nijiati Taxifulati, Gulisumuhan Abulaiti, Yuan Zhang, Chenming Guo, Xin Yang

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Article in Cancer management and research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Nijiati TaxifulatiDepartment of Breast Surgery, Branch of The First Affiliated Hospital of Xinjiang Medical University, Changji, Xinjiang, People's Republic of China.
Gulisumuhan AbulaitiDepartment of Pediatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, People's Republic of China.
Yuan ZhangDepartment of Breast Surgery, Branch of The First Affiliated Hospital of Xinjiang Medical University, Changji, Xinjiang, People's Republic of China.
Chenming GuoDepartment of Breast Surgery, Branch of The First Affiliated Hospital of Xinjiang Medical University, Changji, Xinjiang, People's Republic of China.ORCID 0000-0002-4531-8958
Xin YangDepartment of Breast Surgery, Branch of The First Affiliated Hospital of Xinjiang Medical University, Changji, Xinjiang, People's Republic of China.

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6 · The paper itself

Abstract

Background: Accurate preoperative assessment of axillary lymph node metastasis (ALNM) is essential for individualized axillary management in breast cancer, yet imaging-based evaluation alone remains imperfect. We aimed to develop and externally validate a practical nomogram based on routinely available preoperative ultrasound and core needle biopsy (CNB) variables. Methods: This retrospective, two-center cohort study included 295 women with pathologically confirmed primary breast cancer who underwent breast surgery with axillary nodal staging between January 2021 and January 2025. The training cohort included 182 patients from the Changji Branch, and the external validation cohort included 113 patients from the First Affiliated Hospital of Xinjiang Medical University. Candidate predictors were evaluated using univariable analysis, LASSO regression, and multivariable logistic regression. Model discrimination, calibration, and clinical utility were assessed using receiver operating characteristic analysis, calibration analysis, and decision curve analysis. Results: ALNM was confirmed in 88 of 182 patients (48.4%) in the training cohort and 50 of 113 patients (44.2%) in the external validation cohort. The final nomogram included ultrasound-reported calcifications, tumor size, histological grade, CNB-derived lymphovascular invasion, and HER2 status. The model showed good discrimination, with an AUC of 0.858 (95% CI 0.805-0.911) in the training cohort and 0.854 (95% CI 0.779-0.929) in the external validation cohort. Calibration and decision curve analyses supported acceptable model performance and potential clinical utility in both cohorts. Conclusion : We developed and externally validated an interpretable preoperative nomogram using routinely obtainable ultrasound and CNB variables for individualized estimation of ALNM risk in breast cancer. The model may support preoperative risk stratification and axillary management planning, although prospective multicenter validation is warranted.

Indexed as

axillary lymph node metastasisbreast cancernomogramprediction modelrisk stratification

Identifiers

PMID42829717
PMCPMC13633722

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