A preoperative nomogram to predict axillary lymph node involvement in clinically node-negative HR+/HER2- breast cancer

Abstract Objective To develop a preoperative nomogram to predict axillary lymph node involvement in clinically node-negative hormone receptor-positive/HER2-negative (HR+/HER2-) breast cancer. Materials and methods We analyzed a retrospective cohort of consecutive patients with invasive HR+/HER2- breast cancer treated at Fundación Jiménez Díaz University Hospital (Madrid, Spain) between January 2019 and June 2024. All patients underwent breast surgery with axillary staging. Preoperative clinical, imaging, and pathological variables were collected. Predictors of axillary lymph node involvement were identified using multivariable logistic regression with LASSO regularization to construct a points-based nomogram. Model discrimination was assessed by the area under the receiver operating characteristic curve (AUC) and calibration using standard metrics. Diagnostic performance was calculated across various probability thresholds. Results Among 540 patients, 173 (32.0%) had axillary nodal disease. Independent predictors included suspicious axillary ultrasound findings (OR 16.42, 95% CI 8.93–31.92; p < 0.001), lymphovascular invasion (OR 2.61, 95% CI 1.51–4.51; p = 0.001), larger tumor size (per mm OR 1.04, 95% CI 1.02–1.06; p < 0.001), and multifocality/multicentricity (OR 1.88, 95% CI 1.01–3.47; p = 0.048). Histological grade was retained for clinical relevance. The nomogram demonstrated good discrimination (AUC 0.83, 95% CI 0.79–0.87) and calibration (E/O ratio 1.002; Brier score 0.135). Conclusion This nomogram integrates axillary ultrasound findings with preoperative tumor characteristics to accurately estimate nodal involvement in clinically node-negative HR+/HER2- breast cancer. The tool may support individualized risk stratification and inform axillary management in the context of surgical de-escalation. External validation is required prior to clinical implementation.