Abstract
BACKGROUND: Accurate preoperative prediction of axillary pathological complete response (apCR) following neoadjuvant therapy (NAT) is crucial for de-escalating axillary surgery in breast cancer (BC) patients. This study aimed to develop and validate a dedicated preoperative nomogram for predicting apCR in human epidermal growth factor receptor 2 (HER2)-positive BC using readily available clinical variables and to further evaluate the prognostic significance of apCR for survival outcomes within our cohort. METHODS: This retrospective study enrolled 189 patients with initially node-positive, HER2-positive BC who received NAT and anti-HER2 targeted therapy. Predictors were selected via least absolute shrinkage and selection operator (LASSO) regression, and a multivariable logistic regression model was constructed and presented as a nomogram. Model performance was assessed by the area under the receiver operating characteristic curve (AUC), calibration curves, decision curve analysis (DCA), and clinical impact curve (CIC), with internal validation conducted through 1000 bootstrap resamples. The prognostic value of apCR was evaluated using Kaplan-Meier survival analysis and Cox regression. RESULTS: In total, 115 patients (60.85%) achieved apCR in our cohort. Multivariable analysis identified three independent preoperative predictors of apCR: larger baseline axillary burden (>20 mm; OR = 0.38, 95% CI: 0.19-0.75; P = 0.005), early ultrasonographic response (complete response [CR]: OR = 4.36, 95% CI: 1.46-16.20; P = 0.014; major response [MR]: OR = 3.84, 95% CI: 1.39-12.08; P = 0.014), and receipt of intensive anti-HER2 therapy (OR = 2.03, 95% CI: 1.05-4.00; P = 0.038). The nomogram incorporating these factors demonstrated good discrimination, with an AUC of 0.735 (95% CI: 0.663-0.807), and showed good calibration and clinical utility. Furthermore, patients achieving apCR had significantly superior disease-free survival (DFS) (HR = 0.29, 95% CI: 0.09-0.92, P = 0.036). CONCLUSIONS: Our study developed and validated a preoperative nomogram that predicts apCR in HER2-positive BC by integrating three readily available clinical variables. This model demonstrates the potential to preoperatively identify candidates who may be suitable for axillary de-escalation strategies, pending future multi-center prospective validation. The established prognostic value of apCR in our cohort underscores its relevance as a critical clinical endpoint.