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March 13, 2026Frontiers in OncologyOpen Access

A dynamic nomogram for predicting axillary pathological complete response and its prognostic value in HER2-positive breast cancer

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Retrospective study develops a nomogram to predict axillary response in HER2-positive breast cancer, suggesting its clinical utility.

The aim is to create and validate a preoperative nomogram for predicting axillary pathological complete response (apCR) in HER2-positive breast cancer patients.
Retrospective analysis of 189 HER2-positive breast cancer patients receiving neoadjuvant therapy.
Predictors were identified through least absolute shrinkage and selection operator (LASSO) regression.
A multivariable logistic regression model was constructed and represented as a nomogram.
Model performance assessed using AUC, calibration curves, decision curve analysis, and clinical impact curves, with internal validation via bootstrap resampling.
Prognostic value of apCR evaluated using Kaplan-Meier survival analysis and Cox regression.
115 out of 189 patients (60.85%) achieved apCR.
Three independent predictors of apCR identified: larger baseline axillary burden, early ultrasound response, and intensive anti-HER2 therapy.
Nomogram showed good discrimination with an AUC of 0.735 and demonstrated strong calibration and clinical utility.
Patients achieving apCR exhibited significantly improved disease-free survival (DFS) with a hazard ratio of 0.29.

Liu et al. (2026) studied this question.

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