BACKGROUND: The pan-immune inflammation value (PIV) has unclear predictive utility for pathologic complete response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). This study aimed to evaluate the PIV's predictive value and develop a nomogram integrating PIV for individualized pCR prediction. METHODS: In a retrospective multicenter study of 507 NAC-treated patients (training cohort: 357
validation cohort: 150), independent predictors of pCR were identified through univariate and multivariate logistic regression. A nomogram was constructed and validated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) evaluated the improvement in performance after incorporating the PIV indicator. RESULTS: The high PIV patients (cutoff: 316.533) had significantly lower pCR rates than the low PIV patients ( CONCLUSIONS: The PIV is an independent predictor of pCR, and the PIV-based nomogram provides a reliable tool for optimizing NAC response prediction in breast cancer.