Predictors of pathological complete response to neoadjuvant chemotherapy in HER2-positive breast cancer: development and validation of a clinical-inflammatory nomogram

Background Pathological complete response (pCR) following neoadjuvant chemotherapy (NAC) strongly predicts favorable prognosis in patients with breast cancer. However, significant gaps remain in identifying reliable predictors of pCR—particularly regarding inflammatory biomarkers. This study aimed to identify clinicopathological and inflammatory factors associated with pCR in human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients and develop a predictive nomogram. Methods We retrospectively analyzed 460 patients with HER2 + breast cancer who received NAC at Nanchang People's Hospital (January 2017–May 2024). Patients were randomly allocated to the training (n = 322) or testing (n = 138) cohorts at a ratio of 7:3. Variables with significant associations in the univariate analysis (P < 0.05) were included in the multivariate logistic regression. A nomogram incorporating independent predictors was validated for its discrimination, calibration, and clinical utility. Results The overall pCR rate was 47.2% (217/460). The pCR rates were significantly higher for those aged ≥ 50 years (53.4% vs < 50:38.7%), those with estrogen receptor (ER)- (54.6% vs ER+:39.1%), those with progesterone receptor (PR)- (52.0% vs PR+: 36.2%), those with HER2 IHC3+ (51.9% vs IHC2+/FISH+:26.2%), those with dual HER2 blockade (54.9% vs chemotherapy alone:15.9%), and those with high PLRs (≥ 206 vs < 206:61.0% vs 45.1%) (all P < 0.05). Univariate analysis of the training cohort revealed that age, ER status, PR status, HER2 status, NAC regimens, and the PLR were significant predictors. Multivariate analysis confirmed that age ≥ 50 years (OR = 1.789, 95% CI: 1.098–2.933, p = 0.021), HER2 IHC3 + status (OR = 2.734, 95% CI: 1.414–5.460, p = 0.003), dual HER2 blockade (OR = 6.483, 95% CI: 2.482–20.390, p < 0.001), and high PLR (OR = 2.121, 95% CI: 1.040–4.485, p = 0.043) were independent predictors. The nomogram demonstrated good discrimination (training AUC = 0.755; testing AUC = 0.708), satisfactory calibration (Hosmer–Lemeshow test: training P = 0.203, testing P = 0.459), and favorable net clinical benefit. Conclusion Age ≥ 50 years, HER2 IHC 3 + status, dual HER2 blockade, and high PLR independently predict pCR in patients with HER2 + breast cancer. The developed nomogram provides a clinically applicable tool for pCR prediction, which may aid in optimizing personalized NAC strategies for this patient population.