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Background <p>Pathological complete response (pCR) following neoadjuvant chemotherapy (NAC) predicts favorable prognosis in breast cancer. However, significant gaps remain in identifying reliable predictors of pCR. This study aimed to identify clinicopathological and inflammatory factors associated with pCR in HER2 + breast cancer and develop a predictive nomogram.</p> Patients and Methods <p>We retrospectively analyzed 460 patients with HER2+ breast cancer who received NAC at Nanchang People’s Hospital (January 2017–May 2025). Patients were randomly allocated to the training or testing cohorts at a ratio of 7:3. Variables with significant associations in univariate analysis (<i>P</i> &lt; 0.05) were included in multivariate logistic regression. A nomogram incorporating independent predictors was validated for its discrimination, calibration, and clinical utility.</p> Results <p>Overall pCR rate was 47.2% (217/460). Significantly higher pCR rates occurred with: age ≥ 50 years (53.4% versus &lt; 50:38.7%), ER- (54.6% versus ER+: 39.1%), PR- (52.0% versus PR+: 36.2%), HER2 IHC3+ (51.9% versus IHC2+/FISH+: 26.2%), dual HER2 blockade (54.9% versus chemotherapy alone: 15.9%), and high platelet-to-lymphocyte ratio (PLR) (61.0% versus low: 45.1%) (all <i>p</i> &lt; 0.05). Univariate analysis in the training cohort identified that the aforementioned variables were significant predictors. Multivariate analysis confirmed age ≥ 50 years, HER2 IHC3+, dual HER2 blockade, and high PLR as independent predictors. The nomogram demonstrated good discrimination (training AUC = 0.736; testing AUC = 0.689), satisfactory calibration and favorable clinical net benefit.</p> Conclusions <p>Age ≥ 50 years, HER2 IHC3+, dual HER2 blockade, and high PLR independently predict pCR in patients with HER2+ breast cancer. The nomogram provides a clinically applicable tool for pCR prediction, which may aid in optimizing personalized NAC strategies for this population.</p>

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Predictors of Pathological Complete Response to Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer: Development and Validation of a Clinical-Inflammatory Nomogram

  • 期刊论文

  • 发表日期：

    2026年2月14日

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  • Xiaoliu Jiang,
  • Zhaohui Huang,
  • Xinxin Wang,
  • Jie Long,
  • Lu Jiang,
  • Yali Cao,
  • Jingxian Ding

摘要

Background

Pathological complete response (pCR) following neoadjuvant chemotherapy (NAC) predicts favorable prognosis in breast cancer. However, significant gaps remain in identifying reliable predictors of pCR. This study aimed to identify clinicopathological and inflammatory factors associated with pCR in HER2 + breast cancer and develop a predictive nomogram.

Patients and Methods

We retrospectively analyzed 460 patients with HER2+ breast cancer who received NAC at Nanchang People’s Hospital (January 2017–May 2025). Patients were randomly allocated to the training or testing cohorts at a ratio of 7:3. Variables with significant associations in univariate analysis (P < 0.05) were included in multivariate logistic regression. A nomogram incorporating independent predictors was validated for its discrimination, calibration, and clinical utility.

Results

Overall pCR rate was 47.2% (217/460). Significantly higher pCR rates occurred with: age ≥ 50 years (53.4% versus < 50:38.7%), ER- (54.6% versus ER+: 39.1%), PR- (52.0% versus PR+: 36.2%), HER2 IHC3+ (51.9% versus IHC2+/FISH+: 26.2%), dual HER2 blockade (54.9% versus chemotherapy alone: 15.9%), and high platelet-to-lymphocyte ratio (PLR) (61.0% versus low: 45.1%) (all p < 0.05). Univariate analysis in the training cohort identified that the aforementioned variables were significant predictors. Multivariate analysis confirmed age ≥ 50 years, HER2 IHC3+, dual HER2 blockade, and high PLR as independent predictors. The nomogram demonstrated good discrimination (training AUC = 0.736; testing AUC = 0.689), satisfactory calibration and favorable clinical net benefit.

Conclusions

Age ≥ 50 years, HER2 IHC3+, dual HER2 blockade, and high PLR independently predict pCR in patients with HER2+ breast cancer. The nomogram provides a clinically applicable tool for pCR prediction, which may aid in optimizing personalized NAC strategies for this population.