A Practical Immunohistochemistry-Based Model for Predicting Pathologic Complete Response in Estrogen Receptor-Strong Positive and HER2-Negative Breast Cancer
- Author:
Su Min LEE
1
;
Jeong Eon LEE
;
Seok Jin NAM
;
Seok Won KIM
;
Jonghan YU
;
Byung Joo CHAE
;
Se Kyung LEE
;
Jai Min RYU
;
Eun Yoon CHO
;
Hyunwoo LEE
;
Woong Ki PARK
Author Information
- Publication Type:Original Article
- From:Journal of Breast Cancer 2026;29(2):128-140
- CountryRepublic of Korea
- Language:English
-
Abstract:
Purpose:While the benefit of neoadjuvant chemotherapy (NAC) has been established in human epidermal growth factor receptor 2 (HER2)-positive and triple-negative breast cancers, its effectiveness in achieving pathological complete response (pCR) and optimal patient selection in estrogen receptor (ER)-positive, HER2-negative breast cancers remain less clearly defined. This study aimed to identify immunohistochemistry (IHC)-based predictors of pCR and to develop a scoring model for ER-strong positive/HER2-negative breast cancer.
Methods:Data from a prospective cohort were retrospectively analyzed. We included 522 patients with ER-strong positive/HER2-negative tumors who received NAC and surgery between 2008 and 2021. IHC markers including progesterone receptor (PR), Ki-67, epidermal growth factor receptor (EGFR), cytokeratin 5/6 (CK5/6), and p53 were evaluated to identify predictors of pCR. Independent predictors of pCR from multivariate logistic regression were used to develop a weighted 4-point model. Model performance was assessed using receiver operating characteristic analysis. The prognostic impact of pCR was evaluated using KaplanMeier and Cox regression analyses.
Results:Independent predictors of pCR included PR-negative status, positivity for basallike markers (EGFR or CK5/6), and Ki-67 ≥ 50%. The scoring model demonstrated good discrimination for pCR (area under the curve = 0.754). pCR rates increased stepwise, with scores of 4.9% (low), 10.7% (intermediate), and 36.2% (high). In the high-score group, pCR was significantly associated with improved disease-free survival (hazard ratio [HR], 0.09; p = 0.023) and distant metastasis-free survival (HR, 0.11; p = 0.035), whereas no significant survival differences according to pCR status were observed in the low and intermediate score groups.
Conclusion:This IHC-based model predicts pCR and helps identify subgroups in which pCR is associated with meaningful survival benefit following NAC in ER-positive/HER2-negative breast cancers. High-scoring patients may benefit from NAC, while patients with low- or intermediatescores may be better managed with surgery and endocrine therapy. This model may support personalized treatment decisions regarding NAC.
