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A Practical Immunohistochemistry-Based Model for Predicting Pathologic Complete Response in Estrogen Receptor-Strong Positive and HER2-Negative Breast Cancer.

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Journal of breast cancer 📖 저널 OA 75.9% 2026
Retraction 확인
출처

PICO 자동 추출 (휴리스틱, conf 3/4)

유사 논문
P · Population 대상 환자/모집단
522 patients with ER-strong positive/HER2-negative tumors who received NAC and surgery between 2008 and 2021.
I · Intervention 중재 / 시술
NAC and surgery between 2008 and 2021
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
High-scoring patients may benefit from NAC, while patients with low- or intermediate-scores may be better managed with surgery and endocrine therapy. This model may support personalized treatment decisions regarding NAC.

Lee SM, Lee JE, Nam SJ, Kim SW, Yu J, Chae BJ, Lee SK, Ryu JM, Cho EY, Lee H, Park WK

ℹ️ 이 논문은 무료 전문이 아직 없습니다. 코퍼스 전체의 43.6%는 무료 가능 (통계 →) · 🏥 기관 EZproxy로 시도

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[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

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↓ .bib ↓ .ris
APA Lee SM, Lee JE, et al. (2026). A Practical Immunohistochemistry-Based Model for Predicting Pathologic Complete Response in Estrogen Receptor-Strong Positive and HER2-Negative Breast Cancer.. Journal of breast cancer. https://doi.org/10.4048/jbc.2025.0242
MLA Lee SM, et al.. "A Practical Immunohistochemistry-Based Model for Predicting Pathologic Complete Response in Estrogen Receptor-Strong Positive and HER2-Negative Breast Cancer.." Journal of breast cancer, 2026.
PMID 41612660 ↗

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 Kaplan-Meier and Cox regression analyses.

[RESULTS] Independent predictors of pCR included PR-negative status, positivity for basal-like 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; = 0.023) and distant metastasis-free survival (HR, 0.11; = 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 intermediate-scores may be better managed with surgery and endocrine therapy. This model may support personalized treatment decisions regarding NAC.

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