ArticleJournal of breast cancer2026
A Practical Immunohistochemistry-Based Model for Predicting Pathologic Complete Response in Estrogen Receptor-Strong Positive and HER2-Negative Breast Cancer.
Article in Journal of breast cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeWhile 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.
methodsData 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.
resultsIndependent 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;
conclusionThis 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.