Identification of a Low-Risk Luminal A Breast Cancer Cohort That May Not Benefit From Breast Radiotherapy
Bibliographic record
Abstract
PURPOSE: To determine the prognostic and predictive value of intrinsic subtyping by using immunohistochemical (IHC) biomarkers for ipsilateral breast relapse (IBR) in participants in an early breast cancer randomized trial of tamoxifen with or without breast radiotherapy (RT). PATIENTS AND METHODS: IHC analysis of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 (HER2), cytokeratin 5/6, epidermal growth factor receptor, and Ki-67 was conducted on 501 of 769 available blocks. Patients were classified as luminal A (n = 265), luminal B (n = 165), or high-risk subtype (luminal HER2, n = 22; HER2 enriched, n = 13; basal like, n = 30; or triple-negative nonbasal, n = 6). Median follow-up was 10 years. RESULTS: Classification by subtype was prognostic for IBR (10-year estimates: luminal A, 5.2%; luminal B, 10.5%; high-risk subtypes, 21.3%; P < .001). Luminal subtypes seemed to derive less benefit from RT (luminal A hazard ratio [HR], 0.40; luminal B HR, 0.51) than high-risk subtypes (HR, 0.13); however, the overall subtype-treatment interaction term was not significant (P = .26). In an exploratory analysis of women with clinical low-risk (age older than 60 years, T1, grade 1 or 2) luminal A tumors (n = 151), 10-year IBR was 3.1% versus 11.8% for the high-risk cohort (n = 341; P = .0063). Clinical low-risk luminal A patients had a 10-year IBR of 1.3% with tamoxifen versus 5.0% with tamoxifen plus RT (P = .42). Multivariable analysis showed that RT (HR, 0.31; P < .001), clinical risk group (HR, 2.2; P = .025), and luminal A subtype (HR, 0.25; P < .001) were significantly associated with IBR. CONCLUSION: IHC subtyping was prognostic for IBR but was not predictive of benefit from RT. Further studies may validate the exploratory finding of a low-risk luminal A group who may be spared breast RT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".