Regional Nodal Irradiation After Breast Conserving Surgery for Early HER2-Positive Breast Cancer: Results of a Subanalysis From the ALTTO Trial
Bibliographic record
Abstract
Background: Two randomized trials recently demonstrated that regional nodal irradiation (RNI) could reduce the risk of recurrence in early breast cancer; however, these trials were conducted in the pretrastuzumab era. Whether these results are applicable to human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients treated with anti-HER2-targeted therapy is unknown. Methods: This retrospective analysis was performed on patients with node-positive breast cancer who were enrolled in the Adjuvant Lapatinib and/or Trastuzumab Treatment Optimization phase III adjuvant trial and subjected to BCS. The primary objective of the present study was to examine the effect of RNI on disease-free survival (DFS). A multivariable cox regression analysis adjusted for number of positive lymph nodes, tumor size, grade, age, hormone receptors status, presence of macrometastatis, treatment arm, and chemotherapy timing was carried out to investigate the relationship between RNI and DFS. Results: One thousand six hundred sixty-four HER2-positive breast cancer patients were included, of whom 878 (52.8%) had received RNI to the axillary, supraclavicular, and/or internal mammary lymph nodes. Patients in the RNI group had higher nodal burden and more frequently had tumors larger than 2 cm. At a median follow-up of 4.5 years, DFS was 84.3% in the RNI group and 88.3% in the non-RNI group. No differences in regional recurrence (0.9 % vs 0.6 %) or in overall survival (93.6% vs 95.3%) were observed between the two groups. After adjustment in multivariable analysis, there was no statistically significant association between RNI and DFS (hazard ratio = 0.96, 95% confidence interval = 0.71 to 1.29). Conclusions: Our analysis did not demonstrate a DFS benefit of RNI in HER2-positive, node-positive patients treated with adjuvant HER2-targeted therapy. The benefit of RNI in HER2-positive breast cancer needs further testing within randomized clinical trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".