Pathologic complete response and outcomes by intrinsic subtypes in NSABP B-41, a randomized neoadjuvant trial of chemotherapy with trastuzumab, lapatinib, or the combination
Bibliographic record
Abstract
PURPOSE: NSABP B-41, a phase three randomized trial, evaluated neoadjuvant lapatinib, trastuzumab, or the combination with chemotherapy in patients with HER2-positive operable breast cancer. Though no significant difference in pathologic complete response (pCR) was found among the three arms, pCR was associated with prolonged survival. We analyzed tumor intrinsic subtypes with Prediction Analysis of Microarray 50 in a subset of B-41 patients to determine their value in predicting HER2-targeting benefit. METHODS: Pearson's Chi square test and logistic regression were used to compare pCR in the breast and nodes (ypT0/Tis ypN0). Kaplan-Meier estimates and Cox models were used to compare event-free and overall survival among subtypes. RESULTS: Intrinsic subtypes were determined in 271 baseline core biopsy samples. The pCR rate among patients with HER2-enriched (HER2E) subtype was greater compared to other subtypes combined (120/197, 60.9% versus 19/74, 25.7%; p < 0.001). In multivariate analysis among patients receiving trastuzumab-containing regimens (with clinical factors and HER2E subtype as factors), HER2E subtype was most strongly associated with pCR [OR 8.41 (95% CI 2.52-28.1) p < 0.001]. Patients with HER2E tumors did not benefit more from dual HER2-targeted therapy versus trastuzumab. The pCR rate was higher among HER2E tumors versus other subtypes in both estrogen receptor-positive and -negative tumors (p ≤ 0.001). Higher ESR1 gene expression was associated with lower pCR rate. No association was observed between subtype and long-term outcomes. CONCLUSION: Patients with HER2E tumors were most likely to attain pCR versus other subtypes. HER2E subtype represents a favorable marker for predicting HER2-targeting benefit, particularly with trastuzumab-based therapies.
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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 | 0.001 |
| 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".