Deescalating Adjuvant Trastuzumab in HER2-Positive Early-Stage Breast Cancer: A Systemic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Background One year of adjuvant trastuzumab in combination with chemotherapy is the standard of care in early-stage human epidermal growth factor receptor 2 (HER2)-positive breast cancer. Existing data on shortening trastuzumab treatment show conflicting results. Methods A search of PubMed and abstracts from key conferences identified randomized trials that compared abbreviated trastuzumab therapy to 1 year of treatment in early-stage HER2-positive breast cancer. Hazard ratios (HRs) and 95% confidence intervals (CIs) were extracted for disease-free survival (DFS) and overall survival (OS). Subgroup analyses evaluated the effect of nodal involvement, estrogen receptor expression, and the duration of abbreviated trastuzumab (9–12 weeks vs 6 months). Odds ratios (ORs) and 95% confidence intervals were computed for prespecified cardiotoxicity events including cardiac dysfunction and congestive heart failure. P values were two-sided. Results Analysis included six trials comprising 11 603 patients. Shorter trastuzumab treatment was associated with worse DFS (HR = 1.14, 95% CI = 1.05 to 1.25, P = .002) and OS (HR = 1.15, 95% CI = 1.02 to 1.29. P = .02). The effect on DFS was not influenced by estrogen receptor status (P for the subgroup difference = .23), nodal involvement (P = .44), or the different duration of trastuzumab in the experimental arm (P = .09). Shorter trastuzumab treatment was associated with lower odds of cardiac dysfunction (OR = 0.67, 95% CI = 0.55 to 0.81, P < .001) and congestive heart failure (OR = 0.66, 95% CI = 0.50 to 0.86, P = .003). Conclusions Compared with 1 year, shorter duration of adjuvant trastuzumab is associated with statistically significantly worse DFS and OS despite favorable cardiotoxicity profile. One year of targeted HER2 treatment should remain the standard adjuvant treatment in early-stage HER2-positive disease with appropriate cardiac monitoring.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".