Do all patients with HER2 positive breast cancer require one year of adjuvant trastuzumab? A systematic review and meta-analysis
Bibliographic record
Abstract
One year of adjuvant trastuzumab is considered the standard treatment for patients with HER2 positive breast cancer. However, a shorter duration of trastuzumab may be associated with reduced costs and side effects. Results from randomized trials with diverse non-inferiority margins comparing one year to a shorter duration of adjuvant trastuzumab are not consistent and have not been systematically reviewed using a non-inferiority meta-analysis approach. We conducted a systematic review and meta-analysis of randomized trials to assess whether a shorter duration of adjuvant trastuzumab was non-inferior to one year of treatment or not. The non-inferiority margin for the meta-analysis was pre-defined as the median of the margins of all the trials included. Data of 11,376 patients from 5 trials were analyzed. Non-inferiority margins in included studies varied from 1.15 to 1.53 with median of 1.29 for HR of DFS. A shorter duration of trastuzumab was non-inferior to one year of therapy for DFS (HR 1.13, 95%CI 1.03-1.24) but inconclusive for OS (HR 1.14, 95%CI 1.00-1.30). In a subgroup analysis for DFS outcome, shorter therapy was non-inferior in patients with ER positive disease (HR 1.10, 95%CI 0.95-1.28) and those with sequential therapy (HR 0.97, 95%CI 0.75-1.27) and when the duration of treatment was 6 months (HR 1.09, 95%CI 0.98-1.22). Although a shorter duration of adjuvant trastuzumab was non-inferior to one year of therapy for DFS in patients with HER2 positive breast cancer based on our HR margin of 1.29, any benefit of a shorter duration comes at a loss of efficacy with an increase in absolute risk up to 3.9% for 5 year DFS. Whether the potential increased risk is clinically acceptable for the benefits of a shorter duration remains debatable.
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 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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.038 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".