Longer-Term Outcomes of Letrozole Versus Placebo After 5 Years of Tamoxifen in the NCIC CTG MA.17 Trial: Analyses Adjusting for Treatment Crossover
Bibliographic record
Abstract
PURPOSE: The interim analysis of the National Cancer Institute of Canada Clinical Trials Group MA.17 trial showed that letrozole was significantly better than placebo in disease-free survival (DFS) for postmenopausal women with hormone receptor-positive breast cancer following about 5 years of tamoxifen therapy. When patients were unblinded, those on placebo were offered letrozole. Longer-term efficacy of letrozole, especially survival, was of particular interest because the median follow-up of the first interim analysis was only 2.5 years. Efficacy was difficult to assess because more than 60% of placebo patients crossed over to letrozole after being unblinded. PATIENTS AND METHODS: Two statistical approaches were used to adjust for the potential effects of treatment crossover: one was based on the inverse probability of censoring weighted (IPCW) Cox model and the other on a Cox model with time-dependent covariates. RESULTS: With a median follow-up of 64 months, the hazard ratios (HRs) of letrozole and placebo from the IPCW analyses were HR of 0.52 (95% CI, 0.45 to 0.61; P < .001) for DFS, HR of 0.51 (95% CI, 0.42 to 0.61; P < .001) for distant disease-free survival (DDFS), and HR of 0.61 (95% CI, 0.52 to 0.71; P < .001) for overall survival (OS). The results from the analyses based on the Cox model with time-dependent covariates were similar for letrozole and placebo: HR of 0.58 (95% CI, 0.47 to 0.72; P < .001) for DFS, HR of 0.68 (95% CI, 0.52 to 0.88; P = .004) for DDFS, and HR of 0.76 (95% CI, 0.60 to 0.96; P = .02) for OS. CONCLUSION: Exploratory analyses based on longer follow-up and adjusting for treatment crossover suggest that extended adjuvant letrozole was superior to placebo in DFS, DDFS, and OS.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".