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.
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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 | 0.019 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| 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".