Safety of formoterol in asthma clinical trials: an update
Bibliographic record
Abstract
Use of long-acting β-agonists (LABAs) in asthma remains controversial, and large safety trials are in progress. We have previously reported safety outcomes with formoterol in 117 AstraZeneca asthma trials (78,339 patients, 92% using inhaled corticosteroids) completed by December 2006, and have now added 32 trials with formoterol (26,124 patients, 100% using inhaled corticosteroids) completed by December 2011. The primary dataset of 79 randomised controlled trials includes 94,684 patients, 67,380 of whom were exposed to formoterol, while the complete dataset comprises 149 trials and 104,463 patients. There were no new asthma-related deaths in the expanded primary dataset, with eight asthma-related deaths among formoterol-randomised patients and two among non-LABA-randomised patients (relative risk 1.13, 95% CI 0.23-10.9), and 15 versus nine cardiac-related deaths (relative risk 0.47, 95% CI 0.19-1.22). Nonfatal asthma-related serious adverse events were significantly reduced with formoterol (relative risk 0.63, 95% CI 0.53-0.75), as were discontinuations due to adverse events. Examining 40 trials with direct formoterol versus non-LABA comparisons, Mantel-Haenszel relative risk for asthma-related death was 2.75 (95% CI 0.52-14.4) and for serious adverse events 0.83 (95% CI 0.68-1.02). We conclude that this enlarged dataset indicates no increased risk of asthma-related deaths among patients exposed to formoterol compared with non-LABA treatments, although the wide confidence interval precludes certainty.
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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 | 0.089 | 0.204 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".