Efficacy of mepolizumab in patients with COPD & type 2 inflammation: Pooled Phase III trial results
Bibliographic record
Abstract
Background: MATINEE ( NCT02105948 ) enrolled patients with all COPD subtypes and blood eosinophil count (BEC) ≥300 cells/µL. METREX/METREO ( NCT02105961 /04133909) enrolled patients with BEC ≥300 as well as <300 cells/µL. All studies included airflow obstruction from GOLD 2–4. Aims: Assess mepolizumab efficacy in COPD, in a large population across the Phase III (Ph3) METREX/METREO/MATINEE trials. Methods: Integrated analysis from three Ph3 trials assessing the efficacy of mepolizumab 100 mg vs placebo (PBO) in patients with COPD, BEC ≥300 cells/µL, a history of exacerbations, and receiving triple therapy (N=1146; 568 mepolizumab). Outcomes included annualised rate of and time to first moderate/severe exacerbation, annualised rate of exacerbations requiring emergency department (ED) visit and/or hospitalisation, and change in St. George’s Respiratory Questionnaire (SGRQ) including responders (≥4-point reduction) at Week 52 and change from baseline. Results: Mepolizumab-treated patients had significantly lower annualised rates of moderate/severe exacerbations and exacerbations requiring ED visit and/or hospitalisation vs PBO: by 21% (rate ratio [95% CI]: 0.79 [0.68, 0.91]) and 29% (0.71 [0.51, 0.98]), respectively. Risk of experiencing a first moderate/severe exacerbation was 28% lower with mepolizumab (hazard ratio [95% CI]: 0.72 [0.62, 0.85]). SGRQ improvement was numerically greater with mepolizumab vs PBO (difference [95% CI]: –2.2 [–4.14, –0.24]) as was proportion of SGRQ responders (50% vs 44%; odds ratio [95% CI]: 1.24 [0.97, 1.58]). Conclusions: Integrated analysis of three Ph3 trials confirmed mepolizumab benefits in COPD with BEC ≥300 cells/µL. Funding: GSK (117106/117113/208657).
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".