Indirect treatment comparison (ITC) of mepolizumab and dupilumab in treating COPD
Bibliographic record
Abstract
Background: Monoclonal antibodies targeting type 2 inflammation, mepolizumab and dupilumab, reduced rates of moderate/severe COPD exacerbations in Phase III randomised controlled trials. Aims: Compare mepolizumab data from MATINEE ( NCT04133909 ) vs pooled dupilumab data from BOREAS/NOTUS ( NCT03930732 /04456673). Methods: An ITC was conducted in patients with BEC ≥300 cells/µL, and a subset of MATINEE patients with investigator-assessed symptoms of chronic bronchitis, mMRC score ≥2 and GOLD 1–3 at screening, using matching adjustment for effect modifiers (Figure). Outcomes were annualised rates of moderate/severe and of severe exacerbations, time to first moderate/severe exacerbation, and proportion of SGRQ responders. Results: See Figure. There were no significant differences for mepolizumab vs dupilumab in reducing the rate of moderate/severe exacerbations (RR [95% CI]: 0.91 [0.60, 1.37]). Mepolizumab was associated with lower rates of severe exacerbations (RR [95% CI]: 0.68 [0.27, 1.72]) and hazard of first moderate/severe exacerbation (HR [95% CI]: 0.71 [0.46, 1.08]), although with no statistically significant difference. No significant differences in SGRQ responders (OR [95% CI]: 1.19 [0.63, 2.24]). Conclusions: The ITC showed no significant difference between mepolizumab and dupilumab in reducing the risk of exacerbations and improving SGRQ in a subset of patients with COPD with similar clinical phenotypes. Funding: GSK (223396). erj;66/suppl_69/PA488/F1 F1 F1
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.021 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 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".