Effect of indacaterol/glycopyrronium (IND/GLY) vs salmeterol/fluticasone (SFC) on moderate or severe COPD exacerbations and lung function based on baseline blood eosinophil counts: Results from the FLAME study
Bibliographic record
Abstract
Introduction The FLAME study compared the effect of IND/GLY vs SFC on exacerbations in COPD patients with a risk of exacerbation. Here we present the rate of reduction of moderate or severe exacerbations and lung function changes based on blood eosinophils in moderate-to-very severe COPD patients. Methods This was a 52-week, multicentre study. Patients with moderate-to-very severe COPD, post-bronchodilator FEV1 ≥25% - <60% and a history of ≥1 exacerbation in the previous year were randomised (1:1) to IND/GLY (110/50 µg) once daily or SFC (50/500 µg) twice daily. The data were assessed by blood eosinophil cut offs (<150, 150->300 and ≥300) and percentages (<2% and ≥2%). Results 3362 patients were randomised to IND/GLY (n=1680) or SFC (n=1682). The annualised rate of moderate or severe exacerbations was significantly lower in IND/GLY-treated vs SFC-treated patients9 at all eosinophil counts, although not significant for small number of patients with ≥300 cells/µL. The lung function was significantly improved at all the visits with IND/GLY vs SFC irrespective of eosinophil count (Table 1). Conclusion In patients with high risk of exacerbations, IND/GLY was superior in reducing moderate or severe exacerbations and showed significant improvement in lung function vs SFC independent of blood eosinophil counts.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".