Comparative effectiveness of umeclidinium/vilanterol versus indacaterol/glycopyrronium on acute exacerbations in patients with chronic obstructive pulmonary disease in England
Bibliographic record
Abstract
Background Real-world evidence comparing long-acting muscarinic antagonist/long-acting β 2 -agonist dual therapies on acute exacerbations of chronic obstructive pulmonary disease (AECOPD) is limited. Aim and Objectives To compare AECOPD rates in patients newly initiating single-inhaler umeclidinium/vilanterol (UMEC/VI) or indacaterol/glycopyrronium (IND/GLY) in England. Methods Retrospective cohort study using linked primary and secondary healthcare data. Non-inferiority (NI; 10% pre-defined margin) of UMEC/VI versus IND/GLY on rate of AECOPDs (moderate-to-severe, moderate, severe) was assessed in patients indexed on initiation of single-inhaler UMEC/VI or IND/GLY (01/2015–09/2019) at 6, 12 and 18 months post-index. Inverse probability of treatment weighting (IPTW) was used to balance treatment groups on potential confounders. Results In 12 031 eligible patients (UMEC/VI: 8753; IND/GLY: 3278), weighted AECOPD rates with UMEC/VI versus IND/GLY were below the pre-specified NI margin at all time points and significantly lower at 6 months for severe AECOPD. Unweighted analyses were similar. Groups were well balanced on potential confounders after IPTW. Conclusions Newly prescribed UMEC/VI was non-inferior to IND/GLY on rate of moderate-to-severe, moderate, and severe AECOPD in patients with COPD in England. Funding GSK (study 214887) Original
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".