Reduction of asthma exacerbations after escalation from BUD/FORM or FP/SAL to FF/UMEC/VI
Bibliographic record
Abstract
Rationale ICS/LABA is recommended for patients with asthma, with BUD/FORM and FP/SAL commonly used before escalation to FF/UMEC/VI. Real-world evidence on the effectiveness of FF/UMEC/VI on exacerbations, stratified by prior ICS/LABA used (BUD/FORM or FP/SAL), was evaluated for patients with asthma in the US. Methods Retrospective pre-post outcomes were assessed using Komodo Health Database claims data (09/2019–12/2023). The index date was the first FF/UMEC/VI pharmacy claim. Adults with asthma, ≥12 months continuous insurance pre-/post-initiation and ≥30 consecutive days ICS/LABA (BUD/FORM or FP/SAL) use pre-initiation were included. Asthma-related exacerbations were evaluated using rate ratios (RRs; 95% CIs) from Poisson regression. Results Of 11,522 patients (mean age 50 years; 70% female), 6073 (53%) last used BUD/FORM and 5449 (47%) used FP/SAL. Overall exacerbations were significantly reduced regardless of prior ICS/LABA (38%; RR [95% CI]: 0.62 [0.60, 0.64]). When stratified by formulation, exacerbations were significantly reduced by 39% for BUD/FORM (0.61 [0.58, 0.63]) and 37% for FP/SAL (0.63 [0.60, 0.66]). Reductions were consistent across IP/ED visits and systemic corticosteroid utilisation (Figure). Conclusions Patients who escalate to FF/UMEC/VI from ICS/LABA significantly reduced asthma exacerbations irrespective of prior BUD/FORM or FP/SAL treatment. Funding GSK (300181). erj;66/suppl_69/PA4643/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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".