A Brief Report on a Systematic Review of Real-World Effectiveness Studies of ICS/LAMA/LABA for Treatment of Adults with Asthma in the US
Bibliographic record
Abstract
INTRODUCTION: -agonist (ICS/LABA) dual therapy is recommended for severe asthma, but its real-world effectiveness is not well established. METHODS: A systematic literature review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to investigate clinical outcomes in US adults with asthma receiving ICS + LABA + LAMA as multiple-/single-inhaler triple therapy (MITT/SITT). Real-world/observational studies published in English in Embase/MEDLINE databases (2014-2024) and conference abstracts presented 2022-2024 were eligible for inclusion. RESULTS: From 588 identified records, only 8 articles reporting 6 unique studies were included; 2 assessed SITT and 4 assessed MITT, and 4 treatments were investigated. Exacerbation rates reported in two studies were significantly reduced with tiotropium (TIO) + ICS + LABA MITT versus high-dose ICS + LABA within 6 (64% lower) and 12 months (73%), and fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) 100/62.5/25 mcg SITT versus pre-treatment after 12 months (41%). Oral corticosteroid (OCS) use was reported in two studies. The proportion of patients with ≥ 1 rescue OCS dispensing decreased with TIO 1.25 mcg + ICS + LABA MITT, with greatest reductions for MITT ± leukotriene receptor antagonist (pre-treatment: 68.4%, post treatment: 54.2%). Mean number of OCS dispensings/patient/year significantly decreased (29%, p < 0.001) following FF/UMEC/VI 100/62.5/25 mcg SITT initiation. Treatment adherence/persistence was reported in three studies. Mean (standard deviation) proportion of days covered was significantly higher (p < 0.001) for FF/UMEC/VI SITT versus MITT after 6 (0.56 [0.31] versus 0.46 [0.31]) and 12 months (0.46 [0.33] versus 0.35 [0.30]). Persistence at 12 months was 25.9% and 12.0%, respectively. Lung function, clinical remission, quality of life, and safety outcomes were not reported in any study. CONCLUSIONS: This brief communication reports a systematic review that identified few sources of SITT or MITT in US patients with asthma. Although inclusion of observational studies can result in reporting/selection bias, we identified greater clinical benefits with triple therapies versus dual therapies.
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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 | 0.043 | 0.122 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.016 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".