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Exacerbation Reduction in Patients With Asthma Following Initiation of Fluticasone Furoate/Umeclidinium/Vilanterol (FF/UMEC/VI) in the United States

2025· article· en· W4410273746 on OpenAlexaff
Stephen G. Noorduyn, Alan P. Baptist, Guillaume Germain, J. Klimek, François Laliberté, Robert C. Schell, Sergio Forero-Schwanhaeuser, Abigail Moore, Rosirene Paczkowski

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicRespiratory and Cough-Related Research
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsMedicineFluticasone propionateAsthmaFluticasoneInternal medicineExacerbationPharmacologyAnesthesia

Abstract

fetched live from OpenAlex

Abstract Rationale: In the United States (US), up to 50% of patients with asthma remain uncontrolled despite adherence to inhaled corticosteroid/long-acting β2-agonist (ICS/LABA) dual therapy, requiring escalation to triple therapy.Although the efficacy of fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) triple therapy has been demonstrated in clinical trials, real-world evidence on the clinical and economic benefits is sparse.This study evaluated the impact of FF/UMEC/VI on patients with asthma previously on ICS/LABA. Methods: This was a retrospective, longitudinal, pre-post claims study using Medicaid, commercial, and Medicare insurance data from the Komodo Health database. Data were collected from September 9, 2019, to December 31, 2023; the index date was the first pharmacy claim for FF/UMEC/VI. Eligible patients were adults with asthma with ≥12 months of continuous insurance coverage prior to and following the index date (pre- and post-initiation periods) who received ICS/LABA for ≥30 consecutive days during the pre-initiation period. Outcomes assessed included asthma-related exacerbations, oral corticosteroid (OCS) use, short-acting beta-agonist (SABA) use, asthma-related healthcare resource utilization (HRU, emergency department [ED] visits), and asthma-related medical costs. Odds/rate ratios (ORs/RRs; 95% confidence intervals [CIs]) of asthma-related exacerbations were compared pre-initiation versus post-initiation using logistic/Poisson regression models. OCS bursts, SABA canisters, and HRU were analyzed using Poisson regression models (RRs [95% CIs]); asthma-related medical costs were compared pre-initiation versus post-initiation using mean differences from generalized linear models. Results: Of 17,959 eligible patients, mean (standard deviation) age was 50.6 (14.1) and the majority were female (68.2%, n=12,240). Odds of any asthma-related exacerbations were significantly reduced by 52% post- versus pre-initiation (OR [95% CI]: 0.48 [0.46, 0.50], p<0.001); rates were reduced by 38% (RR [95% CI]: 0.62 [0.61, 0.64], p<0.001) (Figure). Rates of OCS bursts were 30% lower (RR [95% CI]: 0.70 [0.69, 0.72], p<0.001), SABA use 18% lower (RR [95% CI]: 0.82 [0.81, 0.83], p<0.001), asthma-related ED visits 39% lower (RR [95% CI]: 0.61 [0.58, 0.64], p<0.001) (Figure), and asthma-related medical costs 46% lower (mean difference [95% CI]: −$1115 [−$1771, −$459], p<0.001) post- versus pre-initiation. Conclusions: Significant reductions in asthma-related exacerbations, as well as lower OCS and SABA use, and reductions in asthma-related ED visits and medical costs were associated with the post-initiation period of FF/UMEC/VI treatment compared with the pre-initiation period. This provides novel, real-world evidence of the benefits of escalation to FF/UMEC/VI from ICS/LABA therapy in patients with asthma in the US, helping to inform treatment decisions in real-world clinical practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.326
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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