Effects of Inhaled Corticosteroid/Long-Acting β2-Agonist Combination on the Airway Microbiome of Patients with Chronic Obstructive Pulmonary Disease: A Randomized Controlled Clinical Trial (DISARM)
Bibliographic record
Abstract
Abstract Rationale Inhaled corticosteroids (ICS) are commonly prescribed with long-acting β2-agonists (LABA) in chronic obstructive pulmonary disease (COPD). To date, the effects of ICS therapy on the airway microbiome in COPD are unknown. Objectives To determine the effects of ICS/LABA on the airway microbiome of patients with COPD. Methods Clinically stable patients with COPD were enrolled into a 4-week run-in period during which ICS was discontinued and all participants were placed on formoterol (Form) 12 μg twice daily (BID). The participants were then randomized to budesonide/formoterol (Bud + Form; 400/12 μg BID), fluticasone/salmeterol (Flu + Salm; 250/50 μg BID), or formoterol only (12 μg BID) for 12 weeks. Participants underwent bronchoscopy before and after the 12-week treatment period. The primary endpoint was the comparison of changes in the airway microbiome over the trial period between the ICS/LABA and LABA-only groups. Measurements and Main Results Sixty-three participants underwent randomization: Bud + Form (n = 20), Flu + Salm (n = 22), and Form (n = 21) groups; 56 subjects completed all visits. After the treatment period, changes in α-diversity were significantly different across groups, especially between Flu + Salm and Form groups (Δrichness: P = 0.02; ΔShannon index: P = 0.03). Longitudinal differential abundance analyses revealed more pronounced microbial shifts from baseline in the fluticasone (vs. budesonide or formoterol only) group. Conclusions Fluticasone-based ICS/LABA therapy modifies the airway microbiome in COPD, leading to a relative reduction in α-diversity and a greater number of bacterial taxa changes. These data may have implications in patients who develop pneumonia on ICS. Clinical trial registered with www.clinicaltrials.gov(NCT02833480).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".