M13 Antibiotic and systemic corticosteroid use in patients with chronic obstructive pulmonary disease and type 2 inflammation receiving dupilumab
Bibliographic record
Abstract
Introduction and Objectives Systemic corticosteroids (SCS) and antibiotics are often co-prescribed for chronic obstructive pulmonary disease (COPD) exacerbations. However, prolonged use can be associated with adverse events. In the BOREAS and NOTUS trials, dupilumab reduced exacerbations and improved lung function in patients with COPD and type 2 inflammation. This post hoc analysis evaluated whether dupilumab reduced SCS and antibiotic use in patients from BOREAS and NOTUS. Methods BOREAS (NCT03930732) and NOTUS (NCT04456673), phase 3, randomized, placebo-controlled trials, enrolled patients with COPD and type 2 inflammation (screening blood eosinophil counts ≥300 cells/µL) on triple therapy. Patients received add-on dupilumab or placebo for 52 weeks. Endpoints: mean SCS and antibiotic intake duration and adjusted annualized SCS and antibiotic courses for patients with ≥1 moderate or severe exacerbation during the treatment period. Results Among patients with ≥1 moderate or severe exacerbation during the 52-week treatment period (dupilumab: n=338; placebo: n=394), mean (SD) SCS intake duration was 16.1 (22.1) and 22.2 (34.1) days for dupilumab and placebo, respectively; mean antibiotic intake duration was 23.0 (49.2) and 24.8 (49.4) days, respectively. In these patients, dupilumab vs placebo reduced the annualized number of total SCS courses by 20% (relative risk vs placebo of 0.80 [95% CI: 0.71, 0.91]; P=0.0004) and antibiotic courses by 11% (relative risk vs placebo of 0.89 [95% CI: 0.79, 1.00]; P=0.058). For patients using SCS for ≥1 severe exacerbation, mean (SD) SCS intake duration was 23.5 (21.3) and 34.9 (26.4) days for dupilumab and placebo, respectively; antibiotic intake duration was 17.8 (13.8) and 21.3 (20.0) days, respectively. In these patients, dupilumab vs placebo reduced the annualized number of SCS courses by 63% (relative risk vs placebo: 0.37 [0.19, 0.72]; P=0.0033) and of antibiotic courses by 62% (relative risk vs placebo: 0.38 [0.20, 0.74]; P=0.0043). Conclusions In BOREAS and NOTUS, dupilumab compared with placebo significantly reduced the number of exacerbations. In the subgroup of patients who experienced exacerbations during the treatment period, dupilumab compared with placebo reduced the cumulative number of days of exposure to SCS or antibiotics and reduced the number of SCS and antibiotic courses, regardless of exacerbation severity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".