Impact of Dupilumab on Type 2 Inflammatory Biomarkers in Patients With Chronic Obstructive Pulmonary Disease (COPD)
Bibliographic record
Abstract
Abstract RATIONALE: Up to 40% of patients with COPD have type 2 inflammation, indicated by elevated blood eosinophil counts. Dupilumab, a monoclonal antibody, blocks interleukin (IL)-4 and IL-13, key drivers of type 2 inflammation. In the BOREAS and NOTUS trials, dupilumab significantly reduced moderate or severe exacerbations and improved lung function in patients with COPD and type 2 inflammation. Safety was generally consistent with the known dupilumab safety profile. This post hoc analysis of pooled data assessed the impact of dupilumab on type 2 biomarkers in patients with COPD and type 2 inflammation. METHODS: BOREAS (NCT03930732) and NOTUS (NCT04456673), both phase 3, randomized, placebo-controlled trials, enrolled 1,874 patients (aged 40 to 85 years) with COPD, moderate-to-severe airflow limitation, and type 2 inflammation (blood eosinophil count ≥300 cells/L at screening). Patients were treated with dupilumab 300 mg (n = 938) or placebo (n = 936) every 2 weeks. Endpoints assessed included change from baseline to Week 52 in blood eosinophil count, fractional exhaled nitric oxide (FeNO), and IgE levels in the intention-to-treat population. All data are shown as median (Q1 to Q3). RESULTS: Baseline blood eosinophil counts were 340.0 (240.0 to 460.0) cells/μL for patients receiving dupilumab and 330.0 (230.0 to 460.0) for those on placebo. By Week 52, similar median change from baseline in blood eosinophil count was observed in the dupilumab group (−40 [-160 to 80] cells/μL [14% decrease]) and in the placebo group (-40 [-140 to 50] cells/µL [11% decrease]). Patients receiving dupilumab had baseline FeNO of 17.0 (10.0 to 29.0) ppb and those on placebo 16.0 (10.0 to 30.0) ppb. By Week 52, median change from baseline in FeNO was -3 (-13 to 10) ppb (23.3% decrease) in the dupilumab group and 0 (-7 to 4) ppb (no change) in the placebo group. Baseline IgE levels were 126.5 (46.1 to 423.0) IU/mL for patients on dupilumab and 123.0 (40.2 to 347.0) for those on placebo. Median change from baseline to Week 52 in IgE levels in dupilumab recipients was -77 (-255 to -20) IU/mL (65% decrease) and in placebo was -2 (-39 to 21) IU/mL (4% decrease). CONCLUSIONS: Overall, treatment with dupilumab resulted in reductions in type 2 inflammatory biomarkers, including serum IgE and FeNO levels over time; blood eosinophil counts remained stable, consistent with the known mechanism of action of dupilumab.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".