Reduction of Exacerbations According to Type 2 Inflammatory Biomarkers With Dupilumab Treatment in Patients With Chronic Obstructive Pulmonary Disease (COPD)
Bibliographic record
Abstract
Abstract RATIONALE: Type 2 (T2) inflammatory biomarkers, such as blood eosinophil counts (BEC) or fractional exhaled nitric oxide (FeNO) may help to predict response to therapy. Dupilumab, a human monoclonal antibody, blocks interleukin-4/13 signaling, key and central drivers of T2 inflammation. In BOREAS and NOTUS, add-on dupilumab 300 mg q2w vs placebo reduced moderate-or-severe exacerbation rates and T2 biomarkers and improved lung function in patients with COPD and T2 inflammation. Safety was consistent with the known dupilumab profile. This post hoc analysis of BOREAS and NOTUS explored the predictive value of baseline BEC and FeNO, for response to dupilumab treatment in patients with COPD and T2 inflammation. METHODS: BOREAS (NCT03930732) and NOTUS (NCT04456673), phase 3, randomized, placebo-controlled trials, enrolled 1874 patients (40-85 years) with moderate-to-severe COPD and T2 inflammation (screening BEC ≥300 cells/μL) on triple therapy (inhaled corticosteroids, long-acting β2-agonists, and long-acting muscarinic antagonists). Patients received dupilumab 300 mg q2w or placebo for 52 weeks. The annualized moderate-or-severe exacerbation rates over a range of T2 biomarkers (baseline BEC and FeNO) was evaluated using a negative binominal model which included treatment group, study, region, inhaled corticosteroid dose, smoking status at screening, baseline disease severity, number of moderate-or-severe COPD exacerbation events within one year prior to the study and a first-degree fractional polynomial transformation of the biomarker as a continuous variable, and the biomarker-by-treatment interaction. RESULTS: Reductions in annual exacerbation rates were observed over a range of baseline BEC (estimate [95% CI] – dupilumab: 0.57 [0.51, 0.63] for 300 cells/μL to 0.58 [0.51, 0.65] for 900 cells/μL; placebo: 0.81 [0.73, 0.89] for 300 cells/μL to 0.81 [0.73, 0.89] for 900 cells/μL). Reduction in treatment rate ratio for exacerbations was observed with increasing baseline FeNO levels from 0.69 (0.60, 0.80) (FeNO ≥20 ppb) to 0.56 (0.46, 0.69) (FeNO ≥40 ppb), indicating a significant predictive value (P=0.006) for treatment by baseline FeNO interaction unlike baseline BEC (P=0.087). Reductions in annual exacerbation rates were also observed regardless of baseline IgE levels (estimate [95% CI] – dupilumab: 0.56 [0.50, 0.63] for IgE 100 IU/mL to 0.53 [0.44, 0.63] for IgE 1,000 IU/mL; placebo: 0.82 [0.74, 0.90] for IgE 100 IU/mL to 0.78 [0.67, 0.92] for IgE 1,000 IU/mL). CONCLUSION: In BOREAS and NOTUS, dupilumab reduced exacerbations compared to placebo independently of baseline BEC and IgE. Baseline FeNO levels were associated with a greater response to intervention with dupilumab, implying utility to manage T2 inflammatory COPD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".