Type 2 Inflammatory Biomarkers and Lung Function Improvement in Patients With Chronic Obstructive Pulmonary Disease (COPD) Receiving Placebo Therapy
Bibliographic record
Abstract
Abstract RATIONALE: Type 2 inflammation in COPD is characterized by elevated blood eosinophil counts. In BOREAS and NOTUS, add-on dupilumab vs placebo reduced exacerbation rates and improved lung function in patients with COPD and type 2 inflammation. Safety was consistent with the known dupilumab safety profile. This post hoc analysis of pooled data from BOREAS and NOTUS assessed the predictive value of blood eosinophil counts and FeNO on lung function in patients who received placebo. METHODS: BOREAS (NCT03930732) and NOTUS (NCT04456673), both phase 3, randomized, placebo-controlled trials, enrolled 1,874 patients aged 40 to 85 years with COPD with moderate-to-severe airflow limitation and type 2 inflammation (screening blood eosinophil counts ≥300 cells/µL). Patients were randomized to dupilumab 300 mg or placebo every second week for 52 weeks. Regression analyses were conducted to investigate change in forced expiratory volume in 1 second (FEV1) from baseline to Week 52 according to blood eosinophil counts and pre-bronchodilator FeNO levels in patients with available data (N=865; subgroup 1), including former (N=654; subgroup 2) and current smokers (N=282; subgroup 3). Baseline biomarkers were log-transformed; post-bronchodilator FEV1 is reported as (r) (P-value) for lung function as well as, least square [LS] mean change from baseline to Week 52. RESULTS: Univariate regression analysis showed weak correlations between baseline blood eosinophil counts and worsening lung function in patients from subgroup 1 (r=0.029; P=0.298), subgroup 2 (r=0.035; P=0.270), and subgroup 3 (r=−0.012; P=0.782). We also observed weak correlations between baseline FeNO levels and worsening lung function in patients from subgroup 1 (r=0.094; P<0.0001), subgroup 2 (r=0.118; P<0.0001), and subgroup 3 (r=0.054; P=0.101). Changes from baseline to Week 52 showed that patients with both elevated blood eosinophil count and FeNO experienced an improvement exceeding the minimal clinically important difference (Table). CONCLUSIONS: In patients with COPD and type-2 inflammation, greater baseline blood eosinophil counts and FeNO values were associated with greater lung function improvements on placebo therapy.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".