Biological Anti-IL-5/IL-5R Therapeutics for Chronic Obstructive Pulmonary Disease (COPD) with Specific Treatable Traits: A Real-World Retrospective Analysis
Bibliographic record
Abstract
Introduction: We describe the use of anti-IL-5 monoclonal antibodies from a COPD clinic, a source other than traditional clinical trials. The objectives were to characterize the patient subgroup prescribed anti-IL-5 monoclonal antibodies and to report potential benefits. Methods: This is a retrospective case series study of 17 patients treated in a COPD subspecialty clinic. All patients had a diagnosis of COPD (post-bronchodilator FEV1/FVC <0.7) and had been prescribed an anti-IL-5 biologic for at least 8 months. Acute exacerbations of COPD (AECOPDs) were collected as reported in electronic medical records. Results: All patients (17) enrolled were treated with biologics for ≥8 months, and 13 (76%) for ≥1 year. Patients were characterized by severe disease traits, FEV1 <50% predicted, recurrent exacerbations (3.5 moderate-to-severe AECOPDs in the year before treatment), high peripheral blood eosinophil counts (≥250 cells/μL in the previous year), all on inhaled triple therapy, and only 1 patient with a diagnosis of asthma prior to smoking. There was a statistically significant decrease in the exacerbation rate compared with baseline after 8 and 12 months of anti-IL-5 treatment, respectively, yielding the equivalent of a 2-3x reduction in exacerbation rate. Absolute FEV1 decreased, and the decline in FEV1 % of predicted reached statistical significance (p<0.05); CAT score improved (p<0.05). Discussion: This real-world evidence data aligns with existing studies suggesting the potential benefit of anti-IL-5 treatment for specific patients with COPD and therefore advocates for further investigation of RCTs on the use of anti-IL-5 biologics for well-characterized patients with COPD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".