Dupilumab for Chronic Obstructive Pulmonary Disease: A Systematic Review
Bibliographic record
Abstract
Background/Objectives: Dupilumab was recently approved to treat eosinophilic phenotypes of chronic obstructive pulmonary disease (COPD). This systematic review aimed to collect and appraise the efficacy and safety of dupilumab to treat patients with COPD. Methods: Databases searched included Ovid Medline, Embase, Web of Science, Directory of Open Access Journals, and International Pharmaceutical Abstracts. Experimental and observational studies, including case reports/series, were eligible for inclusion. Reports were independently screened, appraised, and extracted by three investigators; disagreements were resolved through discussion and agreement. Quality appraisal was conducted using the Cochrane Risk of Bias Tool 2.0, Newcastle–Ottawa Scale, and JBI Checklist for experimental, observational, and case studies, respectively. Results: A total of 307 unique reports were identified, of which 17 were included in this systematic review. The majority (n = 11, 64.7%) of reports presented evidence from the BOREAS and NOTUS trials, the landmark trials serving as the basis for dupilumab’s approval to treat refractory eosinophilic COPD. The results from this systematic review found that dupilumab reduced exacerbations of COPD in patients treated with inhaled triple therapy and it was well tolerated. Conclusions: When added to inhaled triple therapy, dupilumab may decrease patients’ risk for acute exacerbations of COPD. Additional research is necessary to substantiate these findings for broader generalizability, including populations with non-eosinophilic COPD phenotypes.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".