Dual LABA/LAMA Therapy versus LABA or LAMA Monotherapy for Chronic Obstructive Pulmonary Disease. A Systematic Review and Meta-analysis in Support of the American Thoracic Society Clinical Practice Guideline
Bibliographic record
Abstract
Abstract Rationale There is uncertainty on the optimal first-line therapy for symptomatic chronic obstructive pulmonary disease (COPD). Long-acting β2-receptor agonists (LABAs) and long-acting muscarinic antagonists (LAMAs) have long been mainstays of treatment, though it is still not clear if dual therapy with LABA/LAMA is superior to monotherapy for symptomatic COPD. Objectives To clarify the evidence landscape, we conducted a systematic review to answer the following question: in patients with COPD who complain of dyspnea and/or exercise intolerance, is LABA/LAMA combination therapy more effective and equally safe compared with LABA or LAMA monotherapy? Methods A search of Medline, EMBASE, and the Cochrane Library databases was conducted by a medical librarian for randomized controlled trials enrolling patients with COPD who complain of dyspnea and/or exercise intolerance that compare LABA/LAMA combination therapy to LABA or LAMA monotherapy. A systematic approach was used to screen, abstract, and critically appraise the emerging study evidence. The Grading of Recommendations Assessment, Development, and Evaluation method was applied to rate the certainty and quality of the evidence. Results A total of 24 studies were eligible for inclusion (n = 45,441). Pairwise random-effects meta-analysis revealed reductions in hospital admissions (11% reduction; P < 0.01) and acute exacerbations of COPD (20% reduction; P < 0.002), all in favor of LABA/LAMA dual therapy. Although there is reduced dyspnea (0.10 standardized mean difference; P < 0.001) and improved health-related quality of life (−0.13 standardized mean difference; P < 0.001), both values did not meet a clinical meaningful difference threshold. LABA/LAMA combination therapy showed no difference in treatment-emergent adverse effects (risk ratio, 0.99; P = 0.34) when compared with either LAMA or LABA monotherapy. Conclusions Based on the reviewed evidence, in patients with symptomatic COPD who complain of dyspnea and/or exercise intolerance, dual LABA/LAMA therapy is superior to either LABA or LAMA monotherapy based on the reduced risk of exacerbations and hospitalizations.
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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 | 0.031 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.032 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".