Comparative Effectiveness of Initial LAMA versus LABA in COPD: Real-World Cohort Study
Bibliographic record
Abstract
The Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendations for the initial bronchodilator to use in newly diagnosed chronic obstructive pulmonary disease (COPD) are based on trials of patients with longstanding disease and treatment. We compared the real world effectiveness of initial treatment with long-acting muscarinic agents (LAMA) versus long-acting beta2-agonists (LABA) on the incidence of exacerbations in newly diagnosed patients. We identified a cohort of patients with COPD, new users of a LAMA or LABA (not combined with an inhaled corticosteroid (ICS)) during 2002–2018, age 50 or older, from the UK’s CPRD database, and followed for one year. The hazard ratio (HR) of exacerbation estimated using the Cox regression model, weighted by fine stratification of propensity scores. The cohort included 40,538 initiators of LAMA and 10,680 of LABA. The adjusted hazard ratio (HR) of a first moderate or severe exacerbation comparing LAMA with LABA initiation was 0.96 (95% CI: 0.90–1.02), while for severe exacerbation it was 0.92 (95% CI: 0.75–1.12). The incidence of exacerbation on LAMA was significantly lower than on LABA (HR 0.88; 95% CI: 0.80–0.96) among patients with a prior exacerbation, and the HR of exacerbation increased with percent predicted FEV1. This study in the real world clinical setting of COPD treatment found that using a LAMA or a LABA (no ICS) as the initial bronchodilator is generally as effective at reducing exacerbation incidence and frequency. However, a LAMA may be more effective in patients with prior exacerbations, which supports the GOLD recommendations for newly diagnosed COPD. The role of airway obstruction on the effectiveness of bronchodilators warrants further investigation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".