Triple Inhaler versus Dual Bronchodilator Therapy in COPD: Real-World Effectiveness on Mortality
Bibliographic record
Abstract
Randomized trials of triple therapy including an inhaled corticosteroid (ICS) for chronic obstructive pulmonary disease (COPD) reported remarkable benefits on mortality compared with dual bronchodilators, likely resulting from ICS withdrawal at randomization. We compared triple therapy with dual bronchodilator combinations on major COPD outcomes in a real-world clinical practice setting. We identified a cohort of COPD patients, age 50 or older, treated during 2002-2018, from the United Kingdom’s Clinical Practice Research Datalink. Patients initiating treatment with a long-acting muscarinic antagonist (LAMA), a long-acting beta2-agonist (LABA) and an ICS on the same day, were compared with patients initiating a LAMA and LABA, weighted by fine stratification of propensity scores. Subjects were followed-up one year for all-cause mortality, severe exacerbation and pneumonia. The cohort included 117,729 new-users of LAMA-LABA-ICS and 26,666 of LAMA-LABA. The adjusted hazard ratio (HR) of all-cause mortality with LAMA-LABA-ICS compared with LAMA-LABA was 1.17 (95% CI: 1.04-1.31) while for severe exacerbation and pneumonia it was 1.19 (1.08-1.32) and 1.29 (1.16-1.45) respectively. However, mortality was not elevated with triple therapy among patients with asthma diagnosis (HR 0.99; 95% CI: 0.74-1.34), with two or more prior exacerbations (HR 0.88; 95% CI: 0.70-1.11), and with FEV1 percent predicted >30%. In a real-world setting of COPD treatment, triple therapy initiation was not more effective than dual bronchodilators at preventing all-cause mortality and severe COPD exacerbations. Triple therapy may be unsafe among patients without prior exacerbations, in whom ICS are not recommended, with no asthma diagnosis and with very severe airflow obstruction.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".