Association of Long-acting Bronchodilator Use with Cardiovascular Adverse Events in Patients with Asthma: A Population-based Cohort Study
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1Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, China.
Background:
A recent meta-analysis of randomized controlled trials found that long-acting bronchodilator use was associated with cardiovascular adverse events (AEs) leading to treatment discontinuation in asthma, although the certainty of evidence was low.
Objective:
To evaluate the cardiovascular safety of long-acting bronchodilators in a real-world asthma population.
Methods:
This population-based cohort study used UK Biobank data from patients with asthma (2006-2010). Exposure was categorized into three mutually exclusive groups: LABA alone, LAMA alone, or combined LABA/LAMA therapy. The primary outcome was a composite of cardiovascular AEs, including coronary heart disease, arrhythmia, hypertension, heart failure, and cerebrovascular disease. Cox proportional hazards models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Pre-specified subgroup analyses and interaction tests were performed.
Results:
A total of 14,677 patients were included (median follow-up 14.68 years). Long-acting bronchodilator use was associated with an increased risk of total cardiovascular AEs (HR: 1.08, 95% CI: 1.02-1.15). This was primarily driven by arrhythmia (HR: 1.23, 95% CI: 1.06-1.42), heart failure (HR: 1.30, 95% CI: 1.02-1.65), and cerebrovascular disease (HR: 1.35, 95% CI: 1.02-1.79). When stratified by regimen, the association was confined to the LABA group (HR: 1.07, 95% CI: 1.001-1.13) and the combined group (HR: 1.32, 95% CI: 1.09-1.59). The association was more pronounced in patients using short-acting bronchodilators (HR: 1.15, 95% CI: 1.07-1.23; interaction P = 0.004).
Conclusions:
The observed positive associations are more plausibly attributable to confounding rather than to a causal drug effect. Future research should prioritize new-user designs to clarify whether these signals are drug-specific or confounded by disease severity.
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