THE UNIVERSITY OF BRITISH COLUMBIA

Faculty of Pharmaceutical Sciences & UBC Division of Respiratory Medicine
Respiratory Evaluation Sciences Program

Research Theme Asthma

International variation in severe exacerbation rates in patients with severe asthma

Background: Exacerbation frequency strongly influences treatment choices in patients with severe asthma.

Research question: What is the extent of the variability of exacerbations rate across countries and its implications in disease management?

Study design and methods: We retrieved data from the International Severe Asthma Registry, an international observational cohort of patients with a clinical diagnosis of severe asthma. We identified patients aged ≥18 years who did not initiate any biologics prior to baseline visit. A severe exacerbation was defined as the use of oral corticosteroids for ≥3 days or asthma-related hospitalization/emergency room visit. A series of negative binomial models were applied to estimate country-specific severe exacerbation rates during 365 days of follow-up, starting from a naïve model with country as the only variable, to an adjusted model with country as a random-effect term and patient and disease characteristics as independent variables.

Results: The final sample included 7,510 patients from 17 countries (56% from the United States), contributing to 1,939 severe exacerbations (0.27/person-year). There was large between-country variation in observed severe exacerbation rate (min: 0.04 Argentina, max:0.88 Saudi Arabia, interquartile range IQR: 0.13-0.54), which remained substantial after adjusting for patient characteristics and sampling variability (IQR: 0.16-0.39).

Interpretation: Individuals with similar patient characteristics but coming from different jurisdictions have varied severe exacerbation risks, even after controlling for patient and disease characteristics. This suggests unknown patient factors or system-level variations at play. Disease management guidelines should recognize such between-country variability. Risk prediction models that are calibrated for each jurisdiction will be needed to optimize treatment strategies.

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