The prevalence and disease burden of severe eosinophilic asthma in Japan
- PMID: 30822174
- DOI: 10.1080/02770903.2018.1534967
The prevalence and disease burden of severe eosinophilic asthma in Japan
Abstract
Background: There are limited data on the prevalence and burden of severe eosinophilic asthma (SEA) both in Japan and globally. This study aimed to assess the prevalence and burden of SEA in Japan. Methods: This study was a retrospective, observational cohort analysis using health records or health insurance claims from patients with severe asthma treated at Kyoto University Hospital. The primary outcome was the prevalence of SEA, defined as a baseline blood eosinophil count ≥300 cells/μL. Secondary outcomes included frequency and risk factors of asthma exacerbations, and asthma-related healthcare resource utilization and costs. Results: Overall, 217 patients with severe asthma were included; 160 (74%) had eosinophil assessments. Of these, 97cases (61%), 54cases (34%), and 33cases (21%) had a blood eosinophil count ≥150, ≥300, and ≥500 cells/μL, respectively. Proportion of SEA was 34%. Blood eosinophil count was not associated with a significantly increased frequency of exacerbations. In the eosinophilic group, lower % forced expiratory volume in 1 second and higher fractional exhaled nitric oxide were predictive risk factors, while the existence of exacerbation history was a predictive risk factor for asthma exacerbations in the non-eosinophilic group. Severe asthma management cost was estimated as ¥357,958/patient-year, and asthma exacerbations as ¥26,124/patient-year. Conclusions: Approximately, one-third of patients with severe asthma in Japan have SEA. While risk factors for exacerbations differed between SEA and severe non-eosinophilic asthma, both subgroups were associated with substantial disease and economic burden. From subgroup analysis, blood eosinophil counts could be an important consideration in severe asthma management.
Keywords: Epidemiology; asthma management cost; exacerbation; healthcare resource utilization; predictive risk factor.
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