Identification of asthma phenotypes in a tertiary care medical center.

BACKGROUND: Asthma affects 5% to 10% of the population and its severity is assessed using 4 parameters: lung function, symptom frequency, rescue inhaler use, and number of asthma exacerbations. Asthma is increasingly recognized as a clinical syndrome rather than a single disease. However, the current classification system fails to reflect the heterogeneous characteristics of the disease.
METHODS: A retrospective chart review of 139 patients with mild, moderate, and severe persistent asthma was performed. Variables including baseline and maximal forced expiratory volume over first second (percent predicted), and age of asthma onset were used to classify patients.
RESULTS: This yielded 5 clusters similar to Severe Asthma Research Program (SARP). Subjects in cluster 1 (n = 32) and cluster 2 (n = 47) had early-onset atopic asthma and reduced lung function but differed in medication requirement and health care utilization. Cluster 3 (n = 32) consisted of older obese women with late-onset asthma, less atopy, and mildly reduced forced expiratory volume over first second. Members of cluster 4 (n = 20) and cluster 5 (n = 8) had atopic asthma with severe obstruction but differed in bronchodilator response, age of onset, and oral corticosteroid use. Compared with SARP, our subjects were older, had a higher percentage of African Americans and obesity, and less severe asthma (P < 0.05). The observed clusters differed from SARP clusters in the following: (1) more frequent asthma exacerbations and medication use among cluster 1 and cluster 2; (2) lower medication use in cluster 3 and cluster 4; (3) although total health care utilization was similar, there were fewer emergency department visits in cluster 3 (P < 0.05).
CONCLUSIONS: The SARP algorithm may be used to classify diverse asthmatic populations into a clinically reproducible phenotypic cluster.