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Cluster Analysis and Clinical Asthma Phenotypes.
Haldar, Pranab 1,*; Pavord, Ian D. 1,*; Shaw, Dominic E. 1; Berry, Michael A. 1; Thomas, Michael 2; Brightling, Christopher E. 1; Wardlaw, Andrew J. 1; Green, Ruth H. 1,*
[Miscellaneous] American Journal of Respiratory & Critical Care Medicine. 178(3):218-224, August 1, 2008.

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Rationale: Heterogeneity in asthma expression is multidimensional, including variability in clinical, physiologic, and pathologic parameters. Classification requires consideration of these disparate domains in a unified model.

Objectives: To explore the application of a multivariate mathematical technique, k-means cluster analysis, for identifying distinct phenotypic groups.

Methods: We performed k-means cluster analysis in three independent asthma populations. Clusters of a population managed in primary care (n = 184) with predominantly mild to moderate disease, were compared with a refractory asthma population managed in secondary care (n = 187). We then compared differences in asthma outcomes (exacerbation frequency and change in corticosteroid dose at 12 mo) between clusters in a third population of 68 subjects with predominantly refractory asthma, clustered at entry into a randomized trial comparing a strategy of minimizing eosinophilic inflammation (inflammation-guided strategy) with standard care.

Measurements and Main Results: Two clusters (early-onset atopic and obese, noneosinophilic) were common to both asthma populations. Two clusters characterized by marked discordance between symptom expression and eosinophilic airway inflammation (early-onset symptom predominant and late-onset inflammation predominant) were specific to refractory asthma. Inflammation-guided management was superior for both discordant subgroups leading to a reduction in exacerbation frequency in the inflammation-predominant cluster (3.53 [SD, 1.18] vs. 0.38 [SD, 0.13] exacerbation/patient/yr, P = 0.002) and a dose reduction of inhaled corticosteroid in the symptom-predominant cluster (mean difference, 1,829 [mu]g beclomethasone equivalent/d [95% confidence interval, 307-3,349 [mu]g]; P = 0.02).

Conclusions: Cluster analysis offers a novel multidimensional approach for identifying asthma phenotypes that exhibit differences in clinical response to treatment algorithms.