Cluster analysis and clinical asthma phenotypes

Pranab Haldar, Ian D. Pavord, Dominic E. Shaw, Michael A. Berry, Michael Thomas, Christopher E. Brightling, Andrew I. Wardlaw, Ruth H. Green

Research output: Contribution to journalArticle

1611 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)218-224
Number of pages7
JournalAmerican Journal of Respiratory and Critical Care Medicine
Issue number3
Publication statusPublished - 1 Aug 2008


  • taxonomy
  • corticosteroid response
  • multivariate classification
  • randomized controlled-trial
  • exhaled nitric-oxide
  • management
  • adults


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