Published ahead of print on May 14, 2008, doi:10.1164/rccm.200711-1754OC
Am. J. Respir. Crit. Care Med., Volume 178, Number 3, August 2008, 218-224
A more recent version of this article appeared on August 1, 2008
Submitted on November 28, 2007
Accepted on May 14, 2008
Cluster Analysis and Clinical Asthma Phenotypes
Pranab Haldar1*, Ian D Pavord1, Dominic E Shaw1, Michael A Berry1, Michael Thomas2, Christopher E Brightling1, Andrew J Wardlaw1, and Ruth H Green1
1 Institute for Lung Health, Glenfield Hospital, Leicester, United Kingdom,
2 Department of General Practice, University of Aberdeen, Aberdeen, United Kingdom
* To whom correspondence should be addressed. E-mail: ph62{at}le.ac.uk.
Rationale: Heterogeneity in asthma expression is multidimensional, including variability in clinical,
physiological and pathological 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 months) between clusters in a third population of 68 subjects with predominantly refractory asthma, clustered at entry into a randomised trial comparing a strategy of minimising eosinophilic inflammation (inflammation guided strategy) with standard care.
Results: Two clusters (early onset atopic and obese, non-eosinophilic) were common to both asthma populations. Two clusters characterised 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/year, p=0.002] and a dose reduction of inhaled corticosteroid in the symptom predominant cluster (mean difference 1829µg beclomethasone equivalent/ day (95% CI 307 - 3349 µg) p=0.02).
Conclusions: Cluster analysis offers a novel multidimensional approach for identifying asthma phenotypes
that exhibit differences in clinical response to treatment algorithms.
Key words: taxonomy, corticosteroid response, multivariate classification
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