Cluster Analysis and Clinical Asthma Phenotypes

• Published in: American journal of respiratory and critical care medicine Vol. 178; no. 3; pp. 218 - 224
• Main Authors: Haldar, Pranab, Pavord, Ian D, Shaw, Dominic E, Berry, Michael A, Thomas, Michael, Brightling, Christopher E, Wardlaw, Andrew J, Green, Ruth H
• Format: Journal Article
• Language: English
• Published: New York, NY Am Thoracic Soc 01.08.2008; American Lung Association; American Thoracic Society
• Subjects: Adrenal Cortex Hormones - therapeutic use; Adult; Aged; Algorithms; Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy; Asthma; Asthma - classification; Asthma - drug therapy; Asthma - physiopathology; Biological and medical sciences; Chronic obstructive pulmonary disease, asthma; Classification; Cluster Analysis; Datasets; Family physicians; Female; Humans; Inflammation; Inflammation - physiopathology; Intensive care medicine; Male; Medical sciences; Middle Aged; Phenotype; Pneumology; Primary care; Prospective Studies; Steroids; Taxonomy; Lung disease; Corticosteroid; Intensive care; Respiratory disease; corticosteroid response; taxonomy; Asthma; Phenotype; Classification; Bronchus disease; Obstructive pulmonary disease; multivariate classification; Resuscitation
• ISSN: 1073-449X; 1535-4970; 1535-4970
• DOI: 10.1164/rccm.200711-1754OC

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. To explore the application of a multivariate mathematical technique, k-means cluster analysis, for identifying distinct phenotypic groups. 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. 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 mug beclomethasone equivalent/d [95% confidence interval, 307-3,349 mug]; P = 0.02). Cluster analysis offers a novel multidimensional approach for identifying asthma phenotypes that exhibit differences in clinical response to treatment algorithms.