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 mug beclomethasone equivalent/d [95% confidence interval, 307-3,349 mug]; P = 0.02). CONCLUSIONS: Cluster analysis offers a novel multidimensional approach for identifying asthma phenotypes that exhibit differences in clinical response to treatment algorithms.
RCT Entities:
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 mug beclomethasone equivalent/d [95% confidence interval, 307-3,349 mug]; P = 0.02). CONCLUSIONS: Cluster analysis offers a novel multidimensional approach for identifying asthma phenotypes that exhibit differences in clinical response to treatment algorithms.
Authors: Jane R Smith; Sue Mildenhall; Michael Noble; Miranda Mugford; Lee Shepstone; Brian D W Harrison Journal: J Asthma Date: 2005 Jul-Aug Impact factor: 2.515
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Authors: W Gerald Teague; Brenda R Phillips; John V Fahy; Sally E Wenzel; Anne M Fitzpatrick; Wendy C Moore; Annette T Hastie; Eugene R Bleecker; Deborah A Meyers; Stephen P Peters; Mario Castro; Andrea M Coverstone; Leonard B Bacharier; Ngoc P Ly; Michael C Peters; Loren C Denlinger; Sima Ramratnam; Ronald L Sorkness; Benjamin M Gaston; Serpil C Erzurum; Suzy A A Comhair; Ross E Myers; Joe Zein; Mark D DeBoer; Anne-Marie Irani; Elliot Israel; Bruce Levy; Juan Carlos Cardet; Wanda Phipatanakul; Jonathan M Gaffin; Fernando Holguin; Merritt L Fajt; Shean J Aujla; David T Mauger; Nizar N Jarjour Journal: J Allergy Clin Immunol Pract Date: 2017-08-31
Authors: Edward Zoratti; Suzanne Havstad; Ganesa Wegienka; Charlotte Nicholas; Kevin R Bobbitt; Kimberley J Woodcroft; Dennis R Ownby; Christine Cole Johnson Journal: Ann Allergy Asthma Immunol Date: 2014-05-05 Impact factor: 6.347