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The identification of phenotypes of asthma has a long history, but previous classifications have not identified clinically important differences in pathology, natural history, or treatment response. Progress has accelerated recently, fueled by the development of new techniques to assess airway disease, particularly noninvasive techniques to assess airway inflammation. This article discusses evidence that a simple subdivision of patients into eosinophilic and noneosinophilic asthma is clinically important because it identifies groups with markedly different responses to corticosteroids and other drugs that manipulate the Th-2 (T-helper) pathway. All classification systems suffer from potential bias given that different disease variables are subjectively weighted. There has been increasing interest in the application of mathematical techniques such as factor analysis and cluster analysis to organize and group large amounts of interrelated data in an unbiased way. This article discusses attempts to do this in asthma and speculates on the clinical implications of this new information.

Original publication




Journal article


Semin Respir Crit Care Med

Publication Date





645 - 652


Anti-Asthmatic Agents, Asthma, Cluster Analysis, Eosinophilia, Factor Analysis, Statistical, Glucocorticoids, Humans, Inflammation, Phenotype, Th2 Cells, Treatment Outcome