TY -的T1对个性化医学airways disease: identifying clinical phenotype groups JF - European Respiratory Journal JO - Eur Respir J SP - 1033 LP - 1034 DO - 10.1183/09031936.00122811 VL - 39 IS - 4 AU - Travers, J. AU - Weatherall, M. AU - Fingleton, J. AU - Beasley, R. Y1 - 2012/04/01 UR - //www.qdcxjkg.com/content/39/4/1033.abstract N2 - To the Editors:Asthma and chronic obstructive pulmonary disease (COPD) are heterogeneous diseases [1,2]. In diagnosing a patient with asthma or COPD, an individual is thereby lumped together with other patients whose disease phenotype and response to treatment may be quite different. Doing so simplifies treatment guidelines and facilitates the application of evidence-based medicine but there is a risk that interventions that could provide benefit to certain disease subgroups are overlooked. At present, it is not known to what degree splitting of airways disease groups can lead to improved health outcomes and this question remains a focus of intense research. The approach in recent years has been to re-examine the classification of airways disease to identify disease subgroups that may respond to treatments in different ways.There have been several examples that illustrate the potential for this. It has been shown in both asthma and COPD that the response to corticosteroids can be predicted by sputum eosinophilia [3,4] and that lung volume reduction surgery is of more benefit to those with predominantly upper lobe emphysema [5].More recently, there have been attempts to explore phenotypes with methods that are less reliant on a priori assumptions about the best way to split disease categories into clinically meaningful groups. Cluster analysis is a tool that can identify subsets of patients with airways disease who have similar characteristics. We have previously used cluster analysis to identify five phenotypes of airways disease based on nine key disease variables in a sample of adults selected at random from the … ER -