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• W2094537145 abstract "BackgroundCross-sectional severe asthma cluster analysis identified different phenotypes. We tested the hypothesis that these clusters will follow different courses.ObjectiveWe aimed to identify which asthma outcomes are specific and coherently associated with these different phenotypes in a prospective longitudinal cohort.MethodsIn a longitudinal cohort of 112 patients with severe asthma, the 5 Severe Asthma Research Program (SARP) clusters were identified by means of algorithm application. Because patients of the present cohort all had severe asthma compared with the SARP cohort, homemade clusters were identified and also tested. At the subsequent visit, we investigated several outcomes related to asthma control at 1 year (6-item Asthma Control Questionnaire [ACQ-6], lung function, and medication requirement) and then recorded the 3-year exacerbations rate and time to first exacerbation.ResultsThe SARP algorithm discriminated the 5 clusters at entry for age, asthma duration, lung function, blood eosinophil measurement, ACQ-6 scores, and diabetes comorbidity. Four homemade clusters were mostly segregated by best ever achieved FEV1 values and discriminated the groups by a few clinical characteristics. Nonetheless, all these clusters shared similar asthma outcomes related to asthma control as follows. The ACQ-6 score did not change in any cluster. Exacerbation rate and time to first exacerbation were similar, as were treatment requirements.ConclusionSevere asthma phenotypes identified by using a previously reported cluster analysis or newly homemade clusters do not behave differently concerning asthma control–related outcomes, which are used to assess the response to innovative therapies. This study demonstrates a potential limitation of the cluster analysis approach in the field of severe asthma. Cross-sectional severe asthma cluster analysis identified different phenotypes. We tested the hypothesis that these clusters will follow different courses. We aimed to identify which asthma outcomes are specific and coherently associated with these different phenotypes in a prospective longitudinal cohort. In a longitudinal cohort of 112 patients with severe asthma, the 5 Severe Asthma Research Program (SARP) clusters were identified by means of algorithm application. Because patients of the present cohort all had severe asthma compared with the SARP cohort, homemade clusters were identified and also tested. At the subsequent visit, we investigated several outcomes related to asthma control at 1 year (6-item Asthma Control Questionnaire [ACQ-6], lung function, and medication requirement) and then recorded the 3-year exacerbations rate and time to first exacerbation. The SARP algorithm discriminated the 5 clusters at entry for age, asthma duration, lung function, blood eosinophil measurement, ACQ-6 scores, and diabetes comorbidity. Four homemade clusters were mostly segregated by best ever achieved FEV1 values and discriminated the groups by a few clinical characteristics. Nonetheless, all these clusters shared similar asthma outcomes related to asthma control as follows. The ACQ-6 score did not change in any cluster. Exacerbation rate and time to first exacerbation were similar, as were treatment requirements. Severe asthma phenotypes identified by using a previously reported cluster analysis or newly homemade clusters do not behave differently concerning asthma control–related outcomes, which are used to assess the response to innovative therapies. This study demonstrates a potential limitation of the cluster analysis approach in the field of severe asthma." @default.
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• W2094537145 date "2014-11-01" @default.
• W2094537145 modified "2023-10-14" @default.
• W2094537145 title "Prognostic value of cluster analysis of severe asthma phenotypes" @default.
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• W2094537145 doi "https://doi.org/10.1016/j.jaci.2014.04.038" @default.
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