Phenotypes of asthma in low-income children and adolescents: cluster analysis

ABSTRACT Objective: Studies characterizing asthma phenotypes have predominantly included adults or have involved children and adolescents in developed countries. Therefore, their applicability in other populations, such as those of developing countries, remains indeterminate. Our objective was to...

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Main Authors: Anna Lucia Barros Cabral, Andrey Wirgues Sousa, Felipe Augusto Rodrigues Mendes, Celso Ricardo Fernandes de Carvalho
Format: Article
Language:English
Published: Sociedade Brasileira de Pneumologia e Tisiologia
Series:Jornal Brasileiro de Pneumologia
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-37132017005001102&lng=en&tlng=en
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author Anna Lucia Barros Cabral
Andrey Wirgues Sousa
Felipe Augusto Rodrigues Mendes
Celso Ricardo Fernandes de Carvalho
author_facet Anna Lucia Barros Cabral
Andrey Wirgues Sousa
Felipe Augusto Rodrigues Mendes
Celso Ricardo Fernandes de Carvalho
author_sort Anna Lucia Barros Cabral
collection DOAJ
description ABSTRACT Objective: Studies characterizing asthma phenotypes have predominantly included adults or have involved children and adolescents in developed countries. Therefore, their applicability in other populations, such as those of developing countries, remains indeterminate. Our objective was to determine how low-income children and adolescents with asthma in Brazil are distributed across a cluster analysis. Methods: We included 306 children and adolescents (6-18 years of age) with a clinical diagnosis of asthma and under medical treatment for at least one year of follow-up. At enrollment, all the patients were clinically stable. For the cluster analysis, we selected 20 variables commonly measured in clinical practice and considered important in defining asthma phenotypes. Variables with high multicollinearity were excluded. A cluster analysis was applied using a twostep agglomerative test and log-likelihood distance measure. Results: Three clusters were defined for our population. Cluster 1 (n = 94) included subjects with normal pulmonary function, mild eosinophil inflammation, few exacerbations, later age at asthma onset, and mild atopy. Cluster 2 (n = 87) included those with normal pulmonary function, a moderate number of exacerbations, early age at asthma onset, more severe eosinophil inflammation, and moderate atopy. Cluster 3 (n = 108) included those with poor pulmonary function, frequent exacerbations, severe eosinophil inflammation, and severe atopy. Conclusions: Asthma was characterized by the presence of atopy, number of exacerbations, and lung function in low-income children and adolescents in Brazil. The many similarities with previous cluster analyses of phenotypes indicate that this approach shows good generalizability.
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spelling doaj.art-1962303c9496479d94059b7598cadc282022-12-21T18:20:27ZengSociedade Brasileira de Pneumologia e TisiologiaJornal Brasileiro de Pneumologia1806-3756010.1590/s1806-37562016000000039S1806-37132017005001102Phenotypes of asthma in low-income children and adolescents: cluster analysisAnna Lucia Barros CabralAndrey Wirgues SousaFelipe Augusto Rodrigues MendesCelso Ricardo Fernandes de CarvalhoABSTRACT Objective: Studies characterizing asthma phenotypes have predominantly included adults or have involved children and adolescents in developed countries. Therefore, their applicability in other populations, such as those of developing countries, remains indeterminate. Our objective was to determine how low-income children and adolescents with asthma in Brazil are distributed across a cluster analysis. Methods: We included 306 children and adolescents (6-18 years of age) with a clinical diagnosis of asthma and under medical treatment for at least one year of follow-up. At enrollment, all the patients were clinically stable. For the cluster analysis, we selected 20 variables commonly measured in clinical practice and considered important in defining asthma phenotypes. Variables with high multicollinearity were excluded. A cluster analysis was applied using a twostep agglomerative test and log-likelihood distance measure. Results: Three clusters were defined for our population. Cluster 1 (n = 94) included subjects with normal pulmonary function, mild eosinophil inflammation, few exacerbations, later age at asthma onset, and mild atopy. Cluster 2 (n = 87) included those with normal pulmonary function, a moderate number of exacerbations, early age at asthma onset, more severe eosinophil inflammation, and moderate atopy. Cluster 3 (n = 108) included those with poor pulmonary function, frequent exacerbations, severe eosinophil inflammation, and severe atopy. Conclusions: Asthma was characterized by the presence of atopy, number of exacerbations, and lung function in low-income children and adolescents in Brazil. The many similarities with previous cluster analyses of phenotypes indicate that this approach shows good generalizability.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-37132017005001102&lng=en&tlng=enAsma/classificaçãoAsma/etiologiaCriançaAdolescente.
spellingShingle Anna Lucia Barros Cabral
Andrey Wirgues Sousa
Felipe Augusto Rodrigues Mendes
Celso Ricardo Fernandes de Carvalho
Phenotypes of asthma in low-income children and adolescents: cluster analysis
Jornal Brasileiro de Pneumologia
Asma/classificação
Asma/etiologia
Criança
Adolescente.
title Phenotypes of asthma in low-income children and adolescents: cluster analysis
title_full Phenotypes of asthma in low-income children and adolescents: cluster analysis
title_fullStr Phenotypes of asthma in low-income children and adolescents: cluster analysis
title_full_unstemmed Phenotypes of asthma in low-income children and adolescents: cluster analysis
title_short Phenotypes of asthma in low-income children and adolescents: cluster analysis
title_sort phenotypes of asthma in low income children and adolescents cluster analysis
topic Asma/classificação
Asma/etiologia
Criança
Adolescente.
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-37132017005001102&lng=en&tlng=en
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