The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2018
Identification of chronic obstructive pulmonary disease subgroups in 13 Asian cities.
СтатьяМногоцентровое исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Kim W J, Gupta V, Nishimura M, Makita H, Idolor L, Roa C, Loh L-C, Ong C-K, Wang J-S, Boonsawat W, Gunasekera K D, Madegedara D, Kuo H-P, Wang C-H, Wang C, Yang T, Lin Y-X, Ko F W S, Hui D S C, Lan L T T, Vu Q T T, Bhome A B, Ng A, Seo J B, Lee B Y, Lee J S, Oh Y-M, Lee S-D
Аннотация
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition that can differ in its clinical manifestation, structural changes and response to treatment.
OBJECTIVE: To identify subgroups of COPD with distinct phenotypes, evaluate the distribution of phenotypes in four related regions and calculate the 1-year change in lung function and quality of life according to subgroup.
METHODS: Using clinical characteristics, we performed factor analysis and hierarchical cluster analysis in a cohort of 1676 COPD patients from 13 Asian cities. We compared the 1-year change in forced expiratory volume in one second (FEV1), modified Medical Research Council dyspnoea scale score, St George's Respiratory Questionnaire (SGRQ) score and exacerbations according to subgroup derived from cluster analysis.
RESULTS: Factor analysis revealed that body mass index, Charlson comorbidity index, SGRQ total score and FEV1 were principal factors. Using these four factors, cluster analysis identified three distinct subgroups with differing disease severity and symptoms. Among the three subgroups, patients in subgroup 2 (severe disease and more symptoms) had the most frequent exacerbations, most rapid FEV1 decline and greatest decline in SGRQ total score.
CONCLUSION: Three subgroups with differing severities and symptoms were identified in Asian COPD subjects.
OBJECTIVE: To identify subgroups of COPD with distinct phenotypes, evaluate the distribution of phenotypes in four related regions and calculate the 1-year change in lung function and quality of life according to subgroup.
METHODS: Using clinical characteristics, we performed factor analysis and hierarchical cluster analysis in a cohort of 1676 COPD patients from 13 Asian cities. We compared the 1-year change in forced expiratory volume in one second (FEV1), modified Medical Research Council dyspnoea scale score, St George's Respiratory Questionnaire (SGRQ) score and exacerbations according to subgroup derived from cluster analysis.
RESULTS: Factor analysis revealed that body mass index, Charlson comorbidity index, SGRQ total score and FEV1 were principal factors. Using these four factors, cluster analysis identified three distinct subgroups with differing disease severity and symptoms. Among the three subgroups, patients in subgroup 2 (severe disease and more symptoms) had the most frequent exacerbations, most rapid FEV1 decline and greatest decline in SGRQ total score.
CONCLUSION: Three subgroups with differing severities and symptoms were identified in Asian COPD subjects.