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Prediction of first acute exacerbation using COPD subtypes identified by cluster analysis
PURPOSE: In patients with COPD, acute exacerbation (AE) is not only an important determinant of prognosis, but also an important factor in choosing therapeutic agents. In this study, we evaluated the usefulness of COPD subtypes identified through cluster analysis to predict the first AE. PATIENTS AN...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6607981/ https://www.ncbi.nlm.nih.gov/pubmed/31388298 http://dx.doi.org/10.2147/COPD.S205517 |
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author | Yoon, Hee-Young Park, So Young Lee, Chang Hoon Byun, Min-Kwang Na, Joo Ock Lee, Jae Seung Lee, Won-Yeon Yoo, Kwang Ha Jung, Ki-Suck Lee, Jin Hwa |
author_facet | Yoon, Hee-Young Park, So Young Lee, Chang Hoon Byun, Min-Kwang Na, Joo Ock Lee, Jae Seung Lee, Won-Yeon Yoo, Kwang Ha Jung, Ki-Suck Lee, Jin Hwa |
author_sort | Yoon, Hee-Young |
collection | PubMed |
description | PURPOSE: In patients with COPD, acute exacerbation (AE) is not only an important determinant of prognosis, but also an important factor in choosing therapeutic agents. In this study, we evaluated the usefulness of COPD subtypes identified through cluster analysis to predict the first AE. PATIENTS AND METHODS: Among COPD patients in the Korea COPD Subgroup Study (KOCOSS) cohort, 1,195 who had follow-up data for AE were included in our study. We selected seven variables for cluster analysis – age, body mass index, smoking status, history of asthma, COPD assessment test (CAT) score, post-bronchodilator (BD) FEV(1) % predicted, and diffusing capacity of carbon monoxide % predicted. RESULTS: K-means clustering identified four clusters for COPD that we named putative asthma-COPD overlap (ACO), mild COPD, moderate COPD, and severe COPD subtypes. The ACO group (n=196) showed the second-best post-BD FEV(1) (75.5% vs 80.9% [mild COPD, n=313] vs 52.4% [moderate COPD, n=345] vs 46.7% [severe COPD, n=341] predicted), the longest 6-min walking distance (424 m vs 405 m vs 389 m vs 365 m), and the lowest CAT score (12.2 vs 13.7 vs 15.6 vs 17.5) among the four groups. ACO group had greater risk for first AE compared to the mild COPD group (HR, 1.683; 95% CI, 1.175–2.410). The moderate COPD and severe COPD group HR values were 1.587 (95% CI, 1.145–2.200) and 1.664 (95% CI, 1.203–2.302), respectively. In addition, St. George’s Respiratory Questionnaire score (HR: 1.019; 95% CI, 1.014–1.024) and gastroesophageal reflux disease were independent factors associated with the first AE (HR: 1.535; 95% CI, 1.116–2.112). CONCLUSION: Our cluster analysis revealed an exacerbator subtype of COPD independent of FEV(1). Since these patients are susceptible to AE, a more aggressive treatment strategy is needed in these patients. |
format | Online Article Text |
id | pubmed-6607981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-66079812019-08-06 Prediction of first acute exacerbation using COPD subtypes identified by cluster analysis Yoon, Hee-Young Park, So Young Lee, Chang Hoon Byun, Min-Kwang Na, Joo Ock Lee, Jae Seung Lee, Won-Yeon Yoo, Kwang Ha Jung, Ki-Suck Lee, Jin Hwa Int J Chron Obstruct Pulmon Dis Original Research PURPOSE: In patients with COPD, acute exacerbation (AE) is not only an important determinant of prognosis, but also an important factor in choosing therapeutic agents. In this study, we evaluated the usefulness of COPD subtypes identified through cluster analysis to predict the first AE. PATIENTS AND METHODS: Among COPD patients in the Korea COPD Subgroup Study (KOCOSS) cohort, 1,195 who had follow-up data for AE were included in our study. We selected seven variables for cluster analysis – age, body mass index, smoking status, history of asthma, COPD assessment test (CAT) score, post-bronchodilator (BD) FEV(1) % predicted, and diffusing capacity of carbon monoxide % predicted. RESULTS: K-means clustering identified four clusters for COPD that we named putative asthma-COPD overlap (ACO), mild COPD, moderate COPD, and severe COPD subtypes. The ACO group (n=196) showed the second-best post-BD FEV(1) (75.5% vs 80.9% [mild COPD, n=313] vs 52.4% [moderate COPD, n=345] vs 46.7% [severe COPD, n=341] predicted), the longest 6-min walking distance (424 m vs 405 m vs 389 m vs 365 m), and the lowest CAT score (12.2 vs 13.7 vs 15.6 vs 17.5) among the four groups. ACO group had greater risk for first AE compared to the mild COPD group (HR, 1.683; 95% CI, 1.175–2.410). The moderate COPD and severe COPD group HR values were 1.587 (95% CI, 1.145–2.200) and 1.664 (95% CI, 1.203–2.302), respectively. In addition, St. George’s Respiratory Questionnaire score (HR: 1.019; 95% CI, 1.014–1.024) and gastroesophageal reflux disease were independent factors associated with the first AE (HR: 1.535; 95% CI, 1.116–2.112). CONCLUSION: Our cluster analysis revealed an exacerbator subtype of COPD independent of FEV(1). Since these patients are susceptible to AE, a more aggressive treatment strategy is needed in these patients. Dove 2019-06-28 /pmc/articles/PMC6607981/ /pubmed/31388298 http://dx.doi.org/10.2147/COPD.S205517 Text en © 2019 Yoon et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Yoon, Hee-Young Park, So Young Lee, Chang Hoon Byun, Min-Kwang Na, Joo Ock Lee, Jae Seung Lee, Won-Yeon Yoo, Kwang Ha Jung, Ki-Suck Lee, Jin Hwa Prediction of first acute exacerbation using COPD subtypes identified by cluster analysis |
title | Prediction of first acute exacerbation using COPD subtypes identified by cluster analysis |
title_full | Prediction of first acute exacerbation using COPD subtypes identified by cluster analysis |
title_fullStr | Prediction of first acute exacerbation using COPD subtypes identified by cluster analysis |
title_full_unstemmed | Prediction of first acute exacerbation using COPD subtypes identified by cluster analysis |
title_short | Prediction of first acute exacerbation using COPD subtypes identified by cluster analysis |
title_sort | prediction of first acute exacerbation using copd subtypes identified by cluster analysis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6607981/ https://www.ncbi.nlm.nih.gov/pubmed/31388298 http://dx.doi.org/10.2147/COPD.S205517 |
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