A novel CT-emphysema index/FEV1 approach of phenotyping COPD to predict mortality

Li-Cher Loh,1 Choo-Khoon Ong,1 Hyun-Jung Koo,2 Sang Min Lee,2 Jae-Seung Lee,3 Yeon-Mok Oh,3 Joon-Beom Seo,2 Sang-Do Lee3 1Department of Medicine, RCSI & UCD Malaysia Campus, Penang, Malaysia; 2Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan...

Full description

Bibliographic Details
Main Authors: Loh LC, Ong CK, Koo HJ, Lee SM, Lee JS, Oh YM, Seo JB, Lee SD
Format: Article
Language:English
Published: Dove Medical Press 2018-08-01
Series:International Journal of COPD
Subjects:
Online Access:https://www.dovepress.com/a-novel-ct-emphysema-indexfev1-approach-of-phenotyping-copd-to-predict-peer-reviewed-article-COPD
id doaj-7bd0a49c7d784eb892887388b6f1ff2d
record_format Article
spelling doaj-7bd0a49c7d784eb892887388b6f1ff2d2020-11-24T23:33:39ZengDove Medical PressInternational Journal of COPD1178-20052018-08-01Volume 132543255040019A novel CT-emphysema index/FEV1 approach of phenotyping COPD to predict mortalityLoh LCOng CKKoo HJLee SMLee JSOh YMSeo JBLee SDLi-Cher Loh,1 Choo-Khoon Ong,1 Hyun-Jung Koo,2 Sang Min Lee,2 Jae-Seung Lee,3 Yeon-Mok Oh,3 Joon-Beom Seo,2 Sang-Do Lee3 1Department of Medicine, RCSI & UCD Malaysia Campus, Penang, Malaysia; 2Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea; 3Department of Pulmonary and Critical Care Medicine, and Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea Background: COPD-associated mortality was examined using a novel approach of phenotyping COPD based on computed tomography (CT)-emphysema index from quantitative CT (QCT) and post-bronchodilator (BD) forced expiratory volume in 1 second (FEV1) in a local Malaysian cohort.Patients and methods: Prospectively collected data of 112 eligible COPD subjects (mean age, 67 years; male, 93%; mean post-BD FEV1, 45.7%) was available for mortality analysis. Median follow-up time was 1,000 days (range, 60–1,400). QCT and clinicodemographic data were collected at study entry. Based on CT-emphysema index and post-BD FEV1% predicted, subjects were categorized into “emphysema-dominant,” “airway-dominant,” “mild mixed airway-emphysema,” and “severe mixed airway-emphysema” diseases.Results: Sixteen patients (14.2%) died of COPD-associated causes. There were 29 (25.9%) “mild mixed,” 23 (20.5%) “airway-dominant,” 15 (13.4%) “emphysema-dominant,” and 45 (40.2%) “severe mixed” cases. “Mild mixed” disease was proportionately more in Global Initiative for Chronic Obstructive Lung Disease (GOLD) Group A, while “severe mixed” disease was proportionately more in GOLD Groups B and D. Kaplan–Meier survival estimates showed increased mortality risk with “severe mixed” disease (log rank test, p=0.03) but not with GOLD groups (p=0.08). Univariate Cox proportionate hazard analysis showed that age, body mass index, long-term oxygen therapy, FEV1, forced volume capacity, COPD Assessment Test score, modified Medical Research Council score, St Georges’ Respiratory Questionnaire score, CT-emphysema index, and “severe mixed” disease (vs “mild mixed” disease) were associated with mortality. Multivariate Cox analysis showed that age, body mass index, and COPD Assessment Test score remain independently associated with mortality.Conclusion: “Severe mixed airway-emphysema” disease may predict COPD-associated mortality. Age, body mass index, and COPD Assessment Test score remain as key mortality risk factors in our cohort. Keywords: computed tomography, emphysema, forced expiratory volume, COPD, mortalityhttps://www.dovepress.com/a-novel-ct-emphysema-indexfev1-approach-of-phenotyping-copd-to-predict-peer-reviewed-article-COPDComputed tomographyemphysemaforced expiratory volumeCOPDmortality
collection DOAJ
language English
format Article
sources DOAJ
author Loh LC
Ong CK
Koo HJ
Lee SM
Lee JS
Oh YM
Seo JB
Lee SD
spellingShingle Loh LC
Ong CK
Koo HJ
Lee SM
Lee JS
Oh YM
Seo JB
Lee SD
A novel CT-emphysema index/FEV1 approach of phenotyping COPD to predict mortality
International Journal of COPD
Computed tomography
emphysema
forced expiratory volume
COPD
mortality
author_facet Loh LC
Ong CK
Koo HJ
Lee SM
Lee JS
Oh YM
Seo JB
Lee SD
author_sort Loh LC
title A novel CT-emphysema index/FEV1 approach of phenotyping COPD to predict mortality
title_short A novel CT-emphysema index/FEV1 approach of phenotyping COPD to predict mortality
title_full A novel CT-emphysema index/FEV1 approach of phenotyping COPD to predict mortality
title_fullStr A novel CT-emphysema index/FEV1 approach of phenotyping COPD to predict mortality
title_full_unstemmed A novel CT-emphysema index/FEV1 approach of phenotyping COPD to predict mortality
title_sort novel ct-emphysema index/fev1 approach of phenotyping copd to predict mortality
publisher Dove Medical Press
series International Journal of COPD
issn 1178-2005
publishDate 2018-08-01
description Li-Cher Loh,1 Choo-Khoon Ong,1 Hyun-Jung Koo,2 Sang Min Lee,2 Jae-Seung Lee,3 Yeon-Mok Oh,3 Joon-Beom Seo,2 Sang-Do Lee3 1Department of Medicine, RCSI & UCD Malaysia Campus, Penang, Malaysia; 2Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea; 3Department of Pulmonary and Critical Care Medicine, and Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea Background: COPD-associated mortality was examined using a novel approach of phenotyping COPD based on computed tomography (CT)-emphysema index from quantitative CT (QCT) and post-bronchodilator (BD) forced expiratory volume in 1 second (FEV1) in a local Malaysian cohort.Patients and methods: Prospectively collected data of 112 eligible COPD subjects (mean age, 67 years; male, 93%; mean post-BD FEV1, 45.7%) was available for mortality analysis. Median follow-up time was 1,000 days (range, 60–1,400). QCT and clinicodemographic data were collected at study entry. Based on CT-emphysema index and post-BD FEV1% predicted, subjects were categorized into “emphysema-dominant,” “airway-dominant,” “mild mixed airway-emphysema,” and “severe mixed airway-emphysema” diseases.Results: Sixteen patients (14.2%) died of COPD-associated causes. There were 29 (25.9%) “mild mixed,” 23 (20.5%) “airway-dominant,” 15 (13.4%) “emphysema-dominant,” and 45 (40.2%) “severe mixed” cases. “Mild mixed” disease was proportionately more in Global Initiative for Chronic Obstructive Lung Disease (GOLD) Group A, while “severe mixed” disease was proportionately more in GOLD Groups B and D. Kaplan–Meier survival estimates showed increased mortality risk with “severe mixed” disease (log rank test, p=0.03) but not with GOLD groups (p=0.08). Univariate Cox proportionate hazard analysis showed that age, body mass index, long-term oxygen therapy, FEV1, forced volume capacity, COPD Assessment Test score, modified Medical Research Council score, St Georges’ Respiratory Questionnaire score, CT-emphysema index, and “severe mixed” disease (vs “mild mixed” disease) were associated with mortality. Multivariate Cox analysis showed that age, body mass index, and COPD Assessment Test score remain independently associated with mortality.Conclusion: “Severe mixed airway-emphysema” disease may predict COPD-associated mortality. Age, body mass index, and COPD Assessment Test score remain as key mortality risk factors in our cohort. Keywords: computed tomography, emphysema, forced expiratory volume, COPD, mortality
topic Computed tomography
emphysema
forced expiratory volume
COPD
mortality
url https://www.dovepress.com/a-novel-ct-emphysema-indexfev1-approach-of-phenotyping-copd-to-predict-peer-reviewed-article-COPD
work_keys_str_mv AT lohlc anovelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT ongck anovelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT koohj anovelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT leesm anovelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT leejs anovelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT ohym anovelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT seojb anovelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT leesd anovelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT lohlc novelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT ongck novelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT koohj novelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT leesm novelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT leejs novelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT ohym novelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT seojb novelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
AT leesd novelctemphysemaindexfev1approachofphenotypingcopdtopredictmortality
_version_ 1725531171247357952