Factor analysis in predominantly severe COPD: Identification of disease heterogeneity by easily measurable characteristics
(2013) In Respiratory Medicine 107(12). p.1939-1947- Abstract
- Background: The clinical and demographic variables defining the heterogeneity of chronic obstructive pulmonary disease (COPD) are unclear. A post-hoc analysis of five randomised studies in patients with a history of previous exacerbations examined the clinical and demographic characteristics describing moderate-to-very-severe COPD. Methods: Factor analysis was performed on all continuous baseline demographic and clinical data, without variable selection. Analyses were based on the full cohort and on stratifications by pack-years smoked, smoking status, gender, and comorbidities; patient exacerbation history was analysed in two of the five studies. Findings: 6162 COPD patients were evaluated (70% male; 40% current smokers; mean... (More)
- Background: The clinical and demographic variables defining the heterogeneity of chronic obstructive pulmonary disease (COPD) are unclear. A post-hoc analysis of five randomised studies in patients with a history of previous exacerbations examined the clinical and demographic characteristics describing moderate-to-very-severe COPD. Methods: Factor analysis was performed on all continuous baseline demographic and clinical data, without variable selection. Analyses were based on the full cohort and on stratifications by pack-years smoked, smoking status, gender, and comorbidities; patient exacerbation history was analysed in two of the five studies. Findings: 6162 COPD patients were evaluated (70% male; 40% current smokers; mean pre-bronchodilator forced expiratory volume in 1 s [FEV1] 35.2% predicted). Baseline clinical and demographic variables loaded differentially on six factors with minimal overlap, explaining 60.4% of the heterogeneity: 1) symptoms (cough, dyspnoea, steep disturbance), health status, reliever use; 2) pre-bronchodilator FEV1, FEV1/forced vital capacity, morning peak expiratory flow (PEF), body mass index (BMI); 3) blood pressure; 4) age, months since first COPD symptoms; 5) PEF variability; 6) pulse, FEV1 reversibility. Most factors loaded similarly in stratified and exacerbation analyses. BMI loaded with reversibility in females, and with age and months since first COPD symptoms in ex-smokers. Exacerbations loaded to factor 6. Interpretation: Readily available data can explain similar to 60% of COPD heterogeneity in a large dataset of predominantly severe COPD patients. Factors were robust over determinants of disease outcome; gender, smoking status, pack-years smoked, and comorbidities. The main factors were largely unchanged by adding exacerbations. Only BMI loaded to other factors. (C) 2013 Published by Elsevier Ltd. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4320113
- author
- Postma, Dirkje S. ; Anzueto, Antonio R. ; Jenkins, Christine ; Make, Barry J. ; Similowski, Thomas ; Ostlund, Ollie ; Eriksson, Göran LU and Calverley, Peter M.
- organization
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Chronic obstructive pulmonary disease, Exacerbations, Heterogeneity, Factor analysis
- in
- Respiratory Medicine
- volume
- 107
- issue
- 12
- pages
- 1939 - 1947
- publisher
- Elsevier
- external identifiers
-
- wos:000329558700017
- scopus:84890313666
- pmid:23953956
- ISSN
- 1532-3064
- DOI
- 10.1016/j.rmed.2013.07.011
- language
- English
- LU publication?
- yes
- id
- 90c87da6-a7bd-4beb-b56b-eb8e2b18c601 (old id 4320113)
- date added to LUP
- 2016-04-01 14:41:44
- date last changed
- 2022-01-28 02:03:36
@article{90c87da6-a7bd-4beb-b56b-eb8e2b18c601,
abstract = {{Background: The clinical and demographic variables defining the heterogeneity of chronic obstructive pulmonary disease (COPD) are unclear. A post-hoc analysis of five randomised studies in patients with a history of previous exacerbations examined the clinical and demographic characteristics describing moderate-to-very-severe COPD. Methods: Factor analysis was performed on all continuous baseline demographic and clinical data, without variable selection. Analyses were based on the full cohort and on stratifications by pack-years smoked, smoking status, gender, and comorbidities; patient exacerbation history was analysed in two of the five studies. Findings: 6162 COPD patients were evaluated (70% male; 40% current smokers; mean pre-bronchodilator forced expiratory volume in 1 s [FEV1] 35.2% predicted). Baseline clinical and demographic variables loaded differentially on six factors with minimal overlap, explaining 60.4% of the heterogeneity: 1) symptoms (cough, dyspnoea, steep disturbance), health status, reliever use; 2) pre-bronchodilator FEV1, FEV1/forced vital capacity, morning peak expiratory flow (PEF), body mass index (BMI); 3) blood pressure; 4) age, months since first COPD symptoms; 5) PEF variability; 6) pulse, FEV1 reversibility. Most factors loaded similarly in stratified and exacerbation analyses. BMI loaded with reversibility in females, and with age and months since first COPD symptoms in ex-smokers. Exacerbations loaded to factor 6. Interpretation: Readily available data can explain similar to 60% of COPD heterogeneity in a large dataset of predominantly severe COPD patients. Factors were robust over determinants of disease outcome; gender, smoking status, pack-years smoked, and comorbidities. The main factors were largely unchanged by adding exacerbations. Only BMI loaded to other factors. (C) 2013 Published by Elsevier Ltd.}},
author = {{Postma, Dirkje S. and Anzueto, Antonio R. and Jenkins, Christine and Make, Barry J. and Similowski, Thomas and Ostlund, Ollie and Eriksson, Göran and Calverley, Peter M.}},
issn = {{1532-3064}},
keywords = {{Chronic obstructive pulmonary disease; Exacerbations; Heterogeneity; Factor analysis}},
language = {{eng}},
number = {{12}},
pages = {{1939--1947}},
publisher = {{Elsevier}},
series = {{Respiratory Medicine}},
title = {{Factor analysis in predominantly severe COPD: Identification of disease heterogeneity by easily measurable characteristics}},
url = {{http://dx.doi.org/10.1016/j.rmed.2013.07.011}},
doi = {{10.1016/j.rmed.2013.07.011}},
volume = {{107}},
year = {{2013}},
}