Document Type
Article
Journal Title
International Journal of Chronic Obstructive Pulmonary Disease
Publication Date
2021
Volume
16
Abstract
PURPOSE: Quantitative computed tomography (qCT) imaging-based cluster analysis identified clinically meaningful COPD former-smoker subgroups (clusters) based on cross-sectional data. We aimed to identify progression clusters for former smokers using longitudinal data.
PATIENTS AND METHODS: We selected 472 former smokers from SPIROMICS with a baseline visit and a one-year follow-up visit. A total of 150 qCT imaging-based variables, comprising 75 variables at baseline and their corresponding progression rates, were derived from the respective inspiration and expiration scans of the two visits. The COPD progression clusters identified were then associated with subject demography, clinical variables and biomarkers.
RESULTS: COPD severities at baseline increased with increasing cluster number. Cluster 1 patients were an obese subgroup with rapid progression of functional small airway disease percentage (fSAD%) and emphysema percentage (Emph%). Cluster 2 exhibited a decrease of fSAD% and Emph%, an increase of tissue fraction at total lung capacity and airway narrowing over one year. Cluster 3 showed rapid expansion of Emph% and an attenuation of fSAD%. Cluster 4 demonstrated severe emphysema and fSAD and significant structural alterations at baseline with rapid progression of fSAD% over one year. Subjects with different progression patterns in the same cross-sectional cluster were identified by longitudinal clustering.
CONCLUSION: qCT imaging-based metrics at two visits for former smokers allow for the derivation of four statistically stable clusters associated with unique progression patterns and clinical characteristics. Use of baseline variables and their progression rates enables identification of longitudinal clusters, resulting in a refinement of cross-sectional clusters.
MeSH Headings
Cross-Sectional Studies, Humans, Outcome Assessment, Health Care, Pulmonary Disease, Chronic Obstructive, Pulmonary Emphysema, Smokers
DOI Link
ISSN
1178-2005
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 3.0 License
Rights
Creative Commons License © 2022 The Author(s). 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, 3.0) License. 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.
Recommended Citation
Zou, Chunrui; Li, Frank; Choi, Jiwoong; Haghighi, Babak; Choi, Sanghun; Rajaraman, Prathish K.; Comellas, Alejandro P.; Newell, John D.; Lee, Chang Hyun; Barr, R. Graham; Bleecker, Eugene; Cooper, Christopher B.; Couper, David; Han, Meilan; Hansel, Nadia N.; Kanner, Richard E.; Kazerooni, Ella A.; Kleerup, Eric C.; Martinez, Fernando J.; O'Neal, Wanda; Paine, Robert; Rennard, Stephen I.; Smith, Benjamin M.; Woodruff, Prescott G.; Hoffman, Eric A.; and Lin, Ching-Long, "Longitudinal Imaging-Based Clusters in Former Smokers of the COPD Cohort Associate with Clinical Characteristics: The SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)" (2021). Journal Articles: Pulmonary & Critical Care Med. 39.
https://digitalcommons.unmc.edu/com_pulm_articles/39
Included in
Allergy and Immunology Commons, Critical Care Commons, Respiratory System Commons, Respiratory Tract Diseases Commons