Show simple item record

dc.contributor.authorZou, C.
dc.contributor.authorLi, F.
dc.contributor.authorChoi, J.
dc.contributor.authorHaghighi, B.
dc.contributor.authorChoi, S.
dc.contributor.authorRajaraman, P.K.
dc.contributor.authorComellas, A.P.
dc.contributor.authorNewell, J.D.
dc.contributor.authorJnr
dc.contributor.authorLee, C.H.
dc.contributor.authorGraham Barr, R.
dc.contributor.authorBleecker, E.
dc.contributor.authorCooper, C.B.
dc.contributor.authorCouper, D.
dc.contributor.authorHan, M.
dc.contributor.authorHansel, N.N.
dc.contributor.authorKanner, R.E.
dc.contributor.authorKazerooni, E.A.
dc.contributor.authorKleerup, E.C.
dc.contributor.authorMartinez, F.J.
dc.contributor.authorO’neal, W.
dc.contributor.authorPaine, R., III
dc.contributor.authorRennard, S.I.
dc.contributor.authorSmith, B.M.
dc.contributor.authorWoodruff, P.G.
dc.contributor.authorHoffman, E.A.
dc.contributor.authorLin, C.-L.
dc.date.accessioned2021-07-22T00:48:10Z
dc.date.available2021-07-22T00:48:10Z
dc.date.issued2021
dc.identifier.citationZou, C., Li, F., Choi, J., Haghighi, B., Choi, S., Rajaraman, P. K., Comellas, A. P., Newell, J. D., Jnr, Lee, C. H., Graham Barr, R., Bleecker, E., Cooper, C. B., Couper, D., Han, M., Hansel, N. N., Kanner, R. E., Kazerooni, E. A., Kleerup, E. C., Martinez, F. J., … Lin, C.-L. (2021). 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). International Journal of COPD, 16, 1477–1496.
dc.identifier.issn1176-9106
dc.identifier.pmid34103907
dc.identifier.doi10.2147/COPD.S301466
dc.identifier.urihttp://hdl.handle.net/10150/660969
dc.description.abstractPurpose: 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. © 2021 Zou et al.
dc.language.isoen
dc.publisherDove Medical Press Ltd
dc.rightsCopyright © 2021 Zou et al. 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/).
dc.rights.urihttps://creativecommons.org/licenses/by-nc/3.0/
dc.subjectComputed tomography
dc.subjectEmphysema
dc.subjectFunctional small airway disease
dc.subjectLongitudinal clustering
dc.titleLongitudinal imaging-based clusters in former smokers of the copd cohort associate with clinical characteristics: The subpopulations and intermediate outcome measures in copd study (spiromics)
dc.typeArticle
dc.typetext
dc.contributor.departmentDepartment of Medicine, The University of Arizona
dc.identifier.journalInternational Journal of COPD
dc.description.noteOpen access journal
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal published version
dc.source.journaltitleInternational Journal of COPD
refterms.dateFOA2021-07-22T00:48:10Z


Files in this item

Thumbnail
Name:
COPD-301466-longitudinal-imagi ...
Size:
9.047Mb
Format:
PDF
Description:
Final Published Version

This item appears in the following Collection(s)

Show simple item record

Copyright © 2021 Zou et al. 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/).
Except where otherwise noted, this item's license is described as Copyright © 2021 Zou et al. 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/).