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Disease Progression Modelling in Chronic Obstructive Pulmonary Disease (COPD)

Young, AL; Bragman, FJS; Rangelov, B; Han, M; Galbán, CJ; Lynch, DA; Hawkes, DJ; ... COPDGene Investigators, .; + view all (2019) Disease Progression Modelling in Chronic Obstructive Pulmonary Disease (COPD). American Journal of Respiratory and Critical Care Medicine 10.1164/rccm.201908-1600OC. (In press). Green open access

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Abstract

RATIONALE: The decades-long progression of Chronic Obstructive Pulmonary Disease (COPD) renders identifying different trajectories of disease progression challenging. OBJECTIVES: To identify subtypes of COPD patients with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference (SuStaIn)", and to evaluate the utility of SuStaIn for patient stratification in COPD. METHODS: We applied SuStaIn to cross-sectional CT imaging markers in 3698 GOLD1-4 patients and 3479 controls from the COPDGene study to identify COPD patient subtypes. We confirmed the identified subtypes and progression patterns using ECLIPSE data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data. MEASUREMENTS AND MAIN RESULTS: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n=2354, 70.4%) in which small airway dysfunction and emphysema precede large-airway wall abnormalities, and an "Airway→Tissue" subtype (n=988, 29.6%) in which large-airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r=-0.16 (p<0.001) in the Tissue→Airway group; r=-0.14 (p=0.011) in the Airway→Tissue group). SuStaIn placed 30% of smokers with normal lung function at non-baseline stages suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up. CONCLUSIONS: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One-third of healthy smokers have detectable imaging changes, suggesting a new biomarker of 'early COPD'.

Type: Article
Title: Disease Progression Modelling in Chronic Obstructive Pulmonary Disease (COPD)
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1164/rccm.201908-1600OC
Publisher version: https://doi.org/10.1164/rccm.201908-1600OC
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Bronchitis, CT Imaging, Cluster Analysis, Emphysema, Pulmonary Disease, Chronic Obstructive
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Respiratory Medicine
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10085101
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