Statistical Modeling of Disease Progression for Chronic Obstructive Pulmonary Disease Using Data from the ECLIPSE Study
Alex Exuzides,
Chris Colby,
Andrew H. Briggs,
David A. Lomas,
Maureen P. M. H. Rutten- van Mölken,
Maggie Tabberer,
Mike Chambers,
Hana Muellerova,
Nicholas Locantore,
Nancy A. Risebrough,
Afisi S. Ismaila and
Sebastian Gonzalez-McQuire
Medical Decision Making, 2017, vol. 37, issue 4, 453-468
Abstract:
Background . To develop statistical models predicting disease progression and outcomes in chronic obstructive pulmonary disease (COPD), using data from ECLIPSE, a large, observational study of current and former smokers with COPD. Methods . Based on a conceptual model of COPD disease progression and data from 2164 patients, associations were made between baseline characteristics, COPD disease progression attributes (exacerbations, lung function, exercise capacity, and symptoms), health-related quality of life (HRQoL), and survival. Linear and nonlinear functional forms of random intercept models were used to characterize these relationships. Endogeneity was addressed by time-lagging variables in the regression models. Results . At the 5% significance level, an exacerbation history in the year before baseline was associated with increased risk of future exacerbations (moderate: +125.8%; severe: +89.2%) and decline in lung function (forced expiratory volume in 1 second [FEV 1 ]) (–94.20 mL per year). Each 1% increase in FEV 1 % predicted was associated with decreased risk of exacerbations (moderate: –1.1%; severe: –3.0%) and increased 6-minute walk test distance (6MWD) (+1.5 m). Increases in baseline exercise capacity (6MWD, per meter) were associated with slightly increased risk of moderate exacerbations (+0.04%) and increased FEV 1 (+0.62 mL). Symptoms (dyspnea, cough, and/or sputum) were associated with an increased risk of moderate exacerbations (+13.4% to +31.1%), and baseline dyspnea (modified Medical Research Council score ≥2 v.
Keywords: exacerbation; lung function; survival; St George’s Respiratory Questionnaire; mixed models (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:37:y:2017:i:4:p:453-468
DOI: 10.1177/0272989X15610781
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