4.6 Article

The Association Between Rate and Severity of Exacerbations in Chronic Obstructive Pulmonary Disease: An Application of a Joint Frailty-Logistic Model

期刊

AMERICAN JOURNAL OF EPIDEMIOLOGY
卷 184, 期 9, 页码 681-689

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/aje/kww085

关键词

chronic obstructive pulmonary disease; nonlinear mixed models; random effects; randomized trials; survival analysis

资金

  1. Canadian Institutes of Health Research [142238]
  2. Canadian Respiratory Research Network
  3. Genome Canada: Genome British Columbia
  4. Genome Quebec
  5. Providence
  6. St. Paul's Hospital Foundation
  7. Prevention of Organ Failure (PROOF) Centre of Excellence
  8. National Sanitarium Association

向作者/读者索取更多资源

Exacerbations are a hallmark of chronic obstructive pulmonary disease (COPD). Evidence suggests the presence of substantial between-individual variability (heterogeneity) in exacerbation rates. The question of whether individuals vary in their tendency towards experiencing severe (versus mild) exacerbations, or whether there is an association between exacerbation rate and severity, has not yet been studied. We used data from the MACRO Study, a 1-year randomized trial of the use of azithromycin for prevention of COPD exacerbations (United States and Canada, 2006-2010; n = 1,107, mean age = 65.2 years, 59.1% male). A parametric frailty model was combined with a logistic regression model, with bivariate random effects capturing heterogeneity in rate and severity. The average rate of exacerbation was 1.53 episodes/year, with 95% of subjects having a model-estimated rate of 0.47-4.22 episodes/year. The overall ratio of severe exacerbations to total exacerbations was 0.22, with 95% of subjects having a model-estimated ratio of 0.04-0.60. We did not confirm an association between exacerbation rate and severity (P = 0.099). A unified model, implemented in standard software, could estimate joint heterogeneity in COPD exacerbation rate and severity and can have applications in similar contexts where inference on event time and intensity is considered. We provide SAS code (SAS Institute, Inc., Cary, North Carolina) and a simulated data set to facilitate further uses of this method.

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