Individualized prediction of lung-function decline in chronic obstructive pulmonary disease.
Pubmed ID: 27486205
Pubmed Central ID: PMC5047815
Journal: CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne
Publication Date: 10/04/2016
Affiliation: Centre for Clinical Epidemiology and Evaluation (Zafari, Bryan, Sadatsafavi), Vancouver Coastal Health Research Institute, University of British Columbia; Centre for Heart and Lung Innovation (Sin, Man, McManus, Hollander), St. Paul's Hospital; Institute for Heart and Lung Health (Sin, Man, McManus, Hollander, Sadatsafavi), University of British Columbia; Division of Respiratory Medicine (Sin, Lam, Man, Sadatsafavi), Department of Medicine, University of British Columbia, Vancouver, BC; University Medical Center Groningen (Postma, Vonk), Groningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, Groningen; University Medical Center Groningen (Postma), Department of Pulmonary Diseases, University of Groningen, Groningen, the Netherlands; Department of Respiratory Medicine and Allergology (Löfdahl), Lund University, Lund, Sweden; Department of Epidemiology (Vonk), University of Groningen, University Medical Center Groningen, the Netherlands; School of Population and Public Health (Bryan), University of British Columbia, Vancouver, BC; Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences (Khakban), University of British Columbia, Vancouver, BC; David Geffen School of Medicine at UCLA (Tashkin), Los Angeles, Calif.; Johns Hopkins University School of Medicine (Wise), Baltimore, Md.; University of Minnesota School of Public Health (Connett), Minneapolis, Minn.; PROOF Centre for Excellence (McManus, Ng, Hollander), Vancouver, BC; Department of Community Health Sciences (Tammemagi), Brock University, St. Catharines, Ont.
MeSH Terms: Humans, Male, Adult, Female, Middle Aged, Smoking, Longitudinal Studies, Disease Progression, Forced Expiratory Volume, Lung, Pulmonary Disease, Chronic Obstructive, Smoking Cessation, Canada, Individuality
Authors: Connett JE, Hollander Z, Tashkin D, Ng R, McManus B, Postma DS, Sin DD, Zafari Z, Vonk J, Bryan S, Lam S, Tammemagi CM, Khakban R, Man SF, Wise RA, Sadatsafavi M, Löfdahl CG
Cite As: Zafari Z, Sin DD, Postma DS, Löfdahl CG, Vonk J, Bryan S, Lam S, Tammemagi CM, Khakban R, Man SF, Tashkin D, Wise RA, Connett JE, McManus B, Ng R, Hollander Z, Sadatsafavi M. Individualized prediction of lung-function decline in chronic obstructive pulmonary disease. CMAJ 2016 Oct 4;188(14):1004-1011. Epub 2016 Aug 2.
BACKGROUND: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV<sub>1</sub>) in current smokers with mild-to-moderate COPD. METHODS: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV<sub>1</sub> values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations. RESULTS: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline FEV<sub>1</sub> 2.75 L) to create the individualized prediction equations. There was significant between-individual variability in the rate of FEV<sub>1</sub> decline, with the interval for the annual rate of decline that contained 95% of individuals being -124 to -15 mL/yr for smokers and -83 to 15 mL/yr for sustained quitters. Clinical variables in the final model explained 88% of variation around follow-up FEV<sub>1</sub>. The C statistic for predicting severity grades was 0.90. Prediction equations performed robustly in the 2 external data sets. INTERPRETATION: A substantial part of individual variation in FEV<sub>1</sub> decline can be explained by easily measured clinical variables. The model developed in this work can be used for prediction of future lung health in patients with mild-to-moderate COPD. TRIAL REGISTRATION: Lung Health Study - ClinicalTrials.gov, no. NCT00000568; Pan-Canadian Early Detection of Lung Cancer Study - ClinicalTrials.gov, no. NCT00751660.