Identification of Chronic Obstructive Pulmonary Disease Axes That Predict All-Cause Mortality: The COPDGene Study

• Published in: American journal of epidemiology Vol. 187; no. 10; pp. 2109 - 2116
• Main Authors: Kinney, Gregory L, Santorico, Stephanie A, Young, Kendra A, Cho, Michael H, Castaldi, Peter J, San José Estépar, Raul, Ross, James C, Dy, Jennifer G, Make, Barry J, Regan, Elizabeth A, Lynch, David A, Everett, Douglas C, Lutz, Sharon M, Silverman, Edwin K, Washko, George R, Crapo, James D, Hokanson, John E
• Format: Journal Article
• Language: English
• Published: United States Oxford Publishing Limited (England) 01.10.2018; Oxford University Press
• Subjects: Adult; Aged; Aged, 80 and over; Allergic diseases; Cause of Death; Chronic obstructive pulmonary disease; Computed tomography; Covariance; Domains; Emphysema; Factor analysis; Factor Analysis, Statistical; Female; Humans; Lung - diagnostic imaging; Lung - physiopathology; Lung diseases; Lungs; Male; Middle Aged; Mortality; Obstructive lung disease; Original Contributions; Phenotype; Phenotypes; Predictive Value of Tests; Proportional Hazards Models; Pulmonary Disease, Chronic Obstructive - genetics; Pulmonary Disease, Chronic Obstructive - mortality; Pulmonary functions; Respiratory function; Respiratory Function Tests - statistics & numerical data; Respiratory tract diseases; Risk Assessment - methods; Risk Factors; Structural integrity; Tomography, X-Ray Computed - statistics & numerical data
• ISSN: 0002-9262; 1476-6256
• DOI: 10.1093/aje/kwy087

Chronic obstructive pulmonary disease (COPD) is a syndrome caused by damage to the lungs that results in decreased pulmonary function and reduced structural integrity. Pulmonary function testing (PFT) is used to diagnose and stratify COPD into severity groups, and computed tomography (CT) imaging of the chest is often used to assess structural changes in the lungs. We hypothesized that the combination of PFT and CT phenotypes would provide a more powerful tool for assessing underlying morphologic differences associated with pulmonary function in COPD than does PFT alone. We used factor analysis of 26 variables to classify 8,157 participants recruited into the COPDGene cohort between January 2008 and June 2011 from 21 clinical centers across the United States. These factors were used as predictors of all-cause mortality using Cox proportional hazards modeling. Five factors explained 80% of the covariance and represented the following domains: factor 1, increased emphysema and decreased pulmonary function; factor 2, airway disease and decreased pulmonary function; factor 3, gas trapping; factor 4, CT variability; and factor 5, hyperinflation. After more than 46,079 person-years of follow-up, factors 1 through 4 were associated with mortality and there was a significant synergistic interaction between factors 1 and 2 on death. Considering CT measures along with PFT in the assessment of COPD can identify patients at particularly high risk for death.