Year: 2014
Type: article
Abstract: IMPORTANCE: Comorbidities are common in COPD, but quantifying their burden is difficult. Currently there is a COPD-specific comorbidity index to predict mortality and another to predict general quality of life. We sought to develop and validate a COPD-specific comorbidity score that reflects comorbidity burden on patient-centered outcomes. MATERIALS AND METHODS: Using the COPDGene study (GOLD II-IV COPD), we developed comorbidity scores to describe patient-centered outcomes employing three techniques: 1) simple count, 2) weighted score, and 3) weighted score based upon statistical selection procedure. We tested associations, area under the Curve (AUC) and calibration statistics to validate scores internally with outcomes of respiratory disease-specific quality of life (St. George's Respiratory Questionnaire, SGRQ), six minute walk distance (6MWD), modified Medical Research Council (mMRC) dyspnea score and exacerbation risk, ultimately choosing one score for external validation in SPIROMICS. RESULTS: Associations between comorbidities and all outcomes were comparable across the three scores. All scores added predictive ability to models including age, gender, race, current smoking status, pack-years smoked and FEV1 (p<0.001 for all comparisons). Area under the curve (AUC) was similar between all three scores across outcomes: SGRQ (range 0·7624-0·7676), MMRC (0·7590-0·7644), 6MWD (0·7531-0·7560) and exacerbation risk (0·6831-0·6919). Because of similar performance, the comorbidity count was used for external validation. In the SPIROMICS cohort, the comorbidity count performed well to predict SGRQ (AUC 0·7891), MMRC (AUC 0·7611), 6MWD (AUC 0·7086), and exacerbation risk (AUC 0·7341). CONCLUSIONS: Quantifying comorbidity provides a more thorough understanding of the risk for patient-centered outcomes in COPD. A comorbidity count performs well to quantify comorbidity in a diverse population with COPD.
Source: PLoS ONE
Authors: Nirupama Putcha, Milo A. Puhan, M. Bradley Drummond, MeiLan K. Han, Elizabeth A. Regan, Nicola A. Hanania, Carlos H. Martinez, Marilyn Foreman, Surya P. Bhatt, Barry Make, Joe Ramsdell, Dawn L. DeMeo, R. Graham Barr, Stephen I. Rennard, Fernando Martinez, Edwin K. Silverman, James Crapo, Robert A. Wise, Nadia N. Hansel
Institutions: Johns Hopkins University, Johns Hopkins Medicine, University of Zurich, University of Michigan, Michigan Medicine, National Jewish Health, Baylor College of Medicine, Morehouse School of Medicine, University of Alabama at Birmingham, University of California San Diego, Brigham and Women's Hospital, Harvard University, Columbia University Irving Medical Center, University of Nebraska Medical Center, Cornell University, Weill Cornell Medical Center
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,382
Awards: G1689438493, G2099663897, G2212190077, G2408777687, G2644038179, G2736175024, G3027037974, G377726100, G3868091120, G3999916299, G4621512325, G4749522346, Mechanisms of COPD Subphenotype Development, G535525194, (2 of 2) Genetic Epidemiology of COPD, G650253055, G7206313631, G8002148031, G8957911378, Multidisciplinary Training Program in Lung Disease
OpenAlex ID: W2129407162