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PLoS One. 2014 Dec 16;9(12):e114438. doi: 10.1371/journal.pone.0114438. eCollection 2014.

A simplified score to quantify comorbidity in COPD.

Author information

1
Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
2
Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Zurich, Switzerland.
3
Pulmonary & Critical Care Medicine, University of Michigan, Ann Arbor, Michigan, United States of America.
4
Department of Medicine, National Jewish Health, Denver, Colorado, United States of America.
5
Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine, Houston, Texas, United States of America.
6
Pulmonary and Critical Care Medicine, Morehouse School of Medicine, Atlanta, Georgia, United States of America.
7
Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
8
Pulmonary and Critical Care, National Jewish Health, Denver, Colorado, United States of America.
9
Pulmonary and Critical Care Medicine, University of California San Diego, San Diego, California, United States of America.
10
Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
11
Department of Medicine, Department of Epidemiology, Columbia University Medical Center, New York City, New York, United States of America.
12
Pulmonary and Critical Care Medicine, University of Nebraska Medical Center, Omaha, Nebraska, United States of America.
13
Pulmonary and Critical Care Medicine, New York Presbyterian-Weill Cornell Medical College, New York City, New York, United States of America.

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.

PMID:
25514500
PMCID:
PMC4267736
DOI:
10.1371/journal.pone.0114438
[Indexed for MEDLINE]
Free PMC Article

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