Carlos H Martinez1, Susan Murray2, R Graham Barr3,4, Eugene Bleecker5, Russell P Bowler6, Stephanie A Christenson7, Alejandro P Comellas8, Christopher B Cooper9, David Couper10, Gerard J Criner11, Jeffrey L Curtis1,12, Mark T Dransfield13,14, Nadia N Hansel15, Eric A Hoffman16,17, Richard E Kanner18, Eric Kleerup9, Jerry A Krishnan19, Stephen C Lazarus7, Nancy K Leidy20, Wanda O'Neal21, Fernando J Martinez1,22, Robert Paine18, Stephen I Rennard23, Donald P Tashkin7, Prescott G Woodruff7, MeiLan K Han1. 1. 1 Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, Michigan. 2. 2 School of Public Health, University of Michigan, Ann Arbor, Michigan. 3. 3 Department of Medicine and. 4. 4 Department of Epidemiology, Columbia University Medical Center, New York, New York. 5. 5 Center for Genomics and Personalized Medicine Research, School of Medicine, Wake Forest University, Winston-Salem, North Carolina. 6. 6 Department of Medicine, National Jewish Health, Denver, Colorado. 7. 7 Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California. 8. 8 Division of Pulmonary, Critical Care and Occupational Medicine, Department of Internal Medicine. 9. 9 Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California. 10. 10 Department of Biostatistics and. 11. 11 Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania. 12. 12 Medicine Service, Veterans Administration Ann Arbor Healthcare System, Ann Arbor, Michigan. 13. 13 Division of Pulmonary, Allergy and Critical Care Medicine and. 14. 14 UAB Lung Health Center, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama. 15. 15 Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland. 16. 16 Department of Radiology, and. 17. 17 Department of Biomedical Engineering, Carver College of Medicine, University of Iowa, Iowa City, Iowa. 18. 18 Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, Utah. 19. 19 Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, University of Illinois College of Medicine at Chicago, Chicago, Illinois. 20. 20 Office of Scientific Affairs, Evidera, Bethesda, Maryland. 21. 21 Department of Internal Medicine, Weill Cornell Medical College, New York, New York; and. 22. 22 Marsico Lung Institute/Cystic Fibrosis Research Center, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. 23. 23 Division of Pulmonary, Critical Care, Sleep and Allergy, University of Nebraska Medical Center, Omaha, Nebraska.
Abstract
RATIONALE: Ever-smokers without airflow obstruction scores greater than or equal to 10 on the COPD Assessment Test (CAT) still have frequent acute respiratory disease events (exacerbation-like), impaired exercise capacity, and imaging abnormalities. Identification of these subjects could provide new opportunities for targeted interventions. OBJECTIVES: We hypothesized that the four respiratory-related items of the CAT might be useful for identifying such individuals, with discriminative ability similar to CAT, which is an eight-item questionnaire used to assess chronic obstructive pulmonary disease impact, including nonrespiratory questions, with scores ranging from 0 to 40. METHODS: We evaluated ever-smoker participants in the Subpopulations and Intermediate Outcomes in COPD Study without airflow obstruction (FEV1/FVC ≥0.70; FVC above the lower limit of normal). Using the area under the receiver operating characteristic curve, we compared responses to both CAT and the respiratory symptom-related CAT items (cough, phlegm, chest tightness, and breathlessness) and their associations with longitudinal exacerbations. We tested agreement between the two strategies (κ statistic), and we compared demographics, lung function, and symptoms among subjects identified as having high symptoms by each strategy. RESULTS: Among 880 ever-smokers with normal lung function (mean age, 61 yr; 52% women) and using a CAT cutpoint greater than or equal to 10, we classified 51.8% of individuals as having high symptoms, 15.3% of whom experienced at least one exacerbation during 1-year follow-up. After testing sensitivity and specificity of different scores for the first four questions to predict any 1-year follow-up exacerbation, we selected cutpoints of 0-6 as representing a low burden of symptoms versus scores of 7 or higher as representing a high burden of symptoms for all subsequent comparisons. The four respiratory-related items with cutpoint greater than or equal to 7 selected 45.8% participants, 15.6% of whom experienced at least one exacerbation during follow-up. The two strategies largely identified the same individuals (agreement, 88.5%; κ = 0.77; P < 0.001), and the proportions of high-symptoms subjects who had severe dyspnea were similar between CAT and the first four CAT questions (25.9% and 26.8%, respectively), as were the proportions reporting impaired quality of life (66.9% and 70.5%, respectively) and short walking distance (22.4% and 23.1%, respectively). There was no difference in area under the receiver operating characteristic curve to predict 1-year follow-up exacerbations (CAT score ≥10, 0.66; vs. four respiratory items from CAT ≥7 score, 0.65; P = 0.69). Subjects identified by either method also had more depression/anxiety symptoms, poor sleep quality, and greater fatigue. CONCLUSIONS: Four CAT items on respiratory symptoms identified high-risk symptomatic ever-smokers with preserved spirometry as well as the CAT did. These data suggest that simpler strategies can be developed to identify these high-risk individuals in primary care.
RATIONALE: Ever-smokers without airflow obstruction scores greater than or equal to 10 on the COPD Assessment Test (CAT) still have frequent acute respiratory disease events (exacerbation-like), impaired exercise capacity, and imaging abnormalities. Identification of these subjects could provide new opportunities for targeted interventions. OBJECTIVES: We hypothesized that the four respiratory-related items of the CAT might be useful for identifying such individuals, with discriminative ability similar to CAT, which is an eight-item questionnaire used to assess chronic obstructive pulmonary disease impact, including nonrespiratory questions, with scores ranging from 0 to 40. METHODS: We evaluated ever-smoker participants in the Subpopulations and Intermediate Outcomes in COPD Study without airflow obstruction (FEV1/FVC ≥0.70; FVC above the lower limit of normal). Using the area under the receiver operating characteristic curve, we compared responses to both CAT and the respiratory symptom-related CAT items (cough, phlegm, chest tightness, and breathlessness) and their associations with longitudinal exacerbations. We tested agreement between the two strategies (κ statistic), and we compared demographics, lung function, and symptoms among subjects identified as having high symptoms by each strategy. RESULTS: Among 880 ever-smokers with normal lung function (mean age, 61 yr; 52% women) and using a CAT cutpoint greater than or equal to 10, we classified 51.8% of individuals as having high symptoms, 15.3% of whom experienced at least one exacerbation during 1-year follow-up. After testing sensitivity and specificity of different scores for the first four questions to predict any 1-year follow-up exacerbation, we selected cutpoints of 0-6 as representing a low burden of symptoms versus scores of 7 or higher as representing a high burden of symptoms for all subsequent comparisons. The four respiratory-related items with cutpoint greater than or equal to 7 selected 45.8% participants, 15.6% of whom experienced at least one exacerbation during follow-up. The two strategies largely identified the same individuals (agreement, 88.5%; κ = 0.77; P < 0.001), and the proportions of high-symptoms subjects who had severe dyspnea were similar between CAT and the first four CAT questions (25.9% and 26.8%, respectively), as were the proportions reporting impaired quality of life (66.9% and 70.5%, respectively) and short walking distance (22.4% and 23.1%, respectively). There was no difference in area under the receiver operating characteristic curve to predict 1-year follow-up exacerbations (CAT score ≥10, 0.66; vs. four respiratory items from CAT ≥7 score, 0.65; P = 0.69). Subjects identified by either method also had more depression/anxiety symptoms, poor sleep quality, and greater fatigue. CONCLUSIONS: Four CAT items on respiratory symptoms identified high-risk symptomatic ever-smokers with preserved spirometry as well as the CAT did. These data suggest that simpler strategies can be developed to identify these high-risk individuals in primary care.
Entities:
Keywords:
health status; obstructive lung disease; quality of life; questionnaires; symptoms
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