Format

Send to

Choose Destination
Am J Respir Crit Care Med. 2017 Mar 15;195(6):748-756. doi: 10.1164/rccm.201603-0622OC.

A New Approach for Identifying Patients with Undiagnosed Chronic Obstructive Pulmonary Disease.

Author information

1
1 Joan and Sanford I. Weill Department of Medicine, Weill Cornell Medical College, New York, New York.
2
2 Department of Preventive Medicine and Environmental Health, University of Kentucky, Lexington, Kentucky.
3
3 Outcomes Research, Evidera, Bethesda, Maryland.
4
4 Outcomes Research, Evidera, Seattle, Washington.
5
5 Department of Medicine and.
6
6 Department of Epidemiology, Columbia University Medical Center, New York, New York.
7
7 Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, National Jewish Health, Denver, Colorado.
8
8 Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, Michigan.
9
9 College of Nursing and.
10
10 Pulmonary, Critical Care, Allergy and Sleep Medicine Division, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska.
11
11 Clinical Discovery Unit, Early Clinical Discovery, AstraZeneca, Cambridge, United Kingdom.
12
12 Division of Pulmonary, Allergy and Critical Care Medicine, Columbia University, New York, New York.
13
13 COPD Foundation, Washington, District of Columbia; and.
14
14 Department of Family and Community Health, University of Minnesota, Minneapolis, Minnesota.

Abstract

RATIONALE:

Chronic obstructive pulmonary disease (COPD) is often unrecognized and untreated.

OBJECTIVES:

To develop a method for identifying undiagnosed COPD requiring treatment with currently available therapies (FEV1 <60% predicted and/or exacerbation risk).

METHODS:

We conducted a multisite, cross-sectional, case-control study in U.S. pulmonary and primary care clinics that recruited subjects from primary care settings. Cases were patients with COPD and at least one exacerbation in the past year or FEV1 less than 60% of predicted without exacerbation in the past year. Control subjects were persons with no COPD or with mild COPD (FEV1 ≥60% predicted, no exacerbation in the past year). In random forests analyses, we identified the smallest set of questions plus peak expiratory flow (PEF) with optimal sensitivity (SN) and specificity (SP).

MEASUREMENTS AND MAIN RESULTS:

PEF and spirometry were recorded in 186 cases and 160 control subjects. The mean (SD) age of the sample population was 62.7 (10.1) years; 55% were female; 86% were white; and 16% had never smoked. The mean FEV1 percent predicted for cases was 42.5% (14.2%); for control subjects, it was 82.5% (15.7%). A five-item questionnaire, CAPTURE (COPD Assessment in Primary Care to Identify Undiagnosed Respiratory Disease and Exacerbation Risk), was used to assess exposure, breathing problems, tiring easily, and acute respiratory illnesses. CAPTURE exhibited an SN of 95.7% and an SP of 44.4% for differentiating cases from all control subjects, and an SN of 95.7% and an SP of 67.8% for differentiating cases from no-COPD control subjects. The PEF (males, <350 L/min; females, <250 L/min) SN and SP were 88.0% and 77.5%, respectively, for differentiating cases from all control subjects, and they were 88.0% and 90.8%, respectively, for distinguishing cases from no-COPD control subjects. The CAPTURE plus PEF exhibited improved SN and SP for all cases versus all control subjects (89.7% and 78.1%, respectively) and for all cases versus no-COPD control subjects (89.7% and 93.1%, respectively).

CONCLUSIONS:

CAPTURE with PEF can identify patients with COPD who would benefit from currently available therapy and require further diagnostic evaluation. Clinical trial registered with clinicaltrials.gov (NCT01880177).

KEYWORDS:

chronic obstructive pulmonary disease; primary care; questionnaire; random forests; screening

Comment in

PMID:
27783539
PMCID:
PMC5363964
DOI:
10.1164/rccm.201603-0622OC
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Atypon Icon for PubMed Central
Loading ...
Support Center