A new approach for identifying patients with undiagnosed chronic obstructive pulmonary disease

Fernando J. Martinez, David Mannino, Nancy Kline Leidy, Karen G. Malley, Elizabeth D. Bacci, R. Graham Barr, Russ P. Bowler, Meilan K. Han, Julia F. Houfek, Barry Make, Catherine A. Meldrum, Stephen Rennard, Byron Thomashow, John Walsh, Barbara P. Yawn

Research output: Contribution to journalArticle

25 Citations (Scopus)

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 SNof 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).

Original languageEnglish (US)
Pages (from-to)748-756
Number of pages9
JournalAmerican Journal of Respiratory and Critical Care Medicine
Volume195
Issue number6
DOIs
StatePublished - Mar 15 2017

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Chronic Obstructive Pulmonary Disease
Sensitivity and Specificity
Primary Health Care
Spirometry
Disease Progression
Case-Control Studies
Respiration
Therapeutics
Clinical Trials
Lung

Keywords

  • Chronic obstructive pulmonary disease
  • Primary care
  • Questionnaire
  • Random forests
  • Screening

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine

Cite this

Martinez, F. J., Mannino, D., Leidy, N. K., Malley, K. G., Bacci, E. D., Barr, R. G., ... Yawn, B. P. (2017). A new approach for identifying patients with undiagnosed chronic obstructive pulmonary disease. American Journal of Respiratory and Critical Care Medicine, 195(6), 748-756. https://doi.org/10.1164/rccm.201603-0622OC

A new approach for identifying patients with undiagnosed chronic obstructive pulmonary disease. / Martinez, Fernando J.; Mannino, David; Leidy, Nancy Kline; Malley, Karen G.; Bacci, Elizabeth D.; Barr, R. Graham; Bowler, Russ P.; Han, Meilan K.; Houfek, Julia F.; Make, Barry; Meldrum, Catherine A.; Rennard, Stephen; Thomashow, Byron; Walsh, John; Yawn, Barbara P.

In: American Journal of Respiratory and Critical Care Medicine, Vol. 195, No. 6, 15.03.2017, p. 748-756.

Research output: Contribution to journalArticle

Martinez, FJ, Mannino, D, Leidy, NK, Malley, KG, Bacci, ED, Barr, RG, Bowler, RP, Han, MK, Houfek, JF, Make, B, Meldrum, CA, Rennard, S, Thomashow, B, Walsh, J & Yawn, BP 2017, 'A new approach for identifying patients with undiagnosed chronic obstructive pulmonary disease', American Journal of Respiratory and Critical Care Medicine, vol. 195, no. 6, pp. 748-756. https://doi.org/10.1164/rccm.201603-0622OC
Martinez, Fernando J. ; Mannino, David ; Leidy, Nancy Kline ; Malley, Karen G. ; Bacci, Elizabeth D. ; Barr, R. Graham ; Bowler, Russ P. ; Han, Meilan K. ; Houfek, Julia F. ; Make, Barry ; Meldrum, Catherine A. ; Rennard, Stephen ; Thomashow, Byron ; Walsh, John ; Yawn, Barbara P. / A new approach for identifying patients with undiagnosed chronic obstructive pulmonary disease. In: American Journal of Respiratory and Critical Care Medicine. 2017 ; Vol. 195, No. 6. pp. 748-756.
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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 SNof 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).",
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AU - Martinez, Fernando J.

AU - Mannino, David

AU - Leidy, Nancy Kline

AU - Malley, Karen G.

AU - Bacci, Elizabeth D.

AU - Barr, R. Graham

AU - Bowler, Russ P.

AU - Han, Meilan K.

AU - Houfek, Julia F.

AU - Make, Barry

AU - Meldrum, Catherine A.

AU - Rennard, Stephen

AU - Thomashow, Byron

AU - Walsh, John

AU - Yawn, Barbara P.

PY - 2017/3/15

Y1 - 2017/3/15

N2 - 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 SNof 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).

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KW - Chronic obstructive pulmonary disease

KW - Primary care

KW - Questionnaire

KW - Random forests

KW - Screening

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