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Performance of COPD Population Screener Questionnaire in COPD Screening: a Validation Study and Meta-analysis

Overview
Journal Ann Med
Publisher Informa Healthcare
Specialty General Medicine
Date 2021 Jul 20
PMID 34282697
Citations 9
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Abstract

This study aimed to validate the chronic obstructive pulmonary disease (COPD) Population Screener (COPD-PS) questionnaire as a screening tool in a cohort of Chinese subjects who underwent a health examination, and to summarise its overall performance through a meta-analysis. We enrolled 997 subjects aged ≥40 years who underwent a health examination, both lung function and COPD-PS data were collected. The screening performance of COPD-PS was evaluated with a receiver operating characteristic (ROC) curve analysis, using the area under the curve (AUC) to assess the screening accuracy. A standard diagnostic meta-analysis was used to summarise the screening performance of COPD-PS for COPD. Of the 997 subjects, 157 were identified as having COPD. The COPD-PS score was significantly higher in COPD patients than controls (5.03 ± 5.11 vs. 2.72 ± 1.80,  < .001). At a cut-off of 4, the sensitivity and specificity of COPD-PS for identifying COPD were 74.52 and 70.24%, respectively, with an AUC of 0.79. Eight studies (including this study) were included in this meta-analysis. The pooled estimates for COPD-PS were as follows: sensitivity of 0.66 (95% CI: 0.47-0.63), specificity of 0.86 (95% CI: 0.84-0.89), positive likelihood ratio of 3.00 (95% CI: 1.65-5.47), negative likelihood ratio of 0.43 (95% CI: 0.35-0.52) and diagnostic odds ratio of 7.24 (95% CI: 3.91-13.40). The AUC of the summary ROC curve was 0.78. COPD-PS appears to be a useful tool for screening individuals with a high risk of COPD and guiding the selection of individuals for subsequent spirometry examination.KEY MESSAGESCOPD-PS is a simple and useful method to screen COPD.The combination of COPD-PS with other tools may improve the screen performance.

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References
1.
Deeks J, Macaskill P, Irwig L . The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol. 2005; 58(9):882-93. DOI: 10.1016/j.jclinepi.2005.01.016. View

2.
Leeflang M, Deeks J, Gatsonis C, Bossuyt P . Systematic reviews of diagnostic test accuracy. Ann Intern Med. 2008; 149(12):889-97. PMC: 2956514. DOI: 10.7326/0003-4819-149-12-200812160-00008. View

3.
Soriano J, Molina J, Miravitlles M . Combining case-finding methods for COPD in primary care: a large, two-stage design study. Int J Tuberc Lung Dis. 2018; 22(1):106-111. DOI: 10.5588/ijtld.17.0334. View

4.
Sogbetun F, Eschenbacher W, Welge J, Panos R . A comparison of five surveys that identify individuals at risk for airflow obstruction and chronic obstructive pulmonary disease. Respir Med. 2016; 120:1-9. DOI: 10.1016/j.rmed.2016.09.010. View

5.
Singh D, Agusti A, Anzueto A, Barnes P, Bourbeau J, Celli B . Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease: the GOLD science committee report 2019. Eur Respir J. 2019; 53(5). DOI: 10.1183/13993003.00164-2019. View