Validation of Questionnaire-based Case Definitions for Chronic Obstructive Pulmonary Disease

Epidemiology - Tập 31 Số 3 - Trang 459-466 - 2020
Lydia Feinstein1,2,3,4,5,6,7, Jesse Wilkerson1,3,4,5,6,7, Päivi M. Salo1,8,4,5,6,7, Nathaniel MacNell1,3,4,5,6,7, Matthew F. Bridge1,3,4,5,6,7, Michael B. Fessler1,8,4,5,6,7, Peter S. Thorne1,9,4,5,6,7, Angelico Mendy1,9,8,4,5,6,7, Richard D. Cohn1,10,3,4,5,6,7, Matthew D. Curry1,3,4,5,6,7, Darryl C. Zeldin1,8,4,5,6,7
1All data used in this analysis are publicly available and can be downloaded on the Centers for Disease Control web site: https://wwwn.cdc.gov/nchs/nhanes/Default.aspx. SAS code used in this analysis is provided in eAppendix 2
2Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
3Social & Scientific Systems, Durham, NC
4Submitted August 19, 2019
5Supplemental Digital Content (https://links.lww.com/EDE/B642).
6Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com).
7accepted January 29, 2020.
8Division of Intramural Research, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC
9Department of Occupational and Environmental Health, University of Iowa, Iowa City, Iowa
10Independent Consultant, Chapel Hill, NC

Tóm tắt

Background: Various questionnaire-based definitions of chronic obstructive pulmonary disease (COPD) have been applied using the US representative National Health and Nutrition Examination Survey (NHANES), but few have been validated against objective lung function data. We validated two prior definitions that incorporated self-reported physician diagnosis, respiratory symptoms, and/or smoking. We also validated a new definition that we developed empirically using gradient boosting, an ensemble machine learning method. Methods: Data came from 7,996 individuals 40–79 years who participated in NHANES 2007–2012 and underwent spirometry. We considered participants “true” COPD cases if their ratio of postbronchodilator forced expiratory volume in 1 second to forced vital capacity was below 0.7 or the lower limit of normal. We stratified all analyses by smoking history. We developed a gradient boosting model for smokers only; predictors assessed (25 total) included sociodemographics, inhalant exposures, clinical variables, and respiratory symptoms. Results: The spirometry-based COPD prevalence was 26% for smokers and 8% for never smokers. Among smokers, using questionnaire-based definitions resulted in a COPD prevalence ranging from 11% to 16%, sensitivity ranging from 18% to 35%, and specificity ranging from 88% to 92%. The new definition classified participants based on age, bronchodilator use, body mass index (BMI), smoking pack-years, and occupational organic dust exposure, and resulted in the highest sensitivity (35%) and specificity (92%) among smokers. Among never smokers, the COPD prevalence ranged from 4% to 5%, and we attained good specificity (96%) at the expense of sensitivity (9-10%). Conclusion: Our results can be used to parametrize misclassification assumptions for quantitative bias analysis when pulmonary function data are unavailable.

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Tài liệu tham khảo

Barr, 2002, Validation of self-reported chronic obstructive pulmonary disease in a cohort study of nurses., Am J Epidemiol, 155, 965, 10.1093/aje/155.10.965

Liu, 2014, The association of chronic obstructive pulmonary disease, disability, engagement in social activities, and mortality among US adults aged 70 years or older, 1994-2006., Int J Chron Obstruct Pulmon Dis, 9, 75, 10.2147/COPD.S53676

Martinez, 2014, Chronic obstructive pulmonary disease, cognitive impairment, and development of disability: the health and retirement study., Ann Am Thorac Soc, 11, 1362, 10.1513/AnnalsATS.201405-187OC

Mendy, 2018, House dust endotoxin association with chronic bronchitis and emphysema., Environ Health Perspect, 126, 037007, 10.1289/EHP2452

Cheruvu, 2016, Health-related quality of life in current smokers with COPD: factors associated with current smoking and new insights into sex differences., Int J Chron Obstruct Pulmon Dis, 11, 2211, 10.2147/COPD.S106207

Ford, 2013, Trends in the prevalence of obstructive and restrictive lung function among adults in the United States: findings from the National Health and Nutrition Examination surveys from 1988-1994 to 2007-2010., Chest, 143, 1395, 10.1378/chest.12-1135

Fragoso, 2011, Staging the severity of chronic obstructive pulmonary disease in older persons based on spirometric Z-scores., J Am Geriatr Soc, 59, 1847, 10.1111/j.1532-5415.2011.03596.x

Hankinson, 1999, Spirometric reference values from a sample of the general U.S. population., Am J Respir Crit Care Med, 159, 179, 10.1164/ajrccm.159.1.9712108

Martinez, 2015, Undiagnosed obstructive lung disease in the United States. Associated factors and long-term mortality., Ann Am Thorac Soc, 12, 1788, 10.1513/AnnalsATS.201506-388OC

Tilert, 2013, Estimating the U.S. prevalence of chronic obstructive pulmonary disease using pre- and post-bronchodilator spirometry: the National Health and Nutrition Examination Survey (NHANES) 2007-2010., Respir Res, 14, 103, 10.1186/1465-9921-14-103

Tilert, 2018, Prevalence and factors associated with self-reported chronic obstructive pulmonary disease among adults aged 40-79: the National Health and Nutrition Examination Survey (NHANES) 2007-2012., EC Pulmonol Respir Med, 7, 650

Busse, 2013, Characteristics of allergic sensitization among asthmatic adults older than 55 years: results from the National Health and Nutrition Examination Survey, 2005-2006., Ann Allergy Asthma Immunol, 110, 247, 10.1016/j.anai.2013.01.016

Fessler, 2017, House dust endotoxin and peripheral leukocyte counts: results from two large epidemiologic studies., Environ Health Perspect, 125, 057010, 10.1289/EHP661

Fox, 2009, Creating a demand for bias analysis in epidemiological research., J Epidemiol Community Health, 63, 91, 10.1136/jech.2008.082420

Greenland, 1996, Basic methods for sensitivity analysis of biases., Int J Epidemiol, 25, 1107, 10.1093/ije/25.6.1107

Jurek, 2009, Specifying exposure classification parameters for sensitivity analysis: family breast cancer history., Clin Epidemiol, 1, 109, 10.2147/CLEP.S5755

Lash, 2014, Good practices for quantitative bias analysis., Int J Epidemiol, 43, 1969, 10.1093/ije/dyu149

Lash, 2016, EPIDEMIOLOGY Announces the “Validation Study” Submission Category., Epidemiology, 27, 613, 10.1097/EDE.0000000000000532

Ntritsos, 2018, Gender-specific estimates of COPD prevalence: a systematic review and meta-analysis., Int J Chron Obstruct Pulmon Dis, 13, 1507, 10.2147/COPD.S146390

Friedman, 2001, Greedy function approximation: a gradient boosting machine., Ann Statist, 29, 1189, 10.1214/aos/1013203451

Zhang, 2019, Predictive analytics with gradient boosting in clinical medicine., Ann Transl Med, 7, 152, 10.21037/atm.2019.03.29

Naimi, 2018, Machine learning for fetal growth prediction., Epidemiology, 29, 290, 10.1097/EDE.0000000000000788

Nanayakkara, 2018, Characterising risk of in-hospital mortality following cardiac arrest using machine learning: a retrospective international registry study., PLoS Med, 15, e1002709, 10.1371/journal.pmed.1002709

Setodji, 2017, The right tool for the job: choosing between covariate-balancing and generalized boosted model propensity scores., Epidemiology, 28, 802, 10.1097/EDE.0000000000000734

Chubak, 2012, Tradeoffs between accuracy measures for electronic health care data algorithms., J Clin Epidemiol, 65, 343, 10.1016/j.jclinepi.2011.09.002

Martinez, 2008, Development and initial validation of a self-scored COPD Population Screener Questionnaire (COPD-PS)., COPD, 5, 85, 10.1080/15412550801940721

Hanania, 2010, Predicting risk of airflow obstruction in primary care: validation of the lung function questionnaire (LFQ)., Respir Med, 104, 1160, 10.1016/j.rmed.2010.02.009

Weiss, 2017, Development and validation of the Salzburg COPD-screening questionnaire (SCSQ): a questionnaire development and validation study., NPJ Prim Care Respir Med, 27, 4, 10.1038/s41533-016-0005-7

Almagro, 2017, Underdiagnosis in COPD: a battle worth fighting., Lancet Respir Med, 5, 367, 10.1016/S2213-2600(17)30133-9

Hill, 2010, Prevalence and underdiagnosis of chronic obstructive pulmonary disease among patients at risk in primary care., CMAJ, 182, 673, 10.1503/cmaj.091784

Lamprecht, 2015, Determinants of underdiagnosis of COPD in national and international surveys., Chest, 148, 971, 10.1378/chest.14-2535

Murgia, 2014, Validity of a questionnaire-based diagnosis of chronic obstructive pulmonary disease in a general population-based study., BMC Pulm Med, 14, 49, 10.1186/1471-2466-14-49

Barker, 1991, Relation of birth weight and childhood respiratory infection to adult lung function and death from chronic obstructive airways disease., BMJ, 303, 671, 10.1136/bmj.303.6804.671

Lamprecht, 2011, COPD in never smokers: results from the population-based burden of obstructive lung disease study., Chest, 139, 752, 10.1378/chest.10-1253

Prescott, 1999, Socioeconomic status, lung function and admission to hospital for COPD: results from the Copenhagen City Heart Study., Eur Respir J, 13, 1109, 10.1034/j.1399-3003.1999.13e28.x

Fuller-Thomson, 2016, COPD in a population-based sample of never-smokers: interactions among sex, gender, and race., Int J Chronic Dis, 2016, 5862026

Salvi, 2009, Chronic obstructive pulmonary disease in non-smokers., Lancet, 374, 733, 10.1016/S0140-6736(09)61303-9

Schneider, 2009, Diagnostic accuracy of spirometry in primary care., BMC Pulm Med, 9, 31, 10.1186/1471-2466-9-31

Coxson, 2014, Using pulmonary imaging to move chronic obstructive pulmonary disease beyond FEV1., Am J Respir Crit Care Med, 190, 135, 10.1164/rccm.201402-0256PP

de Marco, 2004, An international survey of chronic obstructive pulmonary disease in young adults according to GOLD stages., Thorax, 59, 120, 10.1136/thorax.2003.011163

Borlée, 2017, Spirometry, questionnaire and electronic medical record based COPD in a population survey: comparing prevalence, level of agreement and associations with potential risk factors., PLoS One, 12, e0171494, 10.1371/journal.pone.0171494