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

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 aged 40-79 years who participated in NHANES 2007-2012 and underwent spirometry. We considered participants "true" COPD cases if their ratio of post-bronchodilator 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 agradient 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%-16%, sensitivity ranging from 18%-35%, and specificity ranging from 88%-92%. The new definition classified participants based on age, bronchodilator use, 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%-5%, and we attained good specificity (96%) at the expense of sensitivity (9-10%). CONCLUSIONS: Our results can be used to parametrize misclassification assumptions for quantitative bias analysis when pulmonary function data are unavailable.