Development and validation of a nomogram for predicting COPD: A nationwide population-based study in South Korea.

Abstract

Chronic obstructive pulmonary disease (COPD) remains a significant global health burden exacerbated by tobacco smoking, occupational exposure, and air pollution. COPD is one of the top 3 causes of death worldwide. In South Korea, the COPD burden is expected to increase due to ongoing exposure to risk factors and the aging population. COPD is extensively underdiagnosed or underestimated, owing to a lack of public awareness. This study aimed to develop and validate a nomogram for COPD by using national data to promote early diagnosis and intervention. This study drew on a dataset from the 7th Korea National Health and Nutrition Examination Survey from 2016 to 2018, including 10,819 subjects aged 40 years or older with spirometry results. Influence of demographic, socioeconomic, and health-related factors on the incidence. Multivariable logistic regression was used to identify the significant predictors of the nomogram. The nomogram was validated using receiver operating characteristic curves, calibration plots, and concordance index (C-index). Internal validation was performed by bootstrapping. In the final analysis, 1059 (14.0%) participants had COPD. Key risk factors associated with increased COPD risk included being male, aged 70 and older, lower educational level, living in a rural area, current smoking status, underweight, and history of tuberculosis and asthma. The area under the curve (AUC) of the model was 0.822 (95% CI: 0.810-0.832), indicating that the nomogram has a high ability to identify COPD. The nomogram demonstrated solid predictive performance, as confirmed by calibration plots with a C-index (of 0.822) for the validation set with 1000 bootstrap samples. In conclusion, we developed a tool for the early detection of COPD with good properties in primary care settings, without spirometry. Appropriate and early diagnosis of COPD can have a crucial impact on public health.