Development and validation of a nomogram to predict pulmonary function and the presence of chronic obstructive pulmonary disease in a Korean population

BACKGROUND: Early suspicion followed by assessing lung function with spirometry could decrease the underdiagnosis of chronic obstructive pulmonary disease (COPD) in primary care. We aimed to develop a nomogram to predict the FEV(1)/FVC ratio and the presence of COPD. METHODS: We retrospectively reviewed the data of 4241 adult patients who underwent spirometry between 2013 and 2019. By linear regression analysis, variables associated with FEV(1)/FVC were identified in the training cohort (n = 2969). Using the variables as predictors, a nomogram was created to predict the FEV(1)/FVC ratio and validated in the test cohort (n = 1272). RESULTS: Older age (β coefficient [95% CI], − 0.153 [− 0.183, − 0.122]), male sex (− 1.904 [− 2.749, − 1.056]), current or past smoking history (− 3.324 [− 4.200, − 2.453]), and the presence of dyspnea (− 2.453 [− 3.612, − 1.291]) or overweight (0.894 [0.191, 1.598]) were significantly associated with the FEV(1)/FVC ratio. In the final testing, the developed nomogram showed a mean absolute error of 8.2% between the predicted and actual FEV(1)/FVC ratios. The overall performance was best when FEV(1)/FVC < 70% was used as a diagnostic criterion for COPD; the sensitivity, specificity, and balanced accuracy were 82.3%, 68.6%, and 75.5%, respectively. CONCLUSION: The developed nomogram could be used to identify potential patients at risk of COPD who may need further evaluation, especially in the primary care setting where spirometry is not available.