Prediction of Treatment Response in Patients with Chronic Obstructive Pulmonary Disease by Determination of Airway Dimensions with Baseline Computed Tomography

Objective: To determine the predictive factors for treatment responsiveness in patients with chronic obstructive pulmonary disease (COPD) at 1-year follow-up by performing quantitative analyses of baseline CT scans. Materials and Methods: COPD patients (n = 226; 212 men, 14 women) were recruited from the Korean Obstructive Lung Disease cohort. Patients received a combination of inhaled long-acting beta-agonists and corticosteroids twice daily for 3 months and subsequently received medications according to the practicing clinician's decision. The emphysema index, air-trapping indices, and airway parameter (Pi10), calculated using both full-width-half-maximum and integral-based half-band (IBHB) methods, were obtained with baseline CT scans. Clinically meaningful treatment response was defined as an absolute increase of >= 0.225 L in the forced expiratory volume in 1 second (FEV1) at the one-year follow-up. Multivariate logistic regression analysis was performed to investigate the predictors of an increase in FEV1, and receiver operating characteristic (ROC) analysis was performed to evaluate the performance of the suggested models. Results: Treatment response was noted in 47 patients (20.8%). The mean FEV1 increase in responders was 0.36 +/- 0.10 L. On univariate analysis, the air-trapping index (ATI) obtained by the subtraction method, ATI of the emphysematous area, and IBHB-measured Pi10 parameter differed significantly between treatment responders and non-responders (p = 0.048, 0.042, and 0.002, respectively). Multivariate analysis revealed that the IBHB-measured Pi10 was the only independent variable predictive of an FEV1 increase (p = 0.003). The adjusted odds ratio was 1.787 (95% confidence interval: 1.220-2.619). The area under the ROC curve was 0.641. Conclusion: Measurement of standardized airway dimensions on baseline CT by using a recently validated quantification method can predict treatment responsiveness in COPD patients.