Diffusing Capacity as a Predictor of Hospitalizations in a Clinical Cohort of Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) hospitalizations are a major burden on patients. Diffusing capacity of the lung for carbon monoxide (Dl_CO) is a potential predictor that has not been studied in large cohorts. Objectives: This study used electronic health record data to evaluate whether clinically obtained Dl_CO predicts COPD hospitalizations. Methods: We performed time-to-event analyses of individuals with COPD and Dl_CO measurements from the Johns Hopkins COPD Precision Medicine Center of Excellence. Cox proportional hazard methods were used to model time from Dl_CO measurement to first COPD hospitalization and composite first hospitalization or death, adjusting for age, sex, race, body mass index, smoking status, forced expiratory volume in 1 second (FEV₁), history of prior COPD hospitalization, and comorbidities. To identify the utility of including Dl_CO in risk models, area under the receiver operating curve (AUC) values were calculated for models with and without Dl_CO. Results were externally validated in a separate analogous cohort. Results: Of 2,793 participants, 368 (13%) had a COPD hospitalization within 3 years. In adjusted analyses, for every 10% decrease in Dl_CO% predicted, risk of COPD hospitalization increased by 10% (hazard ratio, 1.1; 95% confidence interval, 1.1-1.2; P < 0.001). Similar associations were observed for COPD hospitalizations or death. The model including demographics, comorbidities, FEV₁, Dl_CO, and prior COPD hospitalizations performed well, with an AUC of 0.85 and an AUC of 0.84 in an external validation cohort. Conclusions: Diffusing capacity is a strong predictor of COPD hospitalizations in a clinical cohort of individuals with COPD, independent of airflow obstruction and prior hospitalizations. These findings support incorporation of Dl_CO in risk assessment of patients with COPD.