Clinical phenotyping and inflammatory biomarkers of asthma-COPD overlap: a cross-sectional, single-center study in China.

BACKGROUND

Asthma-COPD overlap (ACO) lacks unified diagnostic criteria. We aimed to comprehensively phenotype ACO and identify independent predictors and inflammatory biomarkers.

METHODS

In this cross-sectional, single-center study, 120 hospitalized patients were prospectively enrolled and classified into asthma (n = 40), ACO (n = 40), and COPD (n = 40) according to GINA 2023 and GOLD 2023 criteria. Demographics, lung function, fractional exhaled nitric oxide (FeNO), quantitative high-resolution computed tomography (HRCT) parameters, and systemic and airway inflammatory biomarkers were compared. Multivariable logistic regression was performed to identify independent predictors of ACO. A composite predictive score derived from eight variables was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

ACO patients demonstrated intermediate clinical, inflammatory, and structural characteristics between asthma and COPD. Multivariable analysis identified male sex, age, airway wall area percentage (WA%), pulmonary artery systolic pressure (PASP), FeNO, blood eosinophil count, serum IgE, and sputum eosinophil percentage as independent predictors of ACO. The combined predictive model showed excellent discriminative performance, with an area under the ROC curve (AUC) of 0.94 (95% CI 0.939-0.969, p < 0.001).

CONCLUSIONS

ACO exhibits a distinct intermediate inflammatory and structural phenotype. An integrated model combining clinical features, imaging metrics, and inflammatory biomarkers provides high diagnostic accuracy and may facilitate early identification and personalized anti-inflammatory treatment.