A Comparative Study of Type 2 Inflammatory Biomarkers Combined with Small Airway Parameters for Diagnosing Cough-Variant Asthma

Background: The diagnosis of cough-variant asthma (CVA) traditionally relies on clinical manifestations and bronchial provocation test (BPT). However, the BPT can be costly and complex, and poses risks of severe bronchospasm. Most CVA patients exhibit type 2 airway inflammation and small airway dysfunction. Identifying practical biomarkers such as total immunoglobulin E (tIgE), percentage of eosinophil cell count in induced sputum (sEOS%), peripheral blood eosinophil count (PBEC), and fractional exhaled nitric oxide (FeNO) may enhance the diagnostic process for cough-variant asthma. Objective: This study aims to evaluate and compare the diagnostic utility of T2 inflammatory biomarkers combined with small airway parameters for diagnosing CVA. Methods: This was a single-center, cross-sectional diagnostic study including 211 patients with chronic cough. Participants underwent spirometry, FeNO measurement, and assessment of eosinophilic inflammation, including sEOS%, PBEC, and tIgE. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of individual parameters and combined models. Results: CVA was diagnosed in 27.5% of patients. Compared with non-CVA patients, those with CVA showed significantly higher levels of T2 inflammatory biomarkers and reduced small airway function. Among individual biomarkers, FeNO demonstrated the highest diagnostic accuracy (AUC = 0.79), followed by sEOS% (AUC = 0.75), tIgE (AUC = 0.71), and PBEC (AUC = 0.66). Among small airway parameters, FEF 50% showed the best performance (AUC = 0.79). Combined models significantly improved diagnostic accuracy, with FEF 50% combined with FeNO or sEOS%, achieving the highest AUC (0.82). Correlation analysis revealed that higher inflammatory biomarker levels were associated with reduced small airway function. Conclusion: The combination of T2 inflammatory biomarkers and small airway function parameters improves the diagnostic accuracy for CVA. This approach may provide a practical and non-invasive strategy for identifying CVA, particularly in settings where bronchial provocation testing is not readily available.