Clinical validation of the Rapid Cough Questionnaire across diverse lung diseases

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Abstract
Background: The Rapid Cough Questionnaire (RCQ) is a simplified three-item instrument developed as a pragmatic alternative to the Leicester Cough Questionnaire (LCQ). However, its performance across diverse respiratory diseases, particularly structural lung diseases, has not been sufficiently validated. This study evaluated the performance of the RCQ across major respiratory disease subgroups. Methods: A total of 300 adult patients with chronic cough were prospectively enrolled from multiple respiratory centres. Participants completed five cough-specific instruments: Numeric Rating Scale (NRS), Cough Symptom Score (CSS), COugh Assessment Test (COAT), LCQ and RCQ. Construct validity was evaluated using correlation analyses across disease subgroups, including chronic obstructive pulmonary disease, asthma, idiopathic pulmonary fibrosis (IPF) and bronchiectasis. Results: The RCQ showed strong correlations with the LCQ (r=0.93), COAT (r=−0.75), CSS (r=−0.62) and NRS (r=−0.59). These relationships remained robust among all aetiologies, with the correlation coefficients between RCQ and LCQ exceeding 0.88 in each subgroup. Bland-Altman plots and an intraclass correlation analysis indicated a high level of concordance between the RCQ and LCQ scores. The RCQ aligned closely with multidimensional symptom burden and maintained strong correlation with the LCQ even for IPF, where LCQ correlations with unidimensional tools (NRS or CSS) were attenuated. Conclusions: The RCQ demonstrated strong cross-sectional concordance with the LCQ across heterogeneous respiratory conditions. Its brevity and consistent performance support its suitability in routine clinical practice and large-scale or longitudinal research settings. Further studies are warranted to evaluate its responsiveness and longitudinal performance.
Funding Information
  • National Research Foundation of Korea (RS-2024-00359875)
  • Korean Academy of Tuberculosis and Respiratory Disease (KATRD-S-2023-1)

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