The European respiratory journal · 2022
Derivation and validation of the UCAP-Q case-finding questionnaire to detect undiagnosed asthma and COPD.
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Huynh Chau, Whitmore G A, Vandemheen Katherine L, FitzGerald J Mark, Bergeron Celine, Boulet Louis-Philippe, Cote Andreanne, Field Stephen K, Penz Erika, McIvor R Andrew, Lemière Catherine, Gupta Samir, Mayers Irvin, Bhutani Mohit, Hernandez Paul, Lougheed M Diane, Licskai Christopher J, Azher Tanweer, Ainslie Martha, Fraser Ian, Mahdavian Masoud, Alvarez Gonzalo G, Kendzerska Tetyana, Aaron Shawn D
Аннотация
BACKGROUND: Many people with asthma and COPD remain undiagnosed. We developed and validated a new case-finding questionnaire to identify symptomatic adults with undiagnosed obstructive lung disease.
METHODS: Adults in the community with no prior history of physician-diagnosed lung disease who self-reported respiratory symptoms were contacted via random-digit dialling. Pre- and post-bronchodilator spirometry was used to confirm asthma or COPD. Predictive questions were selected using multinomial logistic regression with backward elimination. Questionnaire performance was assessed using sensitivity, predictive values and area under the receiver operating characteristic curve (AUC). The questionnaire was assessed for test-retest reliability, acceptability and readability. External validation was prospectively conducted in an independent sample and predictive performance re-evaluated.
RESULTS: A 13-item Undiagnosed COPD and Asthma Population Questionnaire (UCAP-Q) case-finding questionnaire to predict undiagnosed asthma or COPD was developed. The most appropriate risk cut-off was determined to be 6% for either disease. Applied to the derivation sample (n=1615), the questionnaire yielded a sensitivity of 92% for asthma and 97% for COPD; specificity of 17%; and an AUC of 0.69 (95% CI 0.64-0.74) for asthma and 0.82 (95% CI 0.78-0.86) for COPD. Prospective validation using an independent sample (n=471) showed sensitivities of 93% and 92% for asthma and COPD, respectively; specificity of 19%; with AUCs of 0.70 (95% CI 0.62-0.79) for asthma and 0.81 (95% CI 0.74-0.87) for COPD. AUCs for UCAP-Q were higher compared to AUCs for currently recommended case-finding questionnaires for asthma or COPD.
CONCLUSIONS: The UCAP-Q demonstrated high sensitivities and AUCs for identifying undiagnosed asthma or COPD. A web-based calculator allows for easy calculation of risk probabilities for each disease.
METHODS: Adults in the community with no prior history of physician-diagnosed lung disease who self-reported respiratory symptoms were contacted via random-digit dialling. Pre- and post-bronchodilator spirometry was used to confirm asthma or COPD. Predictive questions were selected using multinomial logistic regression with backward elimination. Questionnaire performance was assessed using sensitivity, predictive values and area under the receiver operating characteristic curve (AUC). The questionnaire was assessed for test-retest reliability, acceptability and readability. External validation was prospectively conducted in an independent sample and predictive performance re-evaluated.
RESULTS: A 13-item Undiagnosed COPD and Asthma Population Questionnaire (UCAP-Q) case-finding questionnaire to predict undiagnosed asthma or COPD was developed. The most appropriate risk cut-off was determined to be 6% for either disease. Applied to the derivation sample (n=1615), the questionnaire yielded a sensitivity of 92% for asthma and 97% for COPD; specificity of 17%; and an AUC of 0.69 (95% CI 0.64-0.74) for asthma and 0.82 (95% CI 0.78-0.86) for COPD. Prospective validation using an independent sample (n=471) showed sensitivities of 93% and 92% for asthma and COPD, respectively; specificity of 19%; with AUCs of 0.70 (95% CI 0.62-0.79) for asthma and 0.81 (95% CI 0.74-0.87) for COPD. AUCs for UCAP-Q were higher compared to AUCs for currently recommended case-finding questionnaires for asthma or COPD.
CONCLUSIONS: The UCAP-Q demonstrated high sensitivities and AUCs for identifying undiagnosed asthma or COPD. A web-based calculator allows for easy calculation of risk probabilities for each disease.