Stepwise web-based questionnaires for diagnosing cluster headache: LUCA and QATCH

Abstract

Background: Cluster headache (CH) is a primary headache disorder that is diagnosed based on the patients history. For large-scale epidemiologic and genetic studies, a web-based, preferably short, questionnaire can be a feasible alternative to replace time-consuming clinical interviews. Methods: Self-reported CH patients were enrolled via our research website. Participants meeting screening criteria were directed to the Leiden University Cluster headache Analysis program (LUCA) questionnaire. Individual diagnoses were calculated using an algorithm based on International Headache Society criteria. Subsequently, semi-structured telephone interviews were carried out to validate the LUCA questionnaire. The shorter Quick Ascertainment of Cluster Headache (QATCH) questionnaire for diagnosing CH was constructed by using logistic regression to select the most predictive questions. Results: Via our website 437 self-reported CH patients were recruited. Of these, 291 patients were included in this crosssectional study. The LUCA questionnaire was valid and accurate. Using logistic regression, three questions (QATCH) provided similar sensitivity (53.8% vs. 57.2%), specificity (88.9% vs. 87.5%), positive predictive value (95.5% vs. 95.9%) and negative predictive value (30.8% vs. 28.8%) compared with the LUCA questionnaire. Conclusion: The web-based LUCA questionnaire was accurate and reliable in diagnosing CH among self-reported patients. Males with headache attacks of short duration and long headache-free intervals (months to years) are very likely to have CH. © 2013 International Headache Society.