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Health state utilities associated with attributes of migraine preventive treatments based on patient and general population preferences

Research output: Contribution to journalArticle

Louis S. Matza, Kristen A. Deger, Pamela Vo, Farooq Maniyar, Peter J. Goadsby

Original languageEnglish
Pages (from-to)2359-2372
Number of pages14
JournalQuality of Life Research
Issue number9
Publication statusPublished - 15 Sep 2019

King's Authors


Purpose: While previous studies have estimated health state utilities associated with migraine severity and frequency, migraine treatments vary in other ways that may have an impact on patients’ quality of life, preference, and utility. The purpose of this study was to estimate utilities associated with migraine treatment attributes including route of administration and treatment-related adverse events (AEs). Methods: In time trade-off interviews, migraine patients and general population participants in the UK valued health state vignettes drafted based on literature, medication labels, and clinician interviews. All respondents valued migraine health states varying in route of administration. Each participant also valued eight health states (randomly selected from a total of 15) that added the description of an AE to a migraine health state. Results: A total of 400 participants completed interviews (200 general population [49.0% female; mean age = 43.6 years]; 200 migraine patients [74.5% female; mean age = 45.8 years]). In the general population sample, mean utilities of health states without aura were 0.79 with daily oral medication, 0.78 with one injection per month, and 0.72 with 31–39 injections once every 3 months. The greatest disutilities (i.e., decreases in utility) were for AEs associated with oral medications (e.g., − 0.060 [fatigue] and − 0.098 [brain fog]). Differences among health states followed the same pattern in the patient sample as in the general population sample. Conclusions: Utilities estimated from the general population sample may be used to represent route of administration and AEs in cost-utility models. Results from the patient sample indicate that these treatment characteristics have an impact on patient preference.

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