F26 Quality-adjusted life-years (QALYS) and huntington’s disease

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BackgroundAlthough the impacts of Huntington’s Disease (HD) are substantial and life-changing, with wider impacts across the care and support network, there has been little research reporting on the health-related quality of life of people with the condition in a manner that can used in economic evaluations of treatments for HD. Health state utility values (HSUVs), used to calculate quality-adjusted life-years (QALYs), are the metric commonly used to inform such healthcare policy decision-making.ObjectivesThe aim was to report HSUVs for HD, in order to: i) describe HSUVs by demographic and clinical characteristics ii) compare HSUVs of people with HD in the UK with population norms; iii) identify the relative strength of demographic/clinical characteristics in predicting HSUVs.MethodsData from the EHDN REGISTRY were used for analysis. EHDN collects six-monthly demographic, clinical and patient-reported outcome measures, including the SF-36. SF-36 scores were converted to SF-6D HSUVs, described by demographic and clinical characteristics, and compared with population norms for UK respondents. Regression analysis was used to estimate the relative strength of age, gender, time since diagnosis, and disease severity (Total Function Capacity [TFC] score, and UHDRS’s Motor, Behavioural and Cognitive score) in predicting HSUVs.ResultsData used were from 11,328 questionnaires completed by 5,560 respondents across 12 European countries. Women generally had lower HSUVs than men, HSUVs were consistently lower than population norms for those with HD in the UK, and dropped with increasing disease severity. The regression model significantly accounted for variance in HSUVs (n=1,939; F[7,1931]=120.05; p<0.001; adjusted R-squared 0.3007), with Behaviour and TFC scores, and male gender significant predictors (p<0.001).ConclusionTo our knowledge, this is the first report of HSUVs for HD for countries other than the UK, and the first report of SF-6D HSUVs described for 12 European countries, according to demographic and clinical factors. Analyses provide new insights into the relationships between HD disease characteristics and assessment of health-related quality of life in a form that can be used in policy-relevant economic evaluations.

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