Euro-HDB – the first large, comprehensive European study on the burden of Huntington’s disease

Euro-HDB – the first large, comprehensive European study on the burden of Huntington’s disease

2009 3rd Annual Huntington Disease Clinical Research Symposium (HDCRS), November 21, 2009, Baltimore, Maryland, USA

Dorey, J. | Tedroff, J. | Lamure, M. | Toumi, M. | Volume: , Issue: , Pages: , disease burden, Huntington Disease,

Background
Understanding the determinants of health-related quality of life (HR-QoL) and cost is critical for medical doctors, health policy makers, and payers to guide management of disease. We initiated a large observational study to collect information on clinical characteristics, HR-QoL, and healthcare resource utilizations in France, Germany, Italy, Spain, Sweden, and the UK. The main aim of the study is to evaluate the cost of illness associated with Huntington’s disease from various perspectives.

Methods
Patients with Huntington’s disease are recruited through patient support organizations. The Huntington Self Assessment Instrument (HSAI), a fully self-reported patient questionnaire, has been developed and is complimented with SF-36 and EQ-5D questionnaires, the Zarit caregiver burden scale, and the Hospital Anxiety and Depression Scale (HADS) questionnaire. A country-specific medical cost dictionary will be developed, listing all unit costs for healthcare resource utilizations. Indirect costs associated with loss of productivity will be calculated using appropriate costing models for human capital methodology and all other aspects specific to Huntington’s disease. The total cost of management from societal, health insurance, and patient perspectives will be calculated by multiplying resource utilizations by unit cost. Modeling of total costs will include presumed covariables and significant covariates from patients’ socio-demographics using the Manning’s algorithm, in order to identify the drivers of the various costs, depending on the perspective. Both kurtosis and heteroscedasticity will determine which model is to be used, and where the general linear model is chosen, the variance function will be selected using the Park test. Utility will be calculated using the self-reported EQ-5D questionnaire. The drivers of the utility will be identified using a classical ANOVA technique.

Conclusions
This study will provide valuable information for medical doctors, health policy makers, and payers to guide healthcare decisions.