OBJECTIVES: Fabry disease is a rare inherited disorder caused by deficiency of the enzyme α-galactosidase A. Effective therapies are available, currently these are administered intravenously (IV), however a new oral treatment has been developed. This study was designed to estimate the value that people place on different aspects of oral and IV therapies and to elicit health state utilities for quality adjusted life years (QALY). METHODS: A stated preference discrete choice experiment (DCE) was designed to assess the importance of different treatment attributes for Fabry disease. The attributes included overall survival, mode of administration, treatment related reactions, treatment related headaches and risk of antibody formation. Standard DCE methods were employed. A UK general public sample was recruited. The mixed logit model estimated strength of preference for the attributes. Disutilities were also estimated for changes in each attribute based upon marginal rates of substitution with survival and individual predicted overall survival. RESULTS: The sample (n=506) were broadly representative of UK demographics. Participants preferred treatments that were associated with longer life expectancy (each additional year the odds ratio (OR) of preferring a treatment =1.574; 95%CI: 1.504-1.647). Participants preferred an every other day tablet compared to an infusion (OR=2.262; 95%CI: 2.075-2.463). Participants also chose to avoid treatments with headaches and treatment reactions. Estimated disutilities included headaches 12 times a year (-0.047), self-administered infusion (-0.0543) and treatment reactions 12 times a year (-0.0361). CONCLUSIONS: Participants strongly preferred to avoid any loss of overall survival, they also placed significant value on moving to oral administration from IV, avoiding treatment related reactions, avoiding headaches and also avoiding antibody formation. The general public sample supported the estimation of utilities for QALY calculation. Does this methodology represent an alternative mechanism for estimating QALY utilities for rare diseases where collection of EQ-5D data can be very challenging?