How important is parameter uncertainty around the UK EQ-5D-3L value set when estimating treatment effects

Aims: The uncertainty around the EQ-5D-3L value set is commonly ignored in economic evaluation. This study evaluates the impact of including parameter uncertainty around the original UK EQ-5D-3L value set (or “tariff”) within standard errors as well as sampling uncertainty around the trial population. Methods: First, we re-estimated the N3 model of the EQ-5D-3L value set with original data from the Measurement and Valuation of Health (MVH) study to replicate the published coefficients. Second, we estimated standard errors around the predicted utility of each EQ-5D-3L health state to evaluate the impact of parameter uncertainty on these estimated utilities. Third, we used a two-stage bootstrap approach to combine the resulting MVH parameter uncertainty with trial sampling uncertainty for a large randomised trial population. In the first step, we generated 1,000 sets of coefficients for the UK EQ-5D-3L tariff using bootstrap resampling from the original MVH sample. In the second step, we used bootstrap resampling from the clinical trial data 10,000 times for each of the 1,000 sets of EQ-5D tariff coefficients. The standard error including MVH parameter uncertainty was then estimated as the standard deviation across the resulting vector of results from the 10 million bootstrap replicates. This figure was compared against a one-stage bootstrap from the clinical trial sample to assess the impact of including parameter uncertainty. Data: The EQ-5D N3 model was estimated using the original MVH data. The randomised control trial used as a case study was the International Subarachnoid Aneurysm Trial (ISAT), a large clinical trial comparing …