Rescaled Value Set Regressions: Making the Nonparametric Crosswalk Between EQ-5D-5L and EQ-5D-3L More Transparent

Objectives: Introduce the rescaled value set regression for estimating EQ-5D-5L health state values as an alternative way to report the nonparametric crosswalk.

Methods: The rescaled value set regression and the nonparametric crosswalk methods were applied to estimate EQ-5D-5L state values from EQ-5D-3L value sets for 3 example countries (United Kingdom, The Netherlands, and Spain). The rescaled value set regression converted the original 3-level value set regression parameters comprising dichotomous independent variables into regression parameters for the 5-level version. The health state values for 28 common EQ-5D-5L response profiles were then estimated by the rescaled value set regression and nonparametric crosswalk to assess whether they produced the same results using value sets from the 3 different countries.

Results: When applied to EQ-5D-3L value sets, the rescaled value set regression demonstrated that a level-2 response and level-3 response using the EQ-5D-3L, respectively, corresponded with a level-3 response and level-5 response using the EQ-5D-5L. The analysis of 28 common EQ-5D-5L response profiles produced identical health state values for the United Kingdom, The Netherlands, and Spain’s value sets under both the rescaled value set regression and nonparametric crosswalk.

Conclusions: The rescaled value set regression provides improved transparency than the nonparametric crosswalk when estimating EQ-5D-5L health state values anchored to EQ-5D-3L value sets. Both methods may be used in combination for jurisdictions where new EQ-5D-5L valuation studies are not planned but a relevant EQ-5D-3L value set is available.