Zhihao Yang1, Nan Luo2, Gouke Bonsel3, Jan Busschbach4, Elly Stolk5. 1. Erasmus University Rotterdam, Rotterdam, The Netherlands; Guizhou Medical University, Guiyang, China. Electronic address: z.yang@erasmusmc.nl. 2. National University of Singapore, Singapore, Singapore. 3. Erasmus University Rotterdam, Rotterdam, The Netherlands; The EuroQol Office, Rotterdam, The Netherlands. 4. Erasmus University Rotterdam, Rotterdam, The Netherlands. 5. The EuroQol Office, Rotterdam, The Netherlands.
Abstract
OBJECTIVE: The current five-level EQ-5D (EQ-5D-5L) valuation protocol requires the valuation of 86 states. It has been demonstrated that the selection of empirically valued health states affects the extrapolated values in three-level EQ-5D (EQ-3D-3L). In this investigation, we aim to compare the performance of the current EQ-5D-5L valuation design with other designs. STUDY DESIGN: 1603 university students participated in a valuation study using a visual analog scale (VAS) to produce values for all EQ-5D-5L states. Different designs were generated to test their prediction accuracy. METHODS: Subsamples of the dataset were used to mimic data obtained from a particular design; the remaining dataset was used as the validation set. In addition to EuroQol Group Valuation Technology (EQ-VT) design, alternative subsamples and designs were created using random, orthogonal, and "optimizing D-efficiency" sampling methods. The root mean squared error (RMSE) was used as the measure of prediction accuracy. RESULTS: The EuroQol Group Valuation Technology (EQ-VT) design showed an average RMSE of 3.44 on EQ-VAS, for all 3125 health states combined. Notably, a 25-state orthogonal design performed similarly to the EQ-VT design, with a smaller RMSE of 3.40, and was thus the most efficient design. One caveat with respect to the orthogonal design was that it did not predict the mild states well. CONCLUSIONS: Our study supports the EQ-VT design. Smaller designs were identified with similar overall prediction accuracy. It is worth investigating whether issues with misprediction of mild states can be resolved, as the use of smaller size designs would reduce the cost of the valuation of EQ-5D-5L considerably.
OBJECTIVE: The current five-level EQ-5D (EQ-5D-5L) valuation protocol requires the valuation of 86 states. It has been demonstrated that the selection of empirically valued health states affects the extrapolated values in three-level EQ-5D (EQ-3D-3L). In this investigation, we aim to compare the performance of the current EQ-5D-5L valuation design with other designs. STUDY DESIGN: 1603 university students participated in a valuation study using a visual analog scale (VAS) to produce values for all EQ-5D-5L states. Different designs were generated to test their prediction accuracy. METHODS: Subsamples of the dataset were used to mimic data obtained from a particular design; the remaining dataset was used as the validation set. In addition to EuroQol Group Valuation Technology (EQ-VT) design, alternative subsamples and designs were created using random, orthogonal, and "optimizing D-efficiency" sampling methods. The root mean squared error (RMSE) was used as the measure of prediction accuracy. RESULTS: The EuroQol Group Valuation Technology (EQ-VT) design showed an average RMSE of 3.44 on EQ-VAS, for all 3125 health states combined. Notably, a 25-state orthogonal design performed similarly to the EQ-VT design, with a smaller RMSE of 3.40, and was thus the most efficient design. One caveat with respect to the orthogonal design was that it did not predict the mild states well. CONCLUSIONS: Our study supports the EQ-VT design. Smaller designs were identified with similar overall prediction accuracy. It is worth investigating whether issues with misprediction of mild states can be resolved, as the use of smaller size designs would reduce the cost of the valuation of EQ-5D-5L considerably.
Authors: Pedro L Ferreira; Patrícia Antunes; Lara N Ferreira; Luís N Pereira; Juan M Ramos-Goñi Journal: Qual Life Res Date: 2019-06-14 Impact factor: 4.147
Authors: Ruixuan Jiang; James Shaw; Axel Mühlbacher; Todd A Lee; Surrey Walton; Thomas Kohlmann; Richard Norman; A Simon Pickard Journal: Qual Life Res Date: 2020-11-28 Impact factor: 4.147