• Chen-Wei Pan, Ruo-Yu Zhang, Nan Luo, Jun-Yi He, Rui-Jie Liu, Xiao-Hua Ying, and Pei Wang.
• School of Public Health, Medical College of Soochow University, Suzhou, China.
• Qual Life Res. 2020 Nov 1; 29 (11): 3087-3094.

ObjectivesIn China, multiple approaches to calculating EQ-5D utilities are available, including the two EQ-5D-3L (3L2014 and 3L2018) scoring functions, the EQ-5D-5L (5L) scoring function, and the crosswalk function linking the 3L utilities and 5L health states. The study compared utilities derived from them in terms of agreement and discriminative power; and assessed whether the use of different approaches may affect QALY estimation in Chinese type 2 diabetes (T2D) patients.MethodsCross-sectional data of 289 T2D patients who self-completed both the 5L and 3L questions were used. Agreement were examined using intraclass correlation coefficient (ICC) and Bland-Altman plots. The ability of the EQ-5D utilities in differentiating the patients with and without clinical conditions was evaluated using F-statistics. Their influence on QALY estimation was assessed adopting mean absolute difference (MAD) in utility values between the patients.ResultsThe ICC values were 0.881 (3L2014-3L2018), 0.958 (5L-c5L2014), and 0.806 (5L-c5L2018). The two 3L utilities and the three 5L utilities had poor agreement at the lower end of utility scale according to Bland-Altman plots. The 3L2018 utilities had lower F-statistics compared to the 3L2014 utilities; the two c5L utilities had larger or similar F-statistics compared to the 5L utilities. The mean MADs were 0.138 (5L), 0.116 (3L2014), 0.115 (c5L2014), 0.055 (c5L2018), and 0.055 (3L2018).ConclusionThe 3L2014 utilities is more discriminative than the 3L2018 utilities; and the two c5L utilities have no worse discriminative power compared with the 5L utilities. The choice of the approach to calculating the EQ-5D utilities is likely to affect QALY estimates.

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