Chen-Wei Pan1, Ruo-Yu Zhang2, Nan Luo3, Jun-Yi He2, Rui-Jie Liu2, Xiao-Hua Ying2, Pei Wang4,5. 1. School of Public Health, Medical College of Soochow University, Suzhou, China. 2. School of Public Health, Fudan University, Shanghai, China. 3. Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore. 4. School of Public Health, Fudan University, Shanghai, China. wang_p@fudan.edu.cn. 5. Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China (Fudan University), Shanghai, China. wang_p@fudan.edu.cn.
Abstract
OBJECTIVES: In 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. METHODS: Cross-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. RESULTS: The 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). CONCLUSION: The 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.
OBJECTIVES: In 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. METHODS: Cross-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. RESULTS: The 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). CONCLUSION: The 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.
Authors: Ruo-Yu Zhang; Wei Wang; Hui-Jun Zhou; Jian-Wei Xuan; Nan Luo; Pei Wang Journal: Health Qual Life Outcomes Date: 2022-05-19 Impact factor: 3.077