Table 11 Sensitivity analysis, selective analysis for the five studies meeting the inclusion criteria
Studies | Measure | Region | Value set | N | Mean | 95% CI | Weight (%) | Estimate [95% CI] | I2(%) | |
|---|---|---|---|---|---|---|---|---|---|---|
1 | Studies conducted in China, using EQ5D5L, valued by same China dataset (Luo 2017) | |||||||||
Li 2019 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 608 | 0.83 | 0.81, 0.84 | 51 | 0.84 [0.81, 0.87] | 85 | |
Yang 2020 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 446 | 0.86 | 0.84, 0.87 | 48 | |||
2 | Studies using EQ5D5L in China | |||||||||
Li 2019 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 608 | 0.83 | 0.81, 0.84 | 33 | 0.82 [0.77, 0.87] | 97 | |
Yang 2020 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 446 | 0.86 | 0.84, 0.87 | 32 | |||
Wang 2018 | EQ-5D-3L | China | China EQ5D3L, Liu 2014 | 2626 | 0.78 | 0.77, 0.78 | 34 | |||
3 | Studies using EQ5D5L, valued by same China dataset (Luo 2017) | |||||||||
Li 2019 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 608 | 0.83 | 0.81, 0.84 | 33 | 0.87 [0.81, 0.92] | 97 | |
Yang 2020 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 446 | 0.86 | 0.84, 0.87 | 33 | |||
Ou 2019 | EQ-5D-5L | Taiwan | China EQ5D5L, Luo 2017 | 193 | 0.92 | 0.90, 0.93 | 33 | |||
4 | Studies using EQ5D5L | |||||||||
Li 2019 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 608 | 0.83 | 0.81, 0.84 | 25 | 0.84 [0.78, 0.90] | 98 | |
Yang 2020 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 446 | 0.86 | 0.84, 0.87 | 24 | |||
Ou 2019 | EQ-5D-5L | Taiwan | China EQ5D5L, Luo 2017 | 193 | 0.92 | 0.90, 0.93 | 25 | |||
Cheung 2014 | EQ-5D-5L | Singapore | Japanese (Rabin) | 238 | 0.77 | 0.75, 0.79 | 24 | |||
5 | All studies | |||||||||
Li 2019 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 608 | 0.83 | 0.81, 0.84 | 20 | 0.83 [0.77, 0.89] | 99 | |
Yang 2020 | EQ-5D-5L | China | China EQ5D5L, Luo 2017 | 446 | 0.86 | 0.84, 0.87 | 19 | |||
Ou 2019 | EQ-5D-5L | Taiwan | China EQ5D5L, Luo 2017 | 193 | 0.92 | 0.90, 0.93 | 20 | |||
Cheung 2014 | EQ-5D-5L | Singapore | Japanese (Rabin) | 238 | 0.77 | 0.75, 0.79 | 19 | |||
Wang 2018 | EQ-5D-3L | China | China EQ5D3L, Liu 2014 | 2626 | 0.78 | 0.77, 0.78 | 20 | |||