An exploration of methods for obtaining 0 = dead anchors for latent scale EQ-5D-Y values

探索获取潜在量表 EQ-5D-Y 值 0 = 死锚点的方法

阅读:1

Abstract

OBJECTIVES: Discrete choice experiments (DCEs) can be used to obtain latent scale values for the EQ-5D-Y, but these require anchoring at 0 = dead to meet the conventions of quality-adjusted life year (QALY) estimation. The primary aim of this study is to compare four preference elicitation methods for obtaining anchors for latent scale EQ-5D-Y values. METHODS: Four methods were tested: visual analogue scale (VAS), DCE (with a duration attribute), lag-time time trade-off (TTO) and the location-of-dead (LOD) approach. In computer-assisted personal interviews, UK general public respondents valued EQ-5D-3L health states from an adult perspective and EQ-5D-Y health states from a 10-year-old child perspective. Respondents completed valuation tasks using all four methods, under both perspectives. RESULTS: 349 interviews were conducted. Overall, respondents gave lower values under the adult perspective compared to the child perspective, with some variation across methods. The mean TTO value for the worst health state (33333) was about equal to dead in the child perspective and worse than dead in the adult perspective. The mean VAS rescaled value for 33333 was also higher in the child perspective. The DCE produced positive child perspective values and negative adult perspective values, though the models were not consistent. The LOD median rescaled value for 33333 was negative under both perspectives and higher in the child perspective. DISCUSSION: There was broad agreement across methods. Potential criteria for selecting a preferred anchoring method are presented. We conclude by discussing the decision-making circumstances under which utilities and QALY estimates for children and adults need to be commensurate to achieve allocative efficiency.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。