在加拿大为EQ-5D-5L创建多重导入值集:需要州级错误规范术语来正确描述参数不确定性
Teresa C O Tsui1,2,3,4, Kelvin K W Chan2,3,4, Feng Xie5,6
1Child Health Evaluative Sciences, Hospital for Sick Children, Toronto, ON, Canada.
概括
本研究引入了第一个多重推算 (MI) EQ-5D-5L值集,考虑参数不确定性. 使用MI值集会增加标准误差,显示当前的方法低估了健康效用估计的不确定性.
科学领域:
- 卫生经济学 卫生经济学
- 心理测量 心理测量 心理测量
- 生物统计学 生物统计学
背景情况:
- 在EQ-5D-5L值集中的参数不确定性经常被忽视.
- 现有的方法不能完全捕捉这种不确定性,可能会超过该仪器的最小重要差异.
- 之前的任何估值研究都没有实施多重归算 (MI) 来解决这个问题.
研究的目的:
- 为EQ-5D-5L.开发第一个加拿大MI值集.
- 为了使用户能够考虑价值设置估计中的参数不确定性.
- 为了比较MI与原始值集对标准错误估计的影响.
主要方法:
- 使用加拿大估值数据 (N=1,073) 改装EQ-5D-5L模型,包括州级错误规范.
- 基于可信区间覆盖范围的比较模型,用于样本之外的预测.
- 使用后置分布抽取生成了100个归算值集,并得分了两个数据集.
主要成果:
- 一个具有州级错误规范的模型显示出更好的预测性能 (94.2%的CRI覆盖率与11.6%相比).
- 在一般公众和乳腺癌患者样本中,MI值集导致平均健康实用设施的标准误差大幅扩大.
- 观察到的MI标准误差为0.0091 (一般公众) 和0.0169 (乳腺癌),而原始值为0.0035和0.0066.
结论:
- 该研究为EQ-5D-5L和相关代码提供了第一个MI值集.
- 忽视参数不确定性会导致卫生效用估计中的错误标准误差.
- 这些发现与EQ-5D-5L方法学家,开发人员和卫生经济学和政策中的用户有关.
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