A Comparison of Direct and Indirect Methods for the Estimation of Health Utilities from Clinical Outcomes
A Comparison of Direct and Indirect Methods for the Estimation of Health Utilities from Clinical Outcomes
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DOI：
10.1177/0272989x13500720
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发表时间：
2014-10-01
影响因子：
3.6
通讯作者：
Michaud, Kaleb
中科院分区：
文献类型：
--
作者：
Alava, Monica Hernandez;Wailoo, Allan;Michaud, Kaleb
背景：分析师经常根据其他结果来估计健康状态效用值。诸如 EQ-5D 之类的效用值具有使标准统计方法不适用的特征。我们开发了一种定制的混合模型方法来直接估计 EQ-5D。间接方法“响应映射”首先估计 EQ-5D 5 个维度中每个维度的水平，然后计算预期关税得分。这些方法以前从未被比较过。方法：我们使用来自类风湿关节炎患者的大型观察数据库（N = 100,398）。使用有限因变量混合模型对 UK EQ-5D 分数作为健康评估问卷 (HAQ)、疼痛和年龄的函数进行直接估计。使用一组广义有序概率模型进行间接建模，并通过数学计算得出预期关税分数。报告线性回归用于比较目的。现有模型证明了对成本效益的影响。结果：线性模型拟合效果很差，尤其是在分布的极端情况下。定制混合模型和间接方法提高了 EQ-5D 整个范围的拟合度。与线性模型相比，平均误差分别降低了 10% 和 5%。均方根误差分别降低 3% 和 2%。混合模型在几乎整个疼痛和 HAQ 范围内都表现出了优于间接方法的性能。这些导致成本效益差异高达 20%。结论：HAQ 健康状况最严重的患者的数据有限。最好直接使用定制混合模型根据临床测量对 EQ-5D 进行建模。在本例中，这大大优于间接方法。线性模型是不合适的，会受到系统偏差的影响，并且会生成超出可行范围的值。
Background: Analysts frequently estimate health state utility values from other outcomes. Utility values like EQ-5D have characteristics that make standard statistical methods inappropriate. We have developed a bespoke, mixture model approach to directly estimate EQ-5D. An indirect method, "response mapping," first estimates the level on each of the 5 dimensions of the EQ-5D and then calculates the expected tariff score. These methods have never previously been compared. Methods: We use a large observational database from patients with rheumatoid arthritis (N = 100,398). Direct estimation of UK EQ-5D scores as a function of the Health Assessment Questionnaire (HAQ), pain, and age was performed with a limited dependent variable mixture model. Indirect modeling was undertaken with a set of generalized ordered probit models with expected tariff scores calculated mathematically. Linear regression was reported for comparison purposes. Impact on cost-effectiveness was demonstrated with an existing model. Results: The linear model fits poorly, particularly at the extremes of the distribution. The bespoke mixture model and the indirect approaches improve fit over the entire range of EQ-5D. Mean average error is 10% and 5% lower compared with the linear model, respectively. Root mean squared error is 3% and 2% lower. The mixture model demonstrates superior performance to the indirect method across almost the entire range of pain and HAQ. These lead to differences in cost-effectiveness of up to 20%. Conclusions: There are limited data from patients in the most severe HAQ health states. Modeling of EQ-5D from clinical measures is best performed directly using the bespoke mixture model. This substantially outperforms the indirect method in this example. Linear models are inappropriate, suffer from systematic bias, and generate values outside the feasible range.