Shaw James W, Johnson Jeffrey A, Coons Stephen Joel
Tobacco Control Research Branch, Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland, USA.
Med Care. 2005 Mar;43(3):203-20. doi: 10.1097/00005650-200503000-00003.
The EQ-5D is a brief, multiattribute, preference-based health status measure. This article describes the development of a statistical model for generating US population-based EQ-5D preference weights.
A multistage probability sample was selected from the US adult civilian noninstitutional population. Respondents valued 13 of 243 EQ-5D health states using the time trade-off (TTO) method. Data for 12 states were used in econometric modeling. The TTO valuations were linearly transformed to lie on the interval [-1, 1]. Methods were investigated to account for interaction effects caused by having problems in multiple EQ-5D dimensions. Several alternative model specifications (eg, pooled least squares, random effects) also were considered. A modified split-sample approach was used to evaluate the predictive accuracy of the models. All statistical analyses took into account the clustering and disproportionate selection probabilities inherent in our sampling design.
Our D1 model for the EQ-5D included ordinal terms to capture the effect of departures from perfect health as well as interaction effects. A random effects specification of the D1 model yielded a good fit for the observed TTO data, with an overall R of 0.38, a mean absolute error of 0.025, and 7 prediction errors exceeding 0.05 in absolute magnitude.
The D1 model best predicts the values for observed health states. The resulting preference weight estimates represent a significant enhancement of the EQ-5D's utility for health status assessment and economic analysis in the US.
EQ-5D是一种简短的、多属性的、基于偏好的健康状况测量工具。本文描述了一种用于生成基于美国人群的EQ-5D偏好权重的统计模型的开发过程。
从美国成年非机构化平民人口中选取了一个多阶段概率样本。受访者使用时间权衡（TTO）方法对243种EQ-5D健康状态中的13种进行了估值。12种状态的数据用于计量经济学建模。TTO估值经过线性变换后落在区间[-1, 1]内。研究了考虑EQ-5D多个维度出现问题所引起的交互作用的方法。还考虑了几种替代模型规格（例如，混合最小二乘法、随机效应）。采用改进的拆分样本方法评估模型的预测准确性。所有统计分析都考虑了我们抽样设计中固有的聚类和不均衡选择概率。
我们的EQ-5D D1模型包括序数项以捕捉偏离完美健康的影响以及交互作用。D1模型的随机效应规格对观察到的TTO数据拟合良好，总体R值为0.38，平均绝对误差为0.025，绝对幅度超过0.05的预测误差有7个。
D1模型最能预测观察到的健康状态的值。由此得到的偏好权重估计值显著提高了EQ-5D在美国健康状况评估和经济分析中的效用。
