Basu Anirban, Dale William, Elstein Arthur, Meltzer David
Department of Medicine, Section of General Internal Medicine, Center for Health and the Social Sciences, University of Chicago, Chicago, IL 60637, USA.
Health Econ. 2009 Apr;18(4):403-19. doi: 10.1002/hec.1373.
Direct elicitation of utilities for joint health (JS) states may pose substantial interview burden, while traditional models to predict these utilities from utilities of component single states (SS) are inconsistent with the data. Using individual-level data on utilities for health states associated with prostate cancer, we report the performance of a new model that encompasses three traditional models - additive, multiplicative, and minimum - previously used for predicting utilities for joint health states. Describing utilities in terms of utility losses l(.) relative to prefect health, our final estimated linear index for predicting joint health-state utilities is El(JS)=0.05+0.72 x max l(SS1),l(SS2)+0.33.min x l(SS1),l(SS2)-0.18 x l(SS1) x l(SS2). Based on out-of-sample predictions, this model produces up to 50% reduction in mean-square error compared with traditional models and consistent prediction across different ranges of joint-state utilities, which the traditional models do not. Parameter estimates of the new model proposed here provide direct evidence on the inconsistencies of the traditional models, are grounded in psychological theory by emphasizing the more severe component of a joint health state, and provide a simple linear index to generate consistent predictions of utilities for joint health states. Further validation of this function for joint health states in other clinical scenarios is warranted.
直接获取关节健康（JS）状态的效用可能会带来巨大的访谈负担，而从单个组成状态（SS）的效用预测这些效用的传统模型与数据不一致。利用前列腺癌相关健康状态效用的个体层面数据，我们报告了一种新模型的性能，该模型包含三种先前用于预测关节健康状态效用的传统模型——加法模型、乘法模型和最小模型。用相对于完美健康的效用损失l(.)来描述效用，我们最终用于预测关节健康状态效用的估计线性指数为El(JS)=0.05 + 0.72 x max{l(SS1), l(SS2)} + 0.33 x min{l(SS1), l(SS2)} - 0.18 x l(SS1) x l(SS2)。基于样本外预测，与传统模型相比，该模型的均方误差降低了多达50%，并且在不同范围的关节状态效用上具有一致的预测，而传统模型则不具备。这里提出的新模型的参数估计为传统模型的不一致性提供了直接证据，通过强调关节健康状态中更严重的组成部分而基于心理学理论，并提供了一个简单的线性指数来生成关节健康状态效用的一致预测。有必要在其他临床场景中对该关节健康状态函数进行进一步验证。
