In Value of Information (VoI) analysis, the unit normal loss integral (UNLI) frequently emerges as a solution for computation of various VoI metrics for both model-based and data-driven economic evaluations. However, one limitation of the UNLI has been that its closed-form solution is available for only one dimension, and thus can be used for comparisons involving only two strategies (where it is applied to the scalar incremental net benefit). We derive a closed-form solution for the two-dimensional UNLI, enabling closed-form VoI calculations for three strategies. A case study based on a three-arm clinical trial is provided as an example. VoI methods based on the closed-form solutions for the UNLI can now be extended to three-decision comparisons, taking a fraction of a second to compute and not being subject to Monte Carlo error. This method is implemented in R and is available through an R package (https://github.com/resplab/predtools/).
翻译:在信息价值(VoI)分析中,单位正常损失整体部分(UNLI)经常出现,作为计算基于模型和数据驱动的经济评价的各种VoI指标的一种解决办法,但是,UNLI的一个局限性是,其封闭式解决办法只有一个层面,因此可用于比较仅涉及两个战略(在适用于卡路里递增净收益的情况下),我们为二维UNLI产生一个封闭式解决办法,以便能够对三种战略进行封闭式VoI计算,以三重临床试验为基础进行案例研究,例如:VoI基于UNLI封闭式解决办法的方法现在可以扩大到三个决定性比较,用一小部分的第二位来计算,而不受Monte Carlo错误的影响;这种方法在R实施,并通过R组合(https://github.com/resplab/predtools/)提供。