Walter S D, Gafni Amiram, Birch Stephen
Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada.
Pharmacoeconomics. 2007;25(6):455-66. doi: 10.2165/00019053-200725060-00002.
Various methods have been proposed to address uncertainty in economic evaluations of healthcare programmes. One approach suggested in the literature is to estimate separate confidence intervals for the incremental costs and effects of a new health programme in comparison with an existing programme. These intervals are then combined to generate a rectangular confidence region in the cost-effectiveness plane that implicitly defines a corresponding confidence interval for the incremental cost-effectiveness ratio (ICER). The same approach has been used to calculate sample sizes and study power. This application of the rectangle method is consistent with the adoption of ICERs and a threshold as a decision rule, this being the most commonly used approach in empirical applications of cost-effectiveness analysis, as well as the one recommended by agencies that assess medical technology around the world. In this paper, we first outline the rectangle method, and then propose a modification that recognises that separate inferences are being drawn on the cost and effectiveness domains, and that corrects for multiple statistical comparisons. The confidence rectangle is otherwise too small, the corresponding confidence interval for the ICER is too narrow and sample sizes are under-estimated. Our modification corrects these problems. A further difficulty is that the placement of the confidence rectangle around the null value is somewhat arbitrary, and does not correspond to a unique value of ICERs. As a result, different values of sample size and power for the estimation of ICERs can be obtained, depending on the null values of the cost and effectiveness. We conclude that it is important to clearly identify the analytic goal in terms of estimating differential costs, differential effects or a combination of the two using the ICER index. These ideas are illustrated using numerical examples.
针对医疗保健项目经济评估中的不确定性，人们提出了各种方法。文献中建议的一种方法是，针对新的健康项目与现有项目相比的增量成本和效果，分别估计置信区间。然后将这些区间合并，在成本效益平面上生成一个矩形置信区域，该区域隐含地定义了增量成本效益比（ICER）的相应置信区间。同样的方法已被用于计算样本量和研究效能。矩形法的这种应用与采用ICER和阈值作为决策规则是一致的，这是成本效益分析实证应用中最常用的方法，也是全球评估医疗技术的机构所推荐的方法。在本文中，我们首先概述矩形法，然后提出一种修正方法，该方法认识到在成本和效益领域进行的是单独推断，并对多重统计比较进行校正。否则，置信矩形会过小，ICER的相应置信区间会过窄，样本量也会被低估。我们的修正方法纠正了这些问题。另一个难点是，围绕零值放置置信矩形有点随意，并且与ICER的唯一值不对应。因此，根据成本和效益的零值，可以获得用于估计ICER的不同样本量和效能值。我们得出结论，重要的是要根据使用ICER指数估计差异成本、差异效果或两者的组合来明确确定分析目标。这些想法通过数值示例进行说明。
