O'Hagan A, Stevens J W, Montmartin J
Department of Probability and Statistics, University of Sheffield, Sheffield S3 7RH, UK.
Stat Med. 2001 Mar 15;20(5):733-53. doi: 10.1002/sim.861.
A key tool for assessing the relative cost-effectiveness of two treatments in health economics is the incremental C/E acceptability curve. We present Bayesian computations for this curve in the case where data on both costs and efficacy are available from a clinical trial. Analysis is given under various formulations of prior information. A case study is analysed in which reasonable prior information is shown to strengthen substantially the posterior inference, leading to a more conclusive assessment of cost-effectiveness. Calculations can be performed using readily available Bayesian software.
在卫生经济学中,评估两种治疗方法相对成本效益的一个关键工具是增量成本效果可接受性曲线。在可从临床试验获得成本和疗效数据的情况下,我们给出了该曲线的贝叶斯计算方法。在各种先验信息的设定下进行了分析。分析了一个案例研究,其中合理的先验信息被证明能显著加强后验推断,从而对成本效益进行更具决定性的评估。计算可以使用现成的贝叶斯软件来进行。