A framework for cost‐effectiveness analysis from clinical trial data
提出了一个通用的贝叶斯框架，用于从临床试验数据中进行成本效果分析，允许灵活建模成本和疗效数据，并通过案例展示了先验信息的作用。
We present a general Bayesian framework for cost-effectiveness analysis (CEA) from clinical trial data. This framework allows for very flexible modelling of both cost and efficacy related trial data. A common CEA technique is established for this wide class of models through linking mean efficacy and mean cost to the parameters of any given model. Examples are given in which efficacy may be measured as a continuous, binary, ordinal or time-to-event outcome, and in which costs are modelled as distributed normally, log-normally, as a mixture or non-parametrically. A case study is presented, illustrating the methodology and illuminating the role of prior information.