Historical data from previous clinical trials, observational studies and health records may be utilized in analysis of clinical trials data to strengthen inference. Under the Bayesian framework incorporation of information obtained from any source other than the current data is facilitated through construction of an informative prior. The existing methodology for defining an informative prior based on historical data relies on measuring similarity to the current data at the study level and does not take advantage of individual patient data (IPD). This paper proposes a family of priors that utilize IPD to strengthen statistical inference. It is demonstrated that the proposed prior construction approach outperforms the existing methods where the historical data are partially exchangeable with the present data. The proposed method is applied to IPD from a set of trials in non-small cell lung cancer.
翻译:以往临床试验、观察研究和健康记录的历史数据可用于分析临床试验数据,以加强推论; 根据巴伊西亚框架,通过先建信息资料,便利将从目前数据以外的任何其他来源获得的信息纳入其中; 现有的基于历史数据界定先知信息的方法依靠的是测量研究一级现有数据的相似性,而没有利用个别病人的数据(IPD); 本文提出利用IPD加强统计推论的先行数据组合; 证明拟议的先建方法优于历史数据可部分与现有数据交换的现有方法; 拟议的方法从非小细胞肺癌的一系列试验中适用于IPD。