Incorporation of historical data in the analysis of randomized therapeutic trials

Historical studies provide a valuable source of information for the motivation and design of later trials. Bayesian techniques offer possibilities for the quantitative inclusion of prior knowledge within the analysis of current trial data. Combining information from previous studies into an informative prior distribution is, however, a delicate case. The power prior distribution is a tool to estimate the effect of an intervention in a current study sample, while accounting for the information provided by previous research. In this study we evaluate the use of the power prior distribution, illustrated with data from a large randomized clinical trial on the effect of ST-wave analysis in intrapartum fetal monitoring. We advocate the use of a power prior distribution with pre-specified fixed study weights based on differences in study characteristics. We propose obtaining a ranking of the historical studies via expert elicitation, based on relevance for the current study, and specify study weights accordingly.