  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.
