Integrating Aggregate-Data and Individual-Patient-Data in Meta-Analysis: An Empirical Assessment and an Alternative Method for the Two-Stage Approach

In this study, we compared the efficacy of the overall meta-analysis estimates that used only the available aggregate data (AD) studies against those that combined the available AD and individual patient data (IPD) studies. We introduced some modifications to the existing two-stage method for combining the AD and IPD studies. We evaluated the effects of these modifications on the estimates of the overall treatment effect, and investigated the influence of the number of studies included in the meta-analysis, N, and the ratio of AD- IPD on these estimates. We used percentage relative bias (PRB), root mean-square-error (RMSE), and coverage probability to assess the overall efficiency of these estimates. The results revealed the superiority of estimates from the combined AD- IPD studies over those that utilized only the available AD in terms of both the accuracy and the RMSE. We found that the current method for combining the AD-IPD studies provided poor coverage probabilityand that the proposed methods generated improved coverage probability by more than 40% while maintaining the level of bias and RMSE at par to their existing counterparts. These findings validated the importance of utilizing both the AD and IPD studies whenever they are available, and demonstrated the significance of proper technique for combining these studies in order to obtain better overall estimates.