IPDMA: Individual Patient/Participant Data Meta-Analysis

In a previous article in KT Update (Dijkers, 2014), the development of meta-analysis (MA) was sketched from (1) meta-analysis of individual study findings (e.g., means and standard deviations, correlations) reported in the literature, to (2) meta-analysis of individual subject data harvested from the published literature, to (3) merging of datasets from multiple studies that share subject population (but not the same individuals) and have similar variables, to (4) creation of common data elements (CDEs) to standardize the variables in related studies, to (5) trialists’ collaborations, which offer a mechanism to prospectively combine related studies into a single dataset. Of the above, 2, 3, 4, and 5 all require or offer opportunities for individual patient/participant (data) MA, or IPDMA. The major differences between IPDMA and a secondary analysis of a single-site or multi-site dataset is the need to acquire data or datasets, carefully develop a common coding scheme for all variables, and in the analysis address any issues resulting from the origin of the data (e.g., clustering). How much of this painstaking work needs to be done depends largely on the source of one’s data – differences between 2, 3, 4 or 5 above, essentially. IPDMA is most closely associated with 3 above: synthesizing information resulting from a re-analysis of the data produced by two or more studies. Alternative names that have been proposed for this process are “mega-analysis” and “integrative data analysis.” These have not caught on; even though one might ask whether for a one-stage IPDMA (explained below), the term “meta” may be appropriate.