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An XML Based Framework for Merging Incomplete and Inconsistent Statistical Information From Clinical Trials

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Executive Summary

Meta-analysis is a vital task for systematically summarizing statistical results from clinical trials that are carried out to compare the effect of one medication (or other treatment) against another. Currently, most meta-analysis activities are done by manually pooling data. This is a very time consuming and expensive task. An automated or even semi-automated tool that can support some of the processes underlying meta-analysis is greatly needed. Furthermore, statistical results from clinical trials are usually represented as sampling distributions (i.e., with the mean value and the SEM). When collecting statistical information from reports on clinical trials, not all reports contain full statistical information (i.e., some do not provide SEMs) whilst traditional meta-analysis excludes trials reports that contain incomplete information, which inevitably ignores many trials that could be valuable.

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