Coupling Results Data from ClinicalTrials.gov and Bibliographic Databases to Accelerate Evidence Synthesis

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Project Summary Clinical trials are foundational to evidence-based medicine, but results reporting from trials is incomplete and frequently delayed. It is estimated that as many as half of clinical trials are not published and as many as half of published trials underreport or misreport outcomes. This type of results reporting distorts the evidence available to clinicians—particularly when it comes to assessing the safety of interventions like drugs and devices—and may place patients at unnecessary risk. There is a critical need for novel methods to identify and monitor drug safety data. Through the infrastructure provided by ClinicalTrials.gov, structured trial results (including safety findings) are now becoming available for an increasing number of trials in a comprehensive and timely fashion. However, access and use of these data in evidence synthesis tasks remain limited. ClinicalTrials.gov is the largest single registry for clinical studies worldwide and includes more than 260,000 registered studies. Of the 108,941 completed trials registered with the site, 20% have uploaded results data for a total of 7.85 million participants. Results data reported on ClinicalTrials.gov have the potential to fill gaps created by delays and biases in published articles and provide an earlier and more complete overview of available trial evidence. We propose to develop novel informatics approaches based on combinations of information retrieval and machine learning methods to facilitate access and analysis of trial results reported in this registry. Focusing on trials testing drug interventions in type 2 diabetes, obesity, and oncology, we perform this work in three specific aims: 1) Develop semi-automated trial screening for identifying and aggregating trials relevant to a clinical intervention; 2) Extract adverse event and safety outcomes data from results reported in the registry; and 3) Perform validation studies to assess detection of adverse events and performance of semi- automated meta-analyses of safety outcomes. Methods developed in this project will facilitate timely, broad- scale use of trial results reported on ClinicalTrials.gov in order to augment the availability of comprehensive and timely drug safety data. All methods will be made publicly available in order to support adverse event monitoring and systematic reviews of drug interventions.