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    Use of ClinicalTrials.gov Registry in Systematic Reviews and Meta-analyses: A Master's Thesis

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    Authors
    Pradhan, Richeek
    Faculty Advisor
    Hong Yu; Robert Goldberg
    Academic Program
    Interdisciplinary Graduate Program
    UMass Chan Affiliations
    Quantitative Health Sciences
    Document Type
    Master's Thesis
    Publication Date
    2017-11-30
    Keywords
    ClinicalTrials.gov; Systematic Reviews; Meta-analyses; Information sources; Safety data
    Health Information Technology
    Medicine and Health Sciences
    Pharmacy and Pharmaceutical Sciences
    Public Health
    
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    Abstract
    Ensuring the objectivity of systematic reviews and meta-analyses (SRMA) begins with comprehensive searches into diverse resources mining primary studies. Guidelines for systematic reviews recommend authors to routinely search of trial registries to identify unpublished studies. In this dissertation, I investigated the utilization of ClinicalTrials.gov (CTG), the world’s largest clinical trial registry that contains data from clinical trials of products that are subject to United States Food and Drug Administration (FDA) regulation, as an information resource in SRMAs. First, I examined the use of various information resources including CTG in SRMAs published from 2005-2016, and identified the factors associated with their use. Thereafter, to determine the accuracy of trial safety data reported at CTG, I compared the data at CTG with that in corresponding journal articles and FDA drug reviews. I found that trial safety data at both CTG and articles differed frequently from FDA drug reviews, but the differences were modest in magnitude. Finally, I repeated published meta-analysis (conducted using data from primary study articles) with data at CTG to find that most meta-analysis results were reproduced using CTG data. Taken together, this work suggests that CTG should not only be searched more often to find primary research for systematic reviews, but that data at CTG can also be used to conduct quantitative data synthesis.
    DOI
    10.13028/M27H6R
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/32320
    Rights
    Copyright is held by the author, with all rights reserved.
    ae974a485f413a2113503eed53cd6c53
    10.13028/M27H6R
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    Morningside Graduate School of Biomedical Sciences Dissertations and Theses

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