Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: A protocol for a systematic review

Evan Mayo-Wilson, Susan Hutfless, Tianjing Li, Gillian Gresham, Nicole Fusco, Jeffrey Ehmsen, James Heyward, Swaroop Vedula, Diana Lock, Jennifer Haythornthwaite, Jennifer L. Payne, Theresa Cowley, Elizabeth Tolbert, Lori Rosman, Claire Twose, Elizabeth A. Stuart, Hwanhee Hong, Peter Doshi, Catalina Suarez-Cuervo, Sonal SinghKay Dickersin

Research output: Contribution to journalArticle

Abstract

Background: Systematic reviews should provide trustworthy guidance to decision-makers, but their credibility is challenged by the selective reporting of trial results and outcomes. Some trials are not published, and even among clinical trials that are published partially (e.g., as conference abstracts), many are never published in full. Although there are many potential sources of published and unpublished data for systematic reviews, there are no established methods for choosing among multiple reports or data sources about the same trial. Methods: We will conduct systematic reviews of the effectiveness and safety of two interventions following the Institute of Medicine (IOM) guidelines: (1) gabapentin for neuropathic pain and (2) quetiapine for bipolar depression. For the review of gabapentin, we will include adult participants with neuropathic pain who do not require ventilator support. For the review of quetiapine, we will include adult participants with acute bipolar depression (excluding mixed or rapid cycling episodes). We will compare these drugs (used alone or in combination with other interventions) with placebo or with the same intervention alone; direct comparisons with other medications will be excluded. For each review, we will conduct highly sensitive electronic searches, and the results of the searches will be assessed by two independent reviewers. Outcomes, study characteristics, and risk of bias ratings will be extracted from multiple reports by two individuals working independently, stored in a publicly available database (Systematic Review Data Repository) and analyzed using commonly available statistical software. In each review, we will conduct a series of meta-analyses using data from different sources to determine how the results are affected by the inclusion of data from multiple published sources (e.g., journal articles and conference abstracts) as well as unpublished aggregate data (e.g., "clinical study reports") and individual participant data (IPD). We will identify patient-centered outcomes in each report and identify differences in the reporting of these outcomes across sources. Systematic review registration: CRD42015014037, CRD42015014038

Original languageEnglish (US)
Article number143
JournalSystematic reviews
Volume4
Issue number1
DOIs
StatePublished - Nov 2 2015

Keywords

  • Bipolar disorder
  • Depression
  • Gabapentin
  • Guidance
  • Meta-analysis
  • Pain
  • Publication bias
  • Quetiapine
  • Reporting bias
  • Systematic reviews

ASJC Scopus subject areas

  • Medicine (miscellaneous)

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  • Cite this

    Mayo-Wilson, E., Hutfless, S., Li, T., Gresham, G., Fusco, N., Ehmsen, J., Heyward, J., Vedula, S., Lock, D., Haythornthwaite, J., Payne, J. L., Cowley, T., Tolbert, E., Rosman, L., Twose, C., Stuart, E. A., Hong, H., Doshi, P., Suarez-Cuervo, C., ... Dickersin, K. (2015). Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: A protocol for a systematic review. Systematic reviews, 4(1), [143]. https://doi.org/10.1186/s13643-015-0134-z