F1000Research (Feb 2020)

Investigation of Risk Of Bias due to Unreported and SelecTively included results in meta-analyses of nutrition research: the ROBUST study protocol [version 2; peer review: 2 approved]

  • Matthew J. Page,
  • Lisa Bero,
  • Cynthia M. Kroeger,
  • Zhaoli Dai,
  • Sally McDonald,
  • Andrew Forbes,
  • Joanne E. McKenzie

DOI
https://doi.org/10.12688/f1000research.20726.2
Journal volume & issue
Vol. 8

Abstract

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Background: Dietary guidelines should be informed by systematic reviews (SRs) of the available scientific evidence. However, if the SRs that underpin dietary guidelines are flawed in their design, conduct or reporting, the recommendations contained therein may be misleading or harmful. To date there has been little empirical investigation of bias due to selective inclusion of results, and bias due to missing results, in SRs of food/diet-outcome relationships. Objectives: To explore in SRs with meta-analyses of the association between food/diet and health-related outcomes: (i) whether systematic reviewers selectively included study effect estimates in meta-analyses when multiple effect estimates were available; (ii) what impact selective inclusion of study effect estimates may have on meta-analytic effects, and; (iii) the risk of bias due to missing results (publication bias and selective non-reporting bias) in meta-analyses. Methods: We will systematically search for SRs with meta-analysis of the association between food/diet and health-related outcomes in a generally healthy population, published between January 2018 and June 2019. We will randomly sort titles and abstracts and screen them until we identify 50 eligible SRs. The first reported meta-analysis of a binary or continuous outcome in each SR (the ‘index meta-analysis’) will be evaluated. We will extract from study reports all study effect estimates that were eligible for inclusion in the index meta-analyses (e.g. from multiple instruments and time points) and will quantify and test for evidence of selective inclusion of results. We will also assess the risk of bias due to missing results in the index meta-analyses using a new tool (ROB-ME). Ethics and dissemination: Ethics approval is not required because information will only be extracted from published studies. Dissemination of the results will be through peer-reviewed publications and presentations at conferences. We will make all data collected from this study publicly available via the Open Science Framework.