ROB-ME: a tool for assessing risk of bias due to missing evidence in systematic reviews with meta-analysis

Page, Matthew J, Sterne, Jonathan A C, Boutron, Isabelle, Hróbjartsson, Asbjørn, Kirkham, Jamie J, Li, Tianjing, Lundh, Andreas, Mayo-Wilson, Evan, McKenzie, Joanne E, Stewart, Lesley A, Sutton, Alex J, Bero, Lisa, Dunn, Adam G, Dwan, Kerry, Elbers, Roy G, Kanukula, Raju, Meerpohl, Joeg J, Turner, Erick H and Higgins, Julian P T (2023) 'ROB-ME: a tool for assessing risk of bias due to missing evidence in systematic reviews with meta-analysis'. British Medical Journal (BMJ), Vol 383, Issue e076754.

Preview

Text Revised_Manuscript.pdf - Accepted Version Download (347kB) | Preview

Abstract

The reporting of primary studies or results might be influenced by the P value, magnitude, or direction of the study results; this influence can lead to bias in a meta-analysis, because the available evidence (from studies or results) differs systematically from the missing evidence

Existing methods mostly help users assess whether selective non-publication of studies or selective non-reporting of study results has occurred, but not its impact on a meta-analysis, which leaves users to decide their own approach for combining the risks of each type of bias into an overall judgment of risk of bias in a meta-analysis result

The ROB-ME (risk of bias due to missing evidence) tool is a structured approach for assessing the risk of bias that arises when entire studies, or particular results within studies, are missing from a meta-analysis because of the P value, magnitude, or direction of the study results

The tool consists of three preliminary steps: select and define which metaanalyses will be assessed, determine which studies meeting the inclusion criteria for the meta-analyses have missing results, and consider the potential for missing studies across the review; these steps inform an assessment of risk of bias due to missing evidence in a particular meta-analysis result.

The tool is anticipated to help authors and users of systematic reviews identify meta-analyses at high risk of bias and interpret results appropriately.

Item Type:	Article
Subjects:	WA Public Health > Statistics. Surveys > WA 950 Theory or methods of medical statistics. Epidemiologic methods
Faculty: Department:	Clinical Sciences & International Health > Clinical Sciences Department Clinical Sciences & International Health > International Public Health Department
Digital Object Identifer (DOI):	https://doi.org/10.1136/bmj-2023-076754
Depositing User:	Christianne Esparza
Date Deposited:	05 Dec 2023 14:34
Last Modified:	05 Dec 2023 14:34
URI:	https://archive.lstmed.ac.uk/id/eprint/23573

Statistics

View details

Actions (login required)

Edit Item