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Methodological review of NMA bias concepts provides groundwork for the development of a list of concepts for potential inclusion in a new risk of bias tool for network meta-analysis (RoB NMA Tool). | LitMetric

AI Article Synopsis

  • - Network meta-analyses (NMAs) are increasingly popular for comparing multiple treatments for the same condition, prompting a review aimed at identifying concepts related to bias in NMAs.
  • - The study examined 181 articles, ultimately including 58 that focused on bias and methodological standards, leading to the extraction of 22 specific concepts concerning bias in NMAs.
  • - The resulting list of 22 concepts is intended to guide future tool development rather than directly assess biases in NMAs.

Article Abstract

Introduction: Network meta-analyses (NMAs) have gained popularity and grown in number due to their ability to provide estimates of the comparative effectiveness of multiple treatments for the same condition. The aim of this study is to conduct a methodological review to compile a preliminary list of concepts related to bias in NMAs.

Methods And Analysis: We included papers that present items related to bias, reporting or methodological quality, papers assessing the quality of NMAs, or method papers. We searched MEDLINE, the Cochrane Library and unpublished literature (up to July 2020). We extracted items related to bias in NMAs. An item was excluded if it related to general systematic review quality or bias and was included in currently available tools such as ROBIS or AMSTAR 2. We reworded items, typically structured as questions, into concepts (i.e. general notions).

Results: One hundred eighty-one articles were assessed in full text and 58 were included. Of these articles, 12 were tools, checklists or journal standards; 13 were guidance documents for NMAs; 27 were studies related to bias or NMA methods; and 6 were papers assessing the quality of NMAs. These studies yielded 99 items of which the majority related to general systematic review quality and biases and were therefore excluded. The 22 items we included were reworded into concepts specific to bias in NMAs.

Conclusions: A list of 22 concepts was included. This list is not intended to be used to assess biases in NMAs, but to inform the development of items to be included in our tool.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785511PMC
http://dx.doi.org/10.1186/s13643-023-02388-xDOI Listing

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