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Lunny C, Veroniki AA, Higgins JPT, Dias S, Hutton B, Wright JM, White IR, Whiting P, Tricco AC. 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). Syst Rev 2024; 13:25. [PMID: 38217041 PMCID: PMC10785511 DOI: 10.1186/s13643-023-02388-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 11/10/2023] [Indexed: 01/14/2024] Open
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 We searched MEDLINE, the Cochrane Library and unpublished literature (up to July 2020).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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Affiliation(s)
- Carole Lunny
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, 209 Victoria Street, East Building, Toronto, ON, M5B 1T8, Canada.
- Cochrane Hypertension Review Group, the Therapeutics Initiative, University of British Columbia, Vancouver, Canada.
| | - Areti-Angeliki Veroniki
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, 209 Victoria Street, East Building, Toronto, ON, M5B 1T8, Canada
| | - Julian P T Higgins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
- NIHR Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Sofia Dias
- Centre for Reviews and Dissemination, University of York, York, UK
| | - Brian Hutton
- Ottawa Hospital Research Institute, Ottawa, Canada
- Ottawa University, School of Epidemiology and Public Health, Ottawa, Canada
| | - James M Wright
- Cochrane Hypertension Review Group, the Therapeutics Initiative, University of British Columbia, Vancouver, Canada
| | | | - Penny Whiting
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andrea C Tricco
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, 209 Victoria Street, East Building, Toronto, ON, M5B 1T8, Canada
- Dalla Lana School of Public Health & Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
- Queen's Collaboration for Health Care Quality Joanna Briggs Institute Centre of Excellence, Queen's University, Kingston, Canada
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Veroniki AA, Franco JVA. Exploring advanced methods for network meta-analysis. BMJ Evid Based Med 2023; 28:285-286. [PMID: 37495271 DOI: 10.1136/bmjebm-2023-112482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/06/2023] [Indexed: 07/28/2023]
Affiliation(s)
- Areti Angeliki Veroniki
- Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
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