Knowledge user survey and Delphi process to inform development of a new risk of bias tool to assess systematic reviews with network meta-analysis (RoB NMA tool).

Humans Network Meta-Analysis Cross-Sectional Studies Systematic Reviews as Topic Bias Surveys and Questionnaires
evidence-based practice health care quality, access, and evaluation health services research methods

Journal

BMJ evidence-based medicine
ISSN: 2515-4478
Titre abrégé: BMJ Evid Based Med
Pays: England
ID NLM: 101719009

Informations de publication

Date de publication:
02 2023
Historique:
accepted: 16 07 2022
pubmed: 11 8 2022
medline: 24 1 2023
entrez: 10 8 2022
Statut: ppublish

Résumé

Network meta-analysis (NMA) is increasingly used in guideline development and other aspects of evidence-based decision-making. We aimed to develop a risk of bias (RoB) tool to assess NMAs (RoB NMA tool). An international steering committee recommended that the RoB NMA tool to be used in combination with the Risk of Bias in Systematic reviews (ROBIS) tool (i.e. because it was designed to assess biases only) or other similar quality appraisal tools (eg, A MeaSurement Tool to Assess systematic Reviews 2 [AMSTAR 2]) to assess quality of systematic reviews. The RoB NMA tool will assess NMA biases and limitations regarding how the analysis was planned, data were analysed and results were presented, including the way in which the evidence was assembled and interpreted. Conduct (a) a Delphi process to determine expert opinion on an item's inclusion and (b) a knowledge user survey to widen its impact. Cross-sectional survey and Delphi process. Delphi panellists were asked to rate whether items should be included. All agreed-upon item were included in a second round of the survey (defined as 70% agreement). We surveyed knowledge users' views and preferences about the importance, utility and willingness to use the RoB NMA tool to evaluate evidence in practice and in policymaking. We included 12 closed and 10 open-ended questions, and we followed a knowledge translation plan to disseminate the survey through social media and professional networks. 22 items were entered into a Delphi survey of which 28 respondents completed round 1, and 22 completed round 2. Seven items did not reach consensus in round 2. A total of 298 knowledge users participated in the survey (14% respondent rate). 75% indicated that their organisation produced NMAs, and 78% showed high interest in the tool, especially if they had received adequate training (84%). Most knowledge users and Delphi panellists preferred a tool to assess This Delphi process and knowledge user survey informs the development of the RoB NMA tool.

Sections du résumé

BACKGROUND
Network meta-analysis (NMA) is increasingly used in guideline development and other aspects of evidence-based decision-making. We aimed to develop a risk of bias (RoB) tool to assess NMAs (RoB NMA tool). An international steering committee recommended that the RoB NMA tool to be used in combination with the Risk of Bias in Systematic reviews (ROBIS) tool (i.e. because it was designed to assess biases only) or other similar quality appraisal tools (eg, A MeaSurement Tool to Assess systematic Reviews 2 [AMSTAR 2]) to assess quality of systematic reviews. The RoB NMA tool will assess NMA biases and limitations regarding how the analysis was planned, data were analysed and results were presented, including the way in which the evidence was assembled and interpreted.
OBJECTIVES
Conduct (a) a Delphi process to determine expert opinion on an item's inclusion and (b) a knowledge user survey to widen its impact.
DESIGN
Cross-sectional survey and Delphi process.
METHODS
Delphi panellists were asked to rate whether items should be included. All agreed-upon item were included in a second round of the survey (defined as 70% agreement). We surveyed knowledge users' views and preferences about the importance, utility and willingness to use the RoB NMA tool to evaluate evidence in practice and in policymaking. We included 12 closed and 10 open-ended questions, and we followed a knowledge translation plan to disseminate the survey through social media and professional networks.
RESULTS
22 items were entered into a Delphi survey of which 28 respondents completed round 1, and 22 completed round 2. Seven items did not reach consensus in round 2. A total of 298 knowledge users participated in the survey (14% respondent rate). 75% indicated that their organisation produced NMAs, and 78% showed high interest in the tool, especially if they had received adequate training (84%). Most knowledge users and Delphi panellists preferred a tool to assess
CONCLUSIONS
This Delphi process and knowledge user survey informs the development of the RoB NMA tool.

Identifiants

DOI: 10.1136/bmjebm-2022-111944 PMID: 35948412
pubmed: 35948412
pii: bmjebm-2022-111944
doi: 10.1136/bmjebm-2022-111944
doi:

Types de publication

Meta-Analysis Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

58-67

Subventions

Organisme : World Health Organization
ID : 001
Pays : International

Informations de copyright

© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: AAV was an Associate Editor for the journal, but was not involved with the decision or peer-review process.

Auteurs

Carole Lunny (C)

Knowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada carole.lunny@ubc.ca.
Cochrane Hypertension Review Group, The University of British Columbia, Vancouver, British Columbia, Canada.
ORCID: 0000-0002-7825-6765

Areti Angeliki Veroniki (AA)

Knowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.
Epidemiology Division, Dalla Lana School of Public Health and Institute for Health, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada.

Brian Hutton (B)

Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.
ORCID: 0000-0001-5662-8647

Ian White (I)

MRC Clinical Trials Unit, University College London, London, UK.

Jpt Higgins (J)

Population Health Sciences, NIHR Applied Research Collaboration West (ARC West), University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.

James M Wright (JM)

Cochrane Hypertension Review Group, The University of British Columbia, Vancouver, British Columbia, Canada.

Ji Yoon Kim (JY)

McGill University, Montreal, Québec, Canada.

Sai Surabi Thirugnanasampanthar (SS)

University of Toronto, Toronto, Ontario, Canada.

Shazia Siddiqui (S)

Knowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.

Jennifer Watt (J)

Department of Medicine, University of Tornto, Toronto, ON, Canada.
ORCID: 0000-0002-5296-6013

Lorenzo Moja (L)

Department of Health Product Policy and Standards, World Health Organization, Geneva, Switzerland.

Nichole Taske (N)

Centre for Guidelines, National Institute for Health and Care Excellence (NICE), London, UK.

Robert C Lorenz (RC)

Medical Consultancy Department, Federal Joint Committee - Gemeinsamer Bundesausschuss (G-BA), Berlin, Germany.
ORCID: 0000-0003-3286-6792

Savannah Gerrish (S)

Simon Fraser University, Burnaby, British Columbia, Canada.

Sharon Straus (S)

Knowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.
Department of Medicine, University of Tornto, Toronto, ON, Canada.

Virginia Minogue (V)

Health Service Executive, Research and Evidence, Dublin, UK.

Franklin Hu (F)

Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.

Kevin Lin (K)

Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.

Ayah Kapani (A)

Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.

Samin Nagi (S)

Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.

Lillian Chen (L)

Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.

Mona Akbar-Nejad (M)

Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.

Andrea C Tricco (AC)

Knowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.
Epidemiology Division, Dalla Lana School of Public Health and Institute for Health, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada.

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Classifications MeSH

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