Evidence map›Paper›PMID 35948412›Full record

ArticleBMJ evidence-based medicine2023

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).

Carole Lunny, Areti Angeliki Veroniki, Brian Hutton, Ian White, Jpt Higgins, James M Wright, Ji Yoon Kim, Sai Surabi Thirugnanasampanthar, Shazia Siddiqui, Jennifer Watt and 13 more

Abstract read
In one paragraph

Article in BMJ evidence-based medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors.

Carole LunnyKnowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada carole.lunny@ubc.ca.ORCID 0000-0002-7825-6765
Areti Angeliki VeronikiKnowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.
Brian HuttonOttawa Hospital Research Institute, Ottawa, Ontario, Canada.ORCID 0000-0001-5662-8647
Ian WhiteMRC Clinical Trials Unit, University College London, London, UK.
Jpt HigginsPopulation Health Sciences, NIHR Applied Research Collaboration West (ARC West), University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.
James M WrightCochrane Hypertension Review Group, The University of British Columbia, Vancouver, British Columbia, Canada.
Ji Yoon KimMcGill University, Montreal, Québec, Canada.
Sai Surabi ThirugnanasampantharUniversity of Toronto, Toronto, Ontario, Canada.
Shazia SiddiquiKnowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.
Jennifer WattDepartment of Medicine, University of Tornto, Toronto, ON, Canada.ORCID 0000-0002-5296-6013
Lorenzo MojaDepartment of Health Product Policy and Standards, World Health Organization, Geneva, Switzerland.
Nichole TaskeCentre for Guidelines, National Institute for Health and Care Excellence (NICE), London, UK.
Robert C LorenzMedical Consultancy Department, Federal Joint Committee - Gemeinsamer Bundesausschuss (G-BA), Berlin, Germany.ORCID 0000-0003-3286-6792
Savannah GerrishSimon Fraser University, Burnaby, British Columbia, Canada.
Sharon StrausKnowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.
Virginia MinogueHealth Service Executive, Research and Evidence, Dublin, UK.
Franklin HuFaculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.
Kevin LinFaculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.
Ayah KapaniFaculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.
Samin NagiFaculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.
Lillian ChenFaculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.
Mona Akbar-NejadFaculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada.
Andrea C TriccoKnowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.

Funding

Medical Research Council MC_UU_00004/06World Health Organization 001
6 · The paper itself

Abstract

backgroundNetwork 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.

objectivesConduct (a) a Delphi process to determine expert opinion on an item's inclusion and (b) a knowledge user survey to widen its impact.

designCross-sectional survey and Delphi process.

methodsDelphi 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.

results22 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

conclusionsThis Delphi process and knowledge user survey informs the development of the RoB NMA tool.

Indexed as

Delphi TechniqueNetwork Meta-Analysis as TopicSystematic Reviews as TopicBiasCross-Sectional StudiesSurveys and Questionnairesevidence-based practicehealth care quality, access, and evaluationhealth services researchmethods

Identifiers

PMID35948412
PMCPMC11372759

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.