Evidence map›Paper›PMID 38217041›Full record

ArticleSystematic reviews2024

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).

Carole Lunny, Areti-Angeliki Veroniki, Julian P T Higgins, Sofia Dias, Brian Hutton, James M Wright, Ian R White, Penny Whiting, Andrea C Tricco

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Systematic reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

9 authors.

Carole LunnyKnowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, 209 Victoria Street, East Building, Toronto, ON, M5B 1T8, Canada. carole.lunny@ubc.ca.ORCID 0000-0002-7825-6765
Areti-Angeliki VeronikiKnowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, 209 Victoria Street, East Building, Toronto, ON, M5B 1T8, Canada.ORCID 0000-0001-6388-4825
Julian P T HigginsPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Sofia DiasCentre for Reviews and Dissemination, University of York, York, UK.ORCID 0000-0002-2172-0221
Brian HuttonOttawa Hospital Research Institute, Ottawa, Canada.
James M WrightCochrane Hypertension Review Group, the Therapeutics Initiative, University of British Columbia, Vancouver, Canada.
Ian R WhiteMRC Clinical Trials Unit at UCL, London, UK.ORCID 0000-0002-6718-7661
Penny WhitingPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Andrea C TriccoKnowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, 209 Victoria Street, East Building, Toronto, ON, M5B 1T8, Canada.

Funding

Medical Research Council MC_UU_00004/06
6 · The paper itself

Abstract

introductionNetwork 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).

resultsOne 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.

conclusionsA 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.

Indexed as

ChecklistBiasHumansNetwork Meta-Analysis as TopicChecklistCritical appraisalIndirect comparisonMixed treatment comparisonMultiple treatment comparisonNetwork meta-analysisQualityRisk of biasStandardTool

Identifiers

PMID38217041
PMCPMC10785511

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.