Evidence map›Paper›PMID 31647136›Full record

ArticleStatistics in medicine2019

Identifying inconsistency in network meta-analysis: Is the net heat plot a reliable method?

Suzanne C Freeman, David Fisher, Ian R White, Anne Auperin, James R Carpenter

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Statistics in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 13 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

24 citing papers in PubMed, 13 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Ticagrelor Paradox: Systematic Review and Network Meta-Analysis.Journal of the American Heart Association · 2025
    Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Comparative safety of high-efficacy disease-modifying therapies in relapsing-remitting multiple sclerosis: a systematic review and network meta-analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2022
    Pooled it
  11. Pooled it
  12. Pooled it
  13. Pooled it
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Suzanne C FreemanMRC Clinical Trials Unit at UCL, London, UK.ORCID 0000-0001-8045-4405
David FisherMRC Clinical Trials Unit at UCL, London, UK.
Ian R WhiteMRC Clinical Trials Unit at UCL, London, UK.ORCID 0000-0002-6718-7661
Anne AuperinMeta-Analysis Platform, Biostatistics and Epidemiology unit, Gustave Roussy and INSERM U1018, Levallois-Perret, France.
James R CarpenterMRC Clinical Trials Unit at UCL, London, UK.

Funding

Medical Research Council MC_UU_12023/21
6 · The paper itself

Abstract

One of the biggest challenges for network meta-analysis is inconsistency, which occurs when the direct and indirect evidence conflict. Inconsistency causes problems for the estimation and interpretation of treatment effects and treatment contrasts. Krahn and colleagues proposed the net heat approach as a graphical tool for identifying and locating inconsistency within a network of randomized controlled trials. For networks with a treatment loop, the net heat plot displays statistics calculated by temporarily removing each design one at a time, in turn, and assessing the contribution of each remaining design to the inconsistency. The net heat plot takes the form of a matrix which is displayed graphically with coloring indicating the degree of inconsistency in the network. Applied to a network of individual participant data assessing overall survival in 7531 patients with lung cancer, we were surprised to find no evidence of important inconsistency from the net heat approach; this contradicted other approaches for assessing inconsistency such as the Bucher approach, Cochran's Q statistic, node-splitting, and the inconsistency parameter approach, which all suggested evidence of inconsistency within the network at the 5% level. Further theoretical work shows that the calculations underlying the net heat plot constitute an arbitrary weighting of the direct and indirect evidence which may be misleading. We illustrate this further using a simulation study and a network meta-analysis of 10 treatments for diabetes. We conclude that the net heat plot does not reliably signal inconsistency or identify designs that cause inconsistency.

Indexed as

BiostatisticsComputer GraphicsComputer SimulationDatabases, FactualDiabetes Mellitus, Type 2HumansHypoglycemic AgentsLung NeoplasmsModels, StatisticalNetwork Meta-Analysis as TopicHypoglycemic Agentsinconsistencynet heat plotnetwork meta-analysis

Identifiers

PMID31647136
PMCPMC6899484

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.