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Vitruvian plot: a visualisation tool for multiple outcomes in network meta-analysis.

Edoardo Giuseppe Ostinelli1,2,3, Orestis Efthimiou1,4,5, Huseyin Naci6

  • 1Department of Psychiatry, University of Oxford, Oxford, UK.

Evidence-Based Mental Health
|May 25, 2022
PubMed
Summary
This summary is machine-generated.

The Vitruvian plot visually summarizes multiple outcomes from network meta-analyses (NMAs) for patients and clinicians. This tool enhances communication of treatment comparisons and evidence credibility.

Keywords:
PSYCHIATRY

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Area of Science:

  • Health Sciences
  • Medical Informatics
  • Biostatistics

Background:

  • Network meta-analysis (NMA) often involves complex data with multiple outcomes and treatment comparisons.
  • Effective communication of NMA results to diverse audiences, including patients and clinicians, is crucial for informed decision-making.
  • Existing methods for presenting NMA results may not adequately convey the nuances of benefit-risk information.

Purpose of the Study:

  • To introduce and describe the Vitruvian plot, a novel visualization tool for network meta-analysis.
  • To facilitate the clear communication of multiple outcomes and treatment comparisons from NMAs.
  • To enhance the understanding of evidence credibility for patients and clinicians.

Main Methods:

  • Development of the Vitruvian plot tool based on literature recommendations for communicating benefit-risk information.
  • Incorporation of feedback from a multidisciplinary group, including researchers, statisticians, clinicians, and patient representatives.
  • Utilizing the Confidence in Network Meta-Analysis (CINeMA) system to evaluate evidence confidence across six domains.

Main Results:

  • The Vitruvian plot graphically displays absolute estimates and relative intervention performance against a common comparator for multiple outcomes.
  • Two color schemes are offered to highlight either the strength or confidence of statistical evidence.
  • Confidence in evidence is systematically assessed using the CINeMA framework, covering bias, imprecision, heterogeneity, and incoherence.

Conclusions:

  • The Vitruvian plot effectively presents multiple outcomes from NMAs in a user-friendly graphical format.
  • Color-coding within the plot aids in informing users about the credibility of the presented evidence.
  • This tool supports better interpretation and communication of complex NMA findings.