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Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
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The Kilim plot: A tool for visualizing network meta-analysis results for multiple outcomes.

Michael Seo1, Toshi A Furukawa2, Areti Angeliki Veroniki3,4,5

  • 1Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.

Research Synthesis Methods
|June 12, 2020
PubMed
Summary
This summary is machine-generated.

Network meta-analysis (NMA) results for multiple outcomes are complex. A new graphical tool, the Kilim plot, simplifies NMA interpretation by showing absolute treatment effects and evidence strength for better clinical decisions.

Keywords:
indirect comparisonsmixed evidencemultiple outcomesmultiple treatments meta-analysisvisualization

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Area of Science:

  • Medical Statistics
  • Health Informatics
  • Clinical Epidemiology

Background:

  • Network meta-analysis (NMA) enables comparison of multiple treatments for a single disease.
  • Summarizing NMA results across numerous outcomes and treatments is challenging.
  • Relative effect measures from NMA, like odds ratios, can be difficult for clinical application.

Purpose of the Study:

  • To introduce a novel graphical tool, the Kilim plot, for enhanced visualization of NMA results.
  • To facilitate clinical decision-making by presenting NMA findings more intuitively.
  • To address the complexity of summarizing multi-outcome NMA data.

Main Methods:

  • Development of the Kilim plot, a graphical tool for NMA visualization.
  • Presentation of absolute treatment effects instead of relative measures.
  • Incorporation of statistical evidence strength and clinical significance considerations.
  • Application of the method to antidepressant treatment network data.
  • Provision of R source code and an interactive web application for the Kilim plot.

Main Results:

  • The Kilim plot compactly summarizes results for all treatments and outcomes.
  • It visually represents the strength of statistical evidence for treatment effects.
  • The plot illustrates absolute intervention effects, aiding clinical interpretation.
  • The tool is adaptable to include clinically important effect thresholds.

Conclusions:

  • The Kilim plot offers a valuable tool for simplifying and improving the interpretation of multi-outcome NMA.
  • It enhances clinical decision-making by presenting clear, absolute treatment effect data.
  • The developed method and accompanying resources promote wider adoption of NMA in practice.