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The maraca plot: A novel visualization of hierarchical composite endpoints.

Martin Karpefors1, Daniel Lindholm1, Samvel B Gasparyan1

  • 1Late Stage Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.

Clinical Trials (London, England)
|November 14, 2022
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Summary

Visualizing complex hierarchical composite endpoints is challenging. A new maraca plot effectively displays treatment effects for both time-to-event and continuous outcomes, improving interpretation.

Keywords:
Hierarchical composite endpointsKansas City Cardiomyopathy QuestionnaireKaplan–Meier plotbox plotheart failuremaraca plotviolin plotvisualizationwin oddswin ratio

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Data Visualization

Background:

  • Hierarchical composite endpoints integrate diverse outcomes by clinical importance.
  • Analyzing these endpoints often uses win odds, but visualization tools are lacking.
  • Interpreting treatment effects in complex, multi-type event data is difficult.

Purpose of the Study:

  • To introduce a novel visualization tool for hierarchical composite endpoints.
  • To address the challenge of interpreting treatment effects in complex endpoints.
  • To provide a method for visualizing both time-to-event and continuous outcomes.

Main Methods:

  • The study introduces the "maraca plot" for visualizing hierarchical composite endpoints.
  • This novel plot integrates violin plots (with nested box plots) for continuous data.
  • It also incorporates Kaplan-Meier plots for time-to-event data.

Main Results:

  • The maraca plot offers a comprehensive visualization of hierarchical composite endpoints.
  • It effectively displays the density distribution of continuous outcomes.
  • Kaplan-Meier plots within the visualization represent time-to-event data.

Conclusions:

  • The maraca plot is a novel and effective tool for visualizing hierarchical composite endpoints.
  • Its simple structure facilitates communication of overall and component-specific treatment effects.
  • This visualization aids in understanding treatment impacts on mixed-type outcomes.