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MPES-R: Multi-Parameter Evidence Synthesis in R for Survival Extrapolation-A Tutorial.

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Summary

Multi-parameter evidence synthesis (MPES) offers a way to improve survival extrapolation in health technology assessment (HTA) by using external data. This tutorial introduces MPES and provides R code for its application in HTA.

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Area of Science:

  • Health Economics
  • Biostatistics
  • Health Technology Assessment

Background:

  • Survival extrapolation is crucial for health technology assessment (HTA).
  • Conventional methods face uncertainty, prompting the need for approaches leveraging external evidence.
  • Multi-parameter evidence synthesis (MPES) is an advanced method for survival extrapolation.

Purpose of the Study:

  • To introduce Multi-parameter Evidence Synthesis (MPES) for Health Technology Assessment (HTA).
  • To provide a user-friendly R implementation of Guyot's MPES approach.
  • To explore Guyot's and Jackson's MPES methods through case studies and sensitivity analyses.

Main Methods:

  • Tutorial-based introduction to MPES for HTA.
  • Development of an R package for operationalizing Guyot's MPES.
  • Application of MPES approaches in two distinct case studies with sensitivity analyses.

Main Results:

  • MPES offers potential benefits over traditional parametric models for survival extrapolation.
  • The provided R operationalization facilitates practical application of MPES in HTA.
  • Case studies demonstrate the exploration of MPES approaches and sensitivity analyses.

Conclusions:

  • MPES is a valuable, though complex, tool for survival extrapolation in HTA.
  • The tutorial aids analysts in understanding and applying MPES.
  • Further research and examples are encouraged to increase MPES adoption in HTA.