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Area of Science:

  • Health Economics
  • Biostatistics
  • Clinical Trials

Background:

  • Cost-effectiveness analyses (CEA) are crucial for healthcare decision-making.
  • Missing data, particularly missing not at random (MNAR), can compromise the validity of CEA.
  • Existing guidelines recommend sensitivity analyses for MNAR data, but practical implementation is limited.

Purpose of the Study:

  • To provide a practical framework and guidance for conducting sensitivity analysis for MNAR data in trial-based CEA.
  • To address the lack of accessible methods for handling MNAR data in economic evaluations.

Main Methods:

  • Review of sensitivity analysis methods for MNAR data.
  • Focus on a practical approach using multiple imputation and data modification.
  • Illustration with a weight-loss trial, including software code.

Main Results:

  • Demonstration of an accessible method for sensitivity analysis in trial-based CEA.
  • Practical guidance and software implementation for handling MNAR data.

Conclusions:

  • Sensitivity analysis for MNAR data is feasible and essential for robust CEA.
  • The presented framework can improve the reliability of economic evaluations in healthcare.