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Comparison of Methods for Estimating Therapy Effects by Indirect Comparisons: A Simulation Study.

Dorothea Weber1, Katrin Jensen1, Meinhard Kieser1

  • 1Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Baden-Württemberg, Germany.

Medical Decision Making : an International Journal of the Society for Medical Decision Making
|July 14, 2020
PubMed
Summary

Indirect comparisons in evidence synthesis are often underpowered and lack superior methods. Careful selection of effect modifiers is crucial for precision, and results should be interpreted cautiously due to potential bias.

Keywords:
BucherMAICanchored indirect comparisonevidence synthesispopulation adjustment

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Area of Science:

  • Evidence synthesis
  • Comparative effectiveness research
  • Biostatistics

Background:

  • Therapeutic options require comparison even without head-to-head trials.
  • Indirect comparisons are common but their performance with cross-trial heterogeneity is unclear.

Purpose of the Study:

  • To evaluate the performance of matching adjusted indirect comparison (MAIC), simulated treatment comparison (STC), and Bucher methods.
  • To assess power, type I error, bias, and RMSE in various scenarios for binary and time-to-event data.

Main Methods:

  • Simulation study comparing MAIC, STC, and Bucher methods.
  • Evaluation based on statistical performance metrics (power, type I error, bias, RMSE).
  • Investigation of the impact of planned head-to-head trial power on indirect comparison power.

Main Results:

  • Indirect comparisons demonstrated considerable underpowering across all evaluated methods.
  • MAIC and Bucher yielded similar results without effect modification; Bucher preserved randomization.
  • MAIC and STC showed potential power gains but risked type I error inflation; adjusting for non-effect modifiers increased bias and RMSE.

Conclusions:

  • The selection of effect modifiers significantly impacts the precision of indirect comparisons.
  • Missed trial differences can lead to low power and high bias, necessitating cautious interpretation of indirect comparison results.