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Related Experiment Videos

Multicriteria benefit-risk assessment using network meta-analysis.

Gert van Valkenhoef1, Tommi Tervonen, Jing Zhao

  • 1Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands. g.h.m.van.valkenhoef@rug.nl

Journal of Clinical Epidemiology
|December 27, 2011
PubMed
Summary

A new method allows benefit-risk (BR) assessment for multiple treatments using clinical trial data. Placebo is often best for mild depression, while antidepressants suit severe cases, but choosing between them remains uncertain.

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Area of Science:

  • Health Economics and Outcomes Research
  • Clinical Trial Data Analysis
  • Decision Science

Background:

  • Multicriteria benefit-risk (BR) assessment is crucial for treatment selection.
  • Existing methods may not fully utilize evidence from networks of clinical trials.
  • Synthesizing evidence from Mixed Treatment Comparisons (MTC) for decision-making requires robust analytical tools.

Purpose of the Study:

  • To develop a general method for multicriteria decision aiding applicable to BR assessment.
  • To integrate evidence from MTC analyses for evaluating multiple treatment alternatives.
  • To enable the use of all available evidence from a network of clinical trials for comprehensive BR assessment.

Main Methods:

  • Designed a general method for multicriteria decision aiding.
  • Utilized criteria measurements derived from Mixed Treatment Comparison (MTC) analyses.
  • Applied the method to assess the benefit-risk profiles of four second-generation antidepressants and placebo, using data from a published systematic review.

Main Results:

  • Preference-free analysis indicated that placebo is supported across a wide range of potential patient preferences.
  • Incorporating expert preference information revealed that antidepressants are warranted for severely depressed patients, whereas placebo may be optimal for mild depression.
  • High uncertainty was observed when differentiating between the four antidepressants, highlighting challenges in direct comparison.

Conclusions:

  • The developed method facilitates quantitative benefit-risk analysis for alternative treatments by leveraging comprehensive evidence from clinical trial networks.
  • Preference-free analysis offers a valuable approach for presenting MTC results involving multiple outcomes.
  • The methodology supports informed clinical decision-making by providing a structured framework for evaluating treatment options.