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Updated: Apr 18, 2026

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Decision-analytic modeling studies: An overview for clinicians using multiple myeloma as an example.

U Rochau1, B Jahn2, V Qerimi3

  • 1Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Area 4 Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria.

Critical Reviews in Oncology/Hematology
|January 27, 2015
PubMed
Summary

Decision-analytic models aid in evaluating multiple myeloma (MM) treatments. This review summarizes these models, offering insights for clinical and health policy decisions.

Keywords:
Cost–effectiveness analysisDecision-analytic modelingHealth economic modelingMultiple myelomaSystematic overview

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Area of Science:

  • Oncology
  • Health Economics
  • Biostatistics

Background:

  • Multiple myeloma (MM) treatment involves complex decisions.
  • Mathematical modeling offers a framework for evaluating therapeutic strategies.

Purpose of the Study:

  • To provide a clinician-friendly overview of decision-analytic models for multiple myeloma (MM) treatment.
  • To synthesize the application of mathematical modeling in MM therapy evaluation.

Main Methods:

  • Systematic literature search for decision-analytic modeling studies in MM.
  • Inclusion of full-text English articles assessing clinical endpoints.
  • Summarization of methodological characteristics, including modeling approaches and health outcomes.

Main Results:

  • Eleven studies met inclusion criteria.
  • Five modeling approaches were identified: decision-tree, Markov, discrete event simulation, partitioned-survival, and area-under-the-curve.
  • Evaluated treatments included novel therapies, stem cell transplantation, and supportive care, with outcomes like survival and quality-adjusted life years.

Conclusions:

  • Decision-analytic modeling is a valuable tool for multiple myeloma treatment assessment.
  • This review highlights the importance of modeling in informing health policy for MM treatment strategies.