title: Decision-analytic modeling studies: An overview for clinicians using multiple myeloma as an example.
abstract: OBJECTIVE
  The purpose of this study was to provide a clinician-friendly overview of decision-analytic models evaluating different treatment strategies for multiple myeloma (MM).
  
  
  METHODS
  We performed a systematic literature search to identify studies evaluating MM treatment strategies using mathematical decision-analytic models. We included studies that were published as full-text articles in English, and assessed relevant clinical endpoints, and summarized methodological characteristics (e.g., modeling approaches, simulation techniques, health outcomes, perspectives).
  
  
  RESULTS
  Eleven decision-analytic modeling studies met our inclusion criteria. Five different modeling approaches were adopted: decision-tree modeling, Markov state-transition modeling, discrete event simulation, partitioned-survival analysis and area-under-the-curve modeling. Health outcomes included survival, number-needed-to-treat, life expectancy, and quality-adjusted life years. Evaluated treatment strategies included novel agent-based combination therapies, stem cell transplantation and supportive measures.
  
  
  CONCLUSIONS
  Overall, our review provides a comprehensive summary of modeling studies assessing treatment of MM and highlights decision-analytic modeling as an important tool for health policy decision making.
authors.affiliation: Institute 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. Electronic address: ursula.rochau@umit.at.
authors.forename: U
authors.initials: U
authors.lastname: Rochau
authors.affiliation: Institute 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. Electronic address: beate.jahn@umit.at.
authors.forename: B
authors.initials: B
authors.lastname: Jahn
authors.affiliation: Institute 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; Faculty of Pharmacy, School of PhD Studies, Ss. Cyril and Methodius University in Skopje, Macedonia. Electronic address: vjollca.qerimi@umit.at.
authors.forename: V
authors.initials: V
authors.lastname: Qerimi
authors.affiliation: Department of Health Management and Health Economics, University of Oslo, Norway; Center for Health Decision Science, Department of Health Policy and Management, Harvard School of Public Health, Boston, MA, USA. Electronic address: emily.burger@medisin.uio.no.
authors.forename: E A
authors.initials: EA
authors.lastname: Burger
authors.affiliation: Institute 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. Electronic address: christina.kurzthaler@umit.at.
authors.forename: C
authors.initials: C
authors.lastname: Kurzthaler
authors.affiliation: Institute 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. Electronic address: martina.kluibenschaedl@umit.at.
authors.forename: M
authors.initials: M
authors.lastname: Kluibenschaedl
authors.affiliation: Area 4 Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria; Internal Medicine V, Hematology and Oncology, Medical University, Innsbruck, Austria. Electronic address: ella.willenbacher@i-med.ac.at.
authors.forename: E
authors.initials: E
authors.lastname: Willenbacher
authors.affiliation: Area 4 Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria; Internal Medicine V, Hematology and Oncology, Medical University, Innsbruck, Austria. Electronic address: guenther.gastl@i-med.ac.at.
authors.forename: G
authors.initials: G
authors.lastname: Gastl
authors.affiliation: Area 4 Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria; Internal Medicine V, Hematology and Oncology, Medical University, Innsbruck, Austria. Electronic address: wolfgang.willenbacher@uki.at.
authors.forename: W
authors.initials: W
authors.lastname: Willenbacher
authors.affiliation: Institute 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; Center for Health Decision Science, Department of Health Policy and Management, Harvard School of Public Health, Boston, MA, USA; Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: uwe.siebert@umit.at.
authors.forename: U
authors.initials: U
authors.lastname: Siebert
mesh_terms: D003198:Computer Simulation; D003362:Cost-Benefit Analysis; D003657:Decision Making; D003661:Decision Support Techniques; D019468:Disease Management; D006801:Humans; D015233:Models, Statistical; D009101:Multiple Myeloma / Q000175:diagnosis / Q000401:mortality / Q000628:therapy; D016019:Survival Analysis
keywords: Cost–effectiveness analysis; Decision-analytic modeling; Health economic modeling; Multiple myeloma; Systematic overview