Decision-analytic modeling studies: An overview for clinicians using multiple myeloma as an example. Issue 2 (May 2015)

• Record Type: Journal Article
• Authors: Rochau, U.; Jahn, B.; Qerimi, V.; Burger, E.A.; Kurzthaler, C.; Kluibenschaedl, M.; Willenbacher, E.; Gastl, G.; Willenbacher, W.; Siebert, U.
• Is Part Of: Critical reviews in oncology/hematology. Volume 94:Issue 2(2015)
• Page Start: 164
• Page End: 178
• Publication Date: 2015-05
• Subjects: Oncology -- Periodicals; Hematology -- Periodicals; 616.994
• DOI: 10.1016/j.critrevonc.2014.12.017
• Languages: English
• ISSNs: 1040-8428

Abstract

<abstract abstract-type="author" id="abs0005"> <title id="sect0005">Abstract</title> <sec> <title id="sect0010">Purpose</title> <p id="spar0005">The purpose of this study was to provide a clinician-friendly overview of decision-analytic models evaluating different treatment strategies for multiple myeloma (MM).</p> </sec> <sec> <title id="sect0015">Methods</title> <p id="spar0010">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).</p> </sec> <sec> <title id="sect0020">Results</title> <p id="spar0015">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.</p> </sec> <sec> <title id="sect0025">Conclusion</title> <p id="spar0020">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.</p> </sec> </abstract>