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Volume 17, Issue 2, Pages 183-195 (March 2014)
Core Discrete Event Simulation Model for the Evaluation of Health Care Technologies in Major Depressive Disorder Anne-Lise Vataire, MSc, Samuel Aballéa, MSc, Fernando Antonanzas, Pr, Leona Hakkaart-van Roijen, MD, Raymond W. Lam, MD, Paul McCrone, PhD, Ulf Persson, PhD, Mondher Toumi, PhD Value in Health Volume 17, Issue 2, Pages (March 2014) DOI: /j.jval Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions
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Fig. 1 Example of treatment strategy (“medium treatment strategy”). AE, adverse event; LoE, lack of efficacy. Value in Health , DOI: ( /j.jval ) Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions
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Fig. 2 Model structure. Value in Health , DOI: ( /j.jval ) Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions
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Fig. 3 Distribution of average number of days and costs by year and clinical status. QALYs, quality-adjusted life-years. Value in Health , DOI: ( /j.jval ) Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions
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Fig. 4 Distribution of costs by year and clinical status.
Value in Health , DOI: ( /j.jval ) Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions
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Fig. 5 Tornado charts for non–treatment-relative parameters. QALYs, quality-adjusted life-years. Each bar represents the variation of the difference in QALYs and societal costs when the input values are changed according to scenarios specified in the Table 1. The vertical line represents the base case. Assumptions are shown in bold font. Value in Health , DOI: ( /j.jval ) Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions
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