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Entscheiden trotz Unsicherheit: 14. Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin

Deutsches Netzwerk Evidenzbasierte Medizin e. V.

15.03. - 16.03.2013, Berlin

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Choosing a Tyrosine Kinase Inhibitor as First-line Therapy for Chronic Myeloid Leukemia under the Uncertainty of Long-term Effectiveness and Safety

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  • corresponding author Ursula Rochau - 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; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
  • author presenting/speaker Gaby Sroczynski - 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; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
  • author Dominik Wolf - Internal Medicine III, University of Bonn, Germany; Internal Medicine V, Hematology and Oncology, Medical University Innsbruck, Austria
  • author Stefan Schmidt - Internal Medicine V, Hematology and Oncology, Medical University Innsbruck, Austria
  • author Annette Conrads-Frank - 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
  • author Beate Jahn - 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; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
  • author Kim Saverno - 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; Department of Pharmacotherapy, University of Utah, Salt Lake City, Utah, USA
  • author Diana Brixner - Department of Pharmacotherapy and Program in Personalized Health Care, University of Utah, Salt Lake City, Utah, USA; Institute of Public Health, Medical Decision Making and HTA, Dept. of Public Health and Health Technology Assessment, UMIT - Univ. for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, HTA and Health Economics, ONCOTYROL - Center for Personalized Medicine, Innsbruck, Austria
  • author Günther Gastl - Internal Medicine V, Hematology and Oncology, Medical University Innsbruck, Austria
  • author Jerry Radich - Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
  • author Uwe Siebert - Institute of Public Health, Medical Decision Making and HTA, Depart. of Public Health and HTA, UMIT – Univ. for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, HTA and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria; Center for Health Decision Science, Harvard School of Public Health, Boston, MA, USA; MGH, Harvard Medical School, Boston, MA, USA

Entscheiden trotz Unsicherheit. 14. Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin. Berlin, 15.-16.03.2013. Düsseldorf: German Medical Science GMS Publishing House; 2013. Doc13ebmP13

doi: 10.3205/13ebm040, urn:nbn:de:0183-13ebm0402

Published: March 11, 2013

© 2013 Rochau et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.

Outline

Text

Background: The introduction of the tyrosine kinase inhibitor (TKI) imatinib about a decade ago dramatically extended the life span of chronic myeloid leukemia (CML) patients. Currently, there are several different TKIs approved for CML treatment. Long-term effectiveness and safety data for second-generation TKIs are not yet available. Despite this uncertainty about long-term effects, patients and physicians have to choose a first-line therapy. The aim of our study is to develop a clinical decision-analytic model to extrapolate short-term outcomes and to evaluate the comparative long-term effectiveness of first-line therapy for CML within the Austrian health care context.

Methods: We developed a Markov state-transition model for patients in the chronic-phase of CML treated with first-line TKI imatinib, dasatinib or nilotinib. Seven different strategies including different combinations of first and second-generation TKIs as well as chemotherapy or stem cell transplantation were evaluated. The model was parameterized using published trial data, data from the Austrian CML registry and from an Austrian CML expert panel [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]. The model was analyzed as a cohort simulation over a lifelong time horizon. Health outcomes evaluated were life-years (LYs) gained and quality-adjusted life years (QALYs) gained. Deterministic and structural sensitivity analyses were performed.

Results: Nilotinib followed by dasatinib after failure is the most effective treatment in terms of both LYs gained (19.7 LY) and QALYs gained (17.1 QALYs). All strategies including a second-line TKI were superior compared to strategies without second-line TKI. Deterministic sensitivity analyses showed that the ranking of the strategies was mostly influenced by the duration of first- and second-line therapies. In a structural sensitivity analysis, where patients move directly from second-line TKI therapy to advanced stage of disease, strategies without second-line therapy are most effective.

Conclusions: Based on our analyses results, the most clinically effective strategy is nilotinib followed by dasatinib as second-line therapy. All three TKIs are approved as first-line therapy in Austria. Our results may support clinicians and patients in their decision making.

Outline

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