Gesundheitswesen 2015; 77 - A55
DOI: 10.1055/s-0035-1563011

Cost-effectiveness of methods in personalized medicine. Results of a decision-analytic model in patients with AML

L Hörster 1, J Wasem 2, A Ganser 3, M Stadler 3, RF Schlenk 4, M Port 3, M Gabriel 3, J Schildmann 5, U Rochau 6, 7, G Sroczynski 6
  • 1Universität Duisburg-Essen, Lehrstuhl für Medizinmanagement, Essen
  • 2Universität Duisburg-Essen, Lehrstuhl für Medizinmanagement
  • 3Klinik für Hämatologie, Hämostaseologie, Onkologie und Stammzelltransplantation; Medizinische Hochschule Hannover, Hannover
  • 4Klinik für Innere Medizin III, Universitätsklinikum Ulm, Ulm
  • 5Institut für Medizinische Ethik und Geschichte der Medizin, Ruhr-Universität Bochum, Bochum
  • 6Institute 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 in Tirol
  • 7Area 4 Health Technology Assessment and Bioinformatics, ONCOTYROL – Center for Personalized Cancer Medicine, Innsbruck

Introduction/Background: Acute myeloid leukemia is a clonal disease of hematopoietic progenitor cells and can lead to death within a few weeks without treatment. In recent times increasingly cytogenetic and even more importantly molecular genetic data are used in prognostication of clinical outcome including response to intensive chemotherapy and survival. Nowadays the genetic profile permits a detailed risk-classification of AML-patients. Beyond prognostication the genetic profile also allows prediction of the efficacy of a specific treatment in a distinct genetic subgroup. Aim of this study is to evaluate the cost-effectiveness of two different strategies of risk-classification using decision-analytic Markov model. Data/Methods: A Markov model for the natural disease of AML for the German health care context has been developed and evaluates the health economic consequences of two different strategies (conventional cytogenetic diagnostics versus molecular genetic diagnostics). The model was parameterized using trial data from the German Austrian AML study group, completed with estimations by experts, and cost data from Hannover Medical School. Trial data refer to 870 patients with a median age of 46 years and a normal karyotype in the cytogenetically defined group, while 532 patients with a median age of 47 belong to the molecular genetic group. Time horizon of analysis was determined to ten years with a cycle length of one month. Outcomes evaluated were survival per month. The Markov model was analyzed as a microsimulation with 1,000,000 individual patients. Results: We developed a Markov model with 13 health states. First results show higher costs in Euro per person in ten years with increased median survival for the strategy using molecular diagnostics. Conclusion: The first results of the simulation are located in the north-eastern quadrant of the cost-effectiveness plane, with more effective treatment but higher costs. In further considerations the ICER of the results has to be evaluated.