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Cost-Effectiveness of Dabigatran Compared to Vitamin-K Antagonists for the Treatment of Deep Venous Thrombosis in the Netherlands Using Real-World Data

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  • Merlijn W J van Leent
  • Jelena Stevanović
  • Frank G Jansman
  • Maarten J Beinema
  • Jacobus R B J Brouwers
  • Maarten J Postma

Abstract

Background: Vitamin-K antagonists (VKAs) present an effective anticoagulant treatment in deep venous thrombosis (DVT). However, the use of VKAs is limited because of the risk of bleeding and the necessity of frequent and long-term laboratory monitoring. Therefore, new oral anticoagulant drugs (NOACs) such as dabigatran, with lower rates of (major) intracranial bleeding compared to VKAs and not requiring monitoring, may be considered. Objectives: To estimate resource utilization and costs of patients treated with the VKAs acenocoumarol and phenprocoumon, for the indication DVT. Furthermore, a formal cost-effectiveness analysis of dabigatran compared to VKAs for DVT treatment was performed, using these estimates. Methods: A retrospective observational study design in the thrombotic service of a teaching hospital (Deventer, The Netherlands) was applied to estimate real-world resource utilization and costs of VKA monitoring. A pooled analysis of data from RE-COVER and RE-COVER II on DVT was used to reflect the probabilities for events in the cost-effectiveness model. Dutch costs, utilities and specific data on coagulation monitoring levels were incorporated in the model. Next to the base case analysis, univariate probabilistic sensitivity and scenario analyses were performed. Results: Real-world resource utilization in the thrombotic service of patients treated with VKA for the indication of DVT consisted of 12.3 measurements of the international normalized ratio (INR), with corresponding INR monitoring costs of €138 for a standardized treatment period of 180 days. In the base case, dabigatran treatment compared to VKAs in a cohort of 1,000 DVT patients resulted in savings of €18,900 (95% uncertainty interval (UI) -95,832, 151,162) and 41 (95% UI -18, 97) quality-adjusted life-years (QALYs) gained calculated from societal perspective. The probability that dabigatran is cost-effective at a conservative willingness-to pay threshold of €20,000 per QALY was 99%. Sensitivity and scenario analyses also indicated cost savings or cost-effectiveness below this same threshold. Conclusions: Total INR monitoring costs per patient were estimated at minimally €138. Inserting these real-world data into a cost-effectiveness analysis for patients diagnosed with DVT, dabigatran appeared to be a cost-saving alternative to VKAs in the Netherlands in the base case. Cost savings or favorable cost-effectiveness were robust in sensitivity and scenario analyses. Our results warrant confirmation in other settings and locations.

Suggested Citation

  • Merlijn W J van Leent & Jelena Stevanović & Frank G Jansman & Maarten J Beinema & Jacobus R B J Brouwers & Maarten J Postma, 2015. "Cost-Effectiveness of Dabigatran Compared to Vitamin-K Antagonists for the Treatment of Deep Venous Thrombosis in the Netherlands Using Real-World Data," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-15, August.
  • Handle: RePEc:plo:pone00:0135054
    DOI: 10.1371/journal.pone.0135054
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    References listed on IDEAS

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    1. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629.
    2. L. M. Lamers & J. McDonnell & P. F. M. Stalmeier & P. F. M. Krabbe & J. J. V. Busschbach, 2006. "The Dutch tariff: results and arguments for an effective design for national EQ‐5D valuation studies," Health Economics, John Wiley & Sons, Ltd., vol. 15(10), pages 1121-1132, October.
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