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Cost-effectiveness analysis of rivaroxaban for treatment and secondary prevention of venous thromboembolism in the Netherlands
Background
Until recently, standard treatment of venous thromboembolism (VTE) concerned a combination of short-term low-molecular-weight heparin (LMWH) and long-term vitamin-K antagonist (VKA). Risk of bleeding and the requirement for regular anticoagulation monitoring are, however, limiting their use. Rivaroxaban is a novel oral anticoagulant associated with a significantly lower risk of major bleeds (hazard ratio?=?0.54, 95% confidence interval?=?0.37-0.79) compared to LMWH/VKA therapy, and does not require regular anticoagulation monitoring.
Aims
To evaluate the health economic consequences of treating acute VTE patients with rivaroxaban compared to treatment with LMWH/VKA, viewed from the Dutch societal perspective.
Methods
A life-time Markov model was populated with the findings of the EINSTEIN phase III clinical trial to analyze cost-effectiveness of rivaroxaban therapy in treatment and prevention of VTE from a Dutch societal perspective. Primary model outcomes were total and incremental quality-adjusted life years (QALYs), as well as life expectancy and costs.
Results
Over a patient’s lifetime, rivaroxaban was shown to be dominant, with health gains of 0.047 QALYs and cost savings of €304 compared to LMWH/VKA therapy. Dominance was robustly present in all sensitivity analyses. Major drivers of the differences between the two treatment arms were related to anticoagulation monitoring (medical costs, travel costs, and loss of productivity) and the occurrence of major bleeds.
Conclusion
Rivaroxaban treatment of patients with venous thromboembolism results in health gains and cost savings compared to LMWH/VKA therapy. This conclusion holds for the Dutch setting, both for the societal perspective, as well as the healthcare perspective.
Authors
M Heisen, M J Treur, H E Heemstra, E B W Giesen, M J Postma
Journal
Journal of medical economics
Therapeutic Area
Hematology
Center of Excellence
Health Economic Modeling & Meta-analysis
Year
2017
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