OBJECTIVE: To assess the cost-effectiveness of dabigatran etexilate ('dabigatran') vs vitamin K antagonists (VKAs) in the Belgian healthcare setting for the prevention of stroke and systemic embolism (SE) in patients with non-valvular atrial fibrillation (AF). RESEARCH DESIGN AND METHODS: A Markov model was used to calculate the cost-effectiveness of dabigatran vs VKAs in Belgium, whereby warfarin was considered representative for the VKA class. Efficacy and safety data were taken from the Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY) trial and a network meta-analysis. Local resource use and unit costs were included in the model. Effectiveness was expressed in Quality Adjusted Life-Years (QALYs). The model outcomes were total costs, total QALYs, incremental costs, incremental QALYs and the incremental cost-effectiveness ratio (ICER). The level of International Normalized Ratio (INR) control and the use of other antithrombotic therapies observed in Belgian clinical practice were reflected in two scenario analyses. RESULTS: In the base case analysis, total costs per patient were €13,333 for dabigatran and €12,454 for warfarin. Total QALYs per patient were 9.51 for dabigatran and 9.19 for warfarin. The corresponding ICER was €2807/QALY. The ICER of dabigatran was €970/QALY vs warfarin with real-world INR control and €5296/QALY vs a mix of warfarin, aspirin, and no treatment. Results were shown to be robust in one-way and probabilistic sensitivity analyses. LIMITATIONS: The analysis does not include long-term costs for clinical events, as these data were not available for Belgium. As in any economic model based on data from a randomized clinical trial, several assumptions had to be made when extrapolating results to routine clinical practice in Belgium. CONCLUSION: This analysis suggests that dabigatran, a novel oral anticoagulant, is a cost-effective treatment for the prevention of stroke and SE in patients with non-valvular AF in the Belgian healthcare setting.
OBJECTIVE: To assess the cost-effectiveness of dabigatran etexilate ('dabigatran') vs vitamin K antagonists (VKAs) in the Belgian healthcare setting for the prevention of stroke and systemic embolism (SE) in patients with non-valvular atrial fibrillation (AF). RESEARCH DESIGN AND METHODS: A Markov model was used to calculate the cost-effectiveness of dabigatran vs VKAs in Belgium, whereby warfarin was considered representative for the VKA class. Efficacy and safety data were taken from the Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY) trial and a network meta-analysis. Local resource use and unit costs were included in the model. Effectiveness was expressed in Quality Adjusted Life-Years (QALYs). The model outcomes were total costs, total QALYs, incremental costs, incremental QALYs and the incremental cost-effectiveness ratio (ICER). The level of International Normalized Ratio (INR) control and the use of other antithrombotic therapies observed in Belgian clinical practice were reflected in two scenario analyses. RESULTS: In the base case analysis, total costs per patient were €13,333 for dabigatran and €12,454 for warfarin. Total QALYs per patient were 9.51 for dabigatran and 9.19 for warfarin. The corresponding ICER was €2807/QALY. The ICER of dabigatran was €970/QALY vs warfarin with real-world INR control and €5296/QALY vs a mix of warfarin, aspirin, and no treatment. Results were shown to be robust in one-way and probabilistic sensitivity analyses. LIMITATIONS: The analysis does not include long-term costs for clinical events, as these data were not available for Belgium. As in any economic model based on data from a randomized clinical trial, several assumptions had to be made when extrapolating results to routine clinical practice in Belgium. CONCLUSION: This analysis suggests that dabigatran, a novel oral anticoagulant, is a cost-effective treatment for the prevention of stroke and SE in patients with non-valvular AF in the Belgian healthcare setting.
Authors: Taru Hallinen; Erkki Soini; Christian Asseburg; Miika Linna; Pia Eloranta; Sari Sintonen; Mikko Kosunen Journal: Clinicoecon Outcomes Res Date: 2021-08-13
Authors: Charalampos Kasmeridis; Stavros Apostolakis; Lars Ehlers; Lars H Rasmussen; Giuseppe Boriani; Gregory Y H Lip Journal: Pharmacoeconomics Date: 2013-11 Impact factor: 4.981
Authors: Joris Kleintjens; Xiao Li; Steven Simoens; Vincent Thijs; Marnix Goethals; Ernst R Rietzschel; Yumi Asukai; Ömer Saka; Thomas Evers; Petra Faes; Stefaan Vansieleghem; Mimi De Ruyck Journal: Pharmacoeconomics Date: 2013-10 Impact factor: 4.981