Cost-effectiveness of endovascular thrombectomy in patients with acute ischemic stroke. (15th March 2016)

• Record Type: Journal Article
• Authors: Aronsson, Mattias; Persson, Josefine; Blomstrand, Christian; Wester, Per; Levin, Lars-Åke
• Is Part Of: Neurology. Volume 86:Number 11(2016)
• Publication Date: 2016-03-15
• Subjects: Neurology -- Periodicals; Neurology -- Periodicals; Neurologie -- Périodiques; 616.8
• DOI: 10.1212/WNL.0000000000002439
• Languages: English
• ISSNs: 0028-3878

Abstract

Abstract : Objective: To evaluate the cost-effectiveness of adding endovascular thrombectomy to standard care in patients with acute ischemic stroke. Methods: The cost-effectiveness analysis of endovascular thrombectomy in patients with acute ischemic stroke was based on a decision-analytic Markov model. Primary outcomes from ESCAPE, Extending the Time for Thrombolysis in Emergency Neurological Deficits–Intra-Arterial (EXTEND-IA), Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN), Endovascular Revascularization With Solitaire Device Versus Best Medical Therapy in Anterior Circulation Stroke Within 8 Hours (REVASCAT), and Solitaire with the Intention for Thrombectomy as Primary Endovascular Treatment for Acute Ischemic Stroke (SWIFT PRIME) along with data from published studies and registries were used in this analysis. We used a health care payer perspective and a lifelong time horizon to estimate costs and effects. Results: The model showed that adding thrombectomy with stent retrievers to guideline-based care (including IV thrombolysis) resulted in a gain of 0.40 life-years and 0.99 quality-adjusted life-years along with a cost savings of approximately $221 per patient. The sensitivity analysis showed that the results were not sensitive to changes in uncertain parameters or assumptions. Conclusions: Adding endovascular treatment to standard care resulted in substantial clinical benefits at low costs. The results were consistent throughout irrespective of whether data from ESCAPE, EXTEND-IA, MR CLEAN, REVASCAT, or SWIFT PRIME were used in this model.