Background: Previous studies have shown that patients with Acute Ischemic Stroke (AIS) treated with recombinant tissue plasminogen activator (rtPA) have better clinical and in several cases economic outcomes than those who are not. However, the cost-effectiveness of rtPA in the Greek setting is totally unknown. This study aims to evaluate the cost-effectiveness of rtPA for the management of AIS in Greece based on real world data (RWD).

Methods: A cost-effectiveness model was developed in Microsoft® Excel to examine the clinical and economic impact of rtPA from a Greek third-party payer perspective based on RWD collected during the “Improving Stroke Care in Greece in Terms of Management, Costs and Health Outcomes” project, with the participation of nine Greek hospitals from different cities. The primary outcome of the analysis was the incremental cost-effectiveness ratio (ICER) expressed in euros per quality adjusted life year (QALY). The primary clinical outcome was the mRS value at 3 months. Robustness of the results was tested using both one-way and probabilistic sensitivity analyses.

Results: Compared with conservative management, rtPA led to 0.009 incremental QALYs per patient in the first 3 months. The total cost per patient incurred by the rtPA group was 2,196.65€, compared to 2,499.45€ in the conservative treatment group, leading to 302.79€ savings per patient, indicating that rtPA is more effective and costs less than conservative management from a Greek third-party payer perspective. However, probabilistic sensitivity analyses (PSA) showed that there is a significant variability and the probability of rtPA to be cost effective or dominant in the Greek setting is between 58.9%-74.1% within the threshold of one to three times the national GDP per capita.

Conclusion: Intravenous rtPA represents a dominant or cost-effective strategy for the management of AIS in Greece. The analysis may have underestimated the potential benefits of rtPA. Although this study provides additional evidence to decision-makers, more data are required to improve the robustness of the conclusion