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Cost-effectiveness of TTVR with EVOQUE system in patients with Severe Tricuspid Regurgitation based on TRISCEND II
Apolline Grangeon1, Martin Connock2, Peter Auguste2
1University Claude Bernard ISPB, Vyoo Agency, Lyon, France.
Aims:
The Evoque™ transcatheter tricuspid valve replacement (TTVR) system demonstrated superiority over optimal medical treatment (OMT) in the TRISCEND II trial. We aimed to evaluate the cost-effectiveness of TTVR in patients with severe Tricuspid Regurgitation (TR) from the French healthcare perspective.
Methods And Results:
A state-transition Markov model was developed to assess the cost-effectiveness of Evoque™ TTVR versus OMT alone over a lifetime horizon. The modeled cohort reflected the TRISCEND II population. Health states were defined by TR severity (none/trace, mild, moderate, severe) and death. Transition probabilities, adverse events, and hospitalisation rates were informed by TRISCEND II. Long-term survival outcomes were extrapolated by TR severity using published data. Utilities were estimated from NYHA class distribution. Costs and health outcomes were discounted at 2.5% annually.Evoque™ was associated with an incremental 1.76 life-years gained (LYG) and 1.63 quality-adjusted LYG (QALY). Incremental costs were €39,382 driven by device acquisition and procedure costs, resulting in an incremental cost-effectiveness ratio (ICERs) of €22,327/LYG and €24,109/QALY gained. Assuming no mortality difference in extrapolations, the ICER would increase to €86,428/QALY (+258%). The model was highly sensitive to assumptions on time horizon, utility, discount rate and post-trial mortality extrapolation, leading to major uncertainty.
Conclusion:
Evoque™ may represent a cost-effective strategy in severe TR patients, however this should be interpreted with caution, as results rely heavily on extrapolated data and are subject to high structural and parameter uncertainty. The projected long-term benefits are largely model driven rather than empirically demonstrated, emphasising the need for extended follow-up data.
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