Cost-utility analysis of icosapent ethyl in patients with high triglyceride levels and recent acute coronary syndrome in Catalonia.

OBJECTIVE

To evaluate the cost-effectiveness of icosapent ethyl (IPE) as an adjunct to standard of care (SoC) for reducing cardiovascular (CV) events in statin-treated adults with elevated triglycerides (TG ≥ 150 mg/dL), established CV disease, and a recent acute coronary syndrome (ACS) in Catalonia, Spain.

METHODS

A de-novo partitioned survival model was developed to simulate the natural history of CV events over a 20-year horizon from the Catalan healthcare payer perspective. The model incorporated clinical efficacy and safety data from a post-hoc analysis of REDUCE-IT, a global CV outcomes trial with IPE, local treatment patterns, and Spanish-specific cost data. Outcomes were expressed in quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs). Deterministic, probabilistic, and scenario sensitivity analyses were conducted to assess model robustness.

RESULTS

In the base case, IPE plus SoC resulted in an incremental gain of 0.57 QALYs and €8,287 in additional costs compared to SoC alone, yielding an ICER of €14,543/QALY gained-well below the commonly accepted willingness-to-pay threshold of €30,000/QALY in Spain. Probabilistic sensitivity analysis showed that IPE was cost-effective in 75.3% of simulations and dominant in 15.4%. Scenario analyses confirmed the robustness of results across different time horizons and discount rates. Key drivers of cost-effectiveness were the selected efficacy curves for IPE and its per-cycle treatment cost.

CONCLUSIONS

IPE appears to be a cost-effective intervention for high-risk patients with elevated TG and recent ACS in Catalonia. While limitations related to model assumptions, data extrapolation, and partial adaptation to local clinical practice exist, the findings remain consistent with international evidence and suggest that IPE could be a cost-effective intervention in Catalonia, offering a valuable opportunity to optimize healthcare resource allocation in the management of high-risk CV populations.