Once-Weekly Subcutaneous Semaglutide 2.4 mg Injection is Cost-Effective for Weight Management in Spain

A current major challenge for national health systems (NHS) is the increase of obesity and overweight among populations. Subcutaneous semaglutide 2.4 mg, a glucagon-like peptide 1 analogue, has been approved by the European Medicines Agency as an adjunct to a reduced-calorie diet and increased physical activity (diet and exercise [D&E]) for the treatment of obesity. The aim of this study was to evaluate the cost-effectiveness of semaglutide 2.4 mg in combination with D&E compared with D&E alone in the treatment of patients with obesity in Spain.

The analyses were performed using version 26 of the Core Obesity Model, a Markov state transition model, to project health outcomes and costs at 40 years, based on the evolution of risk factors associated with obesity. Efficacy and safety data were obtained from the STEP 1 trial (body mass index [BMI], systolic blood pressure and glycaemic status), involving a cohort of adults with an average age of 46 years and obesity (BMI ≥ 30 kg/m²). The analysis was carried out from the perspective of the Spanish NHS. The results were evaluated in terms of cost per quality-adjusted life year (QALY) gained. Only direct healthcare costs were included. Univariate and probabilistic sensitivity analyses were performed to ensure the robustness of the findings.

Compared with D&E, semaglutide 2.4 mg in combination with D&E generated an additional 0.1049 QALYs and a €2685 increase in costs over 40 years, resulting in an incremental cost-effectiveness ratio of €25,589/QALY. Semaglutide 2.4 mg was shown to be cost-effective under a cost-effectiveness threshold of €30,000/QALY. The robustness of this finding was confirmed by the sensitivity analyses and scenarios evaluated.

On the basis of the model-based analysis, semaglutide 2.4 mg, in combination with D&E, was estimated to be a cost-effective therapeutic alternative in Spain for adults with obesity, compared to treatment based on D&E alone. These results may be useful for optimizing decision-making.