A Cost-Effectiveness Analysis of Biomarkers for Risk Prediction in Atrial Fibrillation

Rationale Atrial fibrillation (AF) is associated with an increased risk of thromboembolism. This risk is currently assessed with scoring systems based on clinical characteristics. However, these tools have limited prognostic performance. Circulating biomarkers are proposed for improved prediction of major clinical events and individualization of treatments in patients with AF. Objective The aim was to assess the cost-effectiveness of precision medicine (PM), i.e., the use of combined biomarkers and clinical variables, in comparison to standard of care (SOC) for risk stratification in a hypothetical cohort of AF patients at risk of stroke. Methods A Markov cohort model was developed to evaluate the costs and quality-adjusted life-years (QALYs) of PM compared to SOC, over 20 years using a Canadian healthcare system perspective. Results PM decreased the mean per-patient overall costs by 7% ($94,932 vs $102,057 [Canadian dollars], respectively) and increased the QALYs by 12% (8.77 vs 7.68 QALYs, respectively). The calculated incremental cost-effectiveness ratio was negative, indicating that PM is an economically dominant strategy. These results were robust to one-way and probabilistic sensitivity analyses. Conclusion PM compared to SOC is economically dominant and is projected to generate cost savings.