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

Area of Science:

• Cardiology
• Biomarkers
• Health Economics

Background:

• Atrial fibrillation (AF) increases thromboembolism risk, with current clinical scoring systems having limited prognostic accuracy.
• Circulating biomarkers offer potential for improved risk prediction and personalized treatment in AF patients.
• There is a need for enhanced risk stratification tools in AF management.

Purpose of the Study:

• To evaluate the cost-effectiveness of precision medicine (PM) versus standard of care (SOC) for stroke risk stratification in AF patients.
• To compare the economic and clinical outcomes of PM and SOC over a 20-year period.
• To determine if PM represents a dominant strategy for managing AF-related stroke risk.

Main Methods:

• A Markov cohort model was utilized to simulate outcomes from a Canadian healthcare system perspective.
• The model compared costs and quality-adjusted life-years (QALYs) for PM and SOC over two decades.
• Sensitivity analyses, including one-way and probabilistic, were performed to assess result robustness.

Main Results:

• Precision medicine (PM) reduced mean per-patient costs by 7% (CAD $94,932 vs $102,057).
• PM increased mean QALYs by 12% (8.77 vs 7.68 QALYs).
• The incremental cost-effectiveness ratio was negative, signifying PM as an economically dominant strategy.

Conclusions:

• Precision medicine (PM) is an economically dominant strategy for AF stroke risk stratification.
• Implementing PM is projected to generate significant cost savings within the healthcare system.
• Combined biomarker and clinical variable assessment offers a superior approach to standard care for AF patients.