OBJECTIVES

Based on Framingham Risk Score (FRS) people can be classified in 3 Cardiovascular (CV) risk categories: 1) low risk (FRS <10%), 2) intermediate CV risk (FRS 10%-19%), and 3) high CV risk (FRS>20%). An individual patient-data meta-analysis conducted on 24,955 men and 23,339 women showed that Ankle-Arm Index (ABI) in combination with FRS classifies female subjects with higher accuracy with no difference for male. The objective of this analysis is assessing the cost-effectiveness of ABI combine with FSR in primary prevention.

METHODS

A decisional analytical model was developed to simulate CV risk of asymptomatic female subjects, stratified in 3 CV risk categories. The model compares the primary prevention intervention (treatment of subjects at intermediate and high risk) based on the classification with FRS alone or in association with ABI<0.9 (FRS-ABI). The cost-effectiveness model used 10 years time-horizon and the point of view of the Italian National Health System. Results were presented as incremental cost-effectiveness ratios (ICERs) per QALY gained. Cost and outcomes were discounted at 3%.

RESULTS

FRS-ABI determined a reclassification to higher risks in 7% of the female population, with an increase in costs per patient (€3,373 vs €3,198) but also greater efficacy (8,683 vs 8,689 QALYs) over a 10 years time horizon, with an ICER of €47.065 per QALY gained. While using an ABI<1.10 cut-off we obtained an ICER of €28.688 per QALY gained over 10 years simulation. In the probabilistic sensitivity analysis, the FRS-ABI reported a 50% probability to be cost-effective with ABI<0.9 cut-off and 80% probability with ABI<1.1 at a willingness to pay threshold of €50,000 per QALY.

CONCLUSIONS

Our study showed that FRS and ABI combination is a potentially cost-effective CV risk classification approach in female population. Our results can help the healthcare decision makers in implementing better strategies for primary CV diseases prevention in Italy.