Objective: 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. Design and method: 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.
Objectives 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. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): ASST Niguarda Cà Granda Hospital, University of Milano-Bicocca, Milan, Italy
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.