Oral anticoagulation therapy, largely performed by warfarin-based drugs, is commonly used for patients with a high risk of blood clotting which can lead to stroke or thrombosis. The state of the patient, with respect to anticoagulation, is captured by the index INR, which is to be kept within a therapeutic range. The patient’s response is marked by high inter-individual and inter-temporal variability, which can lead to serious adverse events. The Food and Drug Administration (FDA)’s Adverse Event Reporting System indicated that warfarin is among the 10 top drugsfor the adverse events reported during the 1990 and 2000 decades . In the last years genetic testing has been argued as a base for personalize dosing: indeed polymorphisms of two genes CYP2C9 and VKORC1 are markers of lower dosing requirements, but still account for a relatively minor part of this variability. For these reason there is no widely agreed conclusion as to whether the net economic results, keeping the cost of testing into account of the therapeutic improvement allowed by genetic testing are positive. In this paper the authors develop a model based on a decision tree to assess the cost-effectiveness of genotype based warfarin dosing. Clinical/therapeutical data inputs for the model have been derived from a database of nearly 4000 patients of which around 350 have been so far genotyped. Several scenarios have been simulated about the prevalence of major bleeding and ischemic events among anticoagulated patients and the rate of their reduction attributable, according to the literature, to genotyped dosing.

A model for cost effectiveness analysis of using genetic information of oral anticoagulation patients / F. Archetti, I. Giordani, E. Messina, D. Maccagnola, G. Ogliari, D. Mari - In: WHCM 2010 Health Care Management[s.l] : Institute of Electrical and Electronics Engineers ( IEEE ), 2010. - ISBN 9781424449972. - pp. 1-6 (( convegno Workshop on Health Care Management (WHCM) : 18th - 20th February tenutosi a Venezia nel 2010 [10.1109/WHCM.2010.5441249].

A model for cost effectiveness analysis of using genetic information of oral anticoagulation patients

G. Ogliari
Penultimo
;
D. Mari
Ultimo
2010

Abstract

Oral anticoagulation therapy, largely performed by warfarin-based drugs, is commonly used for patients with a high risk of blood clotting which can lead to stroke or thrombosis. The state of the patient, with respect to anticoagulation, is captured by the index INR, which is to be kept within a therapeutic range. The patient’s response is marked by high inter-individual and inter-temporal variability, which can lead to serious adverse events. The Food and Drug Administration (FDA)’s Adverse Event Reporting System indicated that warfarin is among the 10 top drugsfor the adverse events reported during the 1990 and 2000 decades . In the last years genetic testing has been argued as a base for personalize dosing: indeed polymorphisms of two genes CYP2C9 and VKORC1 are markers of lower dosing requirements, but still account for a relatively minor part of this variability. For these reason there is no widely agreed conclusion as to whether the net economic results, keeping the cost of testing into account of the therapeutic improvement allowed by genetic testing are positive. In this paper the authors develop a model based on a decision tree to assess the cost-effectiveness of genotype based warfarin dosing. Clinical/therapeutical data inputs for the model have been derived from a database of nearly 4000 patients of which around 350 have been so far genotyped. Several scenarios have been simulated about the prevalence of major bleeding and ischemic events among anticoagulated patients and the rate of their reduction attributable, according to the literature, to genotyped dosing.
oral anticoagulation therapy ; patient profiling ; cost-effectiveness
Settore MED/09 - Medicina Interna
2010
Institute of Electrical and Electronics Engineers (IEEE)
Book Part (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/157657
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