CQUniversity
Browse

File(s) not publicly available

Cost-effectiveness analysis of genetic screening for the Taq1B polymorphism in the secondary prevention of coronary heart disease

journal contribution
posted on 2018-08-06, 00:00 authored by LK Kemp, Christopher DoranChristopher Doran, T Vos, W Hall
Coronary heart disease is a major health priority area in Australia. Cholesterol-lowering agents are generally considered to be cost effective for the secondary prevention of coronary heart disease. There Is growing evidence, however, that the effectiveness of statins varies from one individual to another. The Taq 1B polymorphism is an example of a genetic polymorphism that is thought to influence the effectiveness of stafins. The aim of the current analysis is to estimate the cost-effectiveness of genetically screening coronary heart disease and stroke patients for the Taq lB polymorphism, and prescribing statin treatment to those with the B1B2 or B2B2 forms of the gene. A health sector perspective was adopted with a maximum acceptable cost-effectiveness ratio set at AUS$50,000/disability-adjusted life year. There is an 89% probability that screening and prescribing statins to those with the B1B2 and B2B2 alieles is more cost effective than prescribing statins to all patients. Modeling the cost-effectiveness of pharmacogenetics in major areas of medicine provides useful information to help in resource allocation and decision making. Economic evaluations similar to this one Will be required In the future as he results of further clinical trials to establish the effectiveness of statins based on genotype become available. © 2007 Future Drugs Ltd.

History

Volume

7

Issue

2

Start Page

119

End Page

128

Number of Pages

10

eISSN

1744-8379

ISSN

1473-7167

Publisher

Taylor & Francis

Peer Reviewed

  • Yes

Open Access

  • No

Era Eligible

  • Yes

Journal

Expert Review of Pharmacoeconomics and Outcomes Research

Usage metrics

    CQUniversity

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC