Literature DB >> 24309564

Cost-effectiveness of a genetic test for breast cancer risk.

Henry J Folse1, Linda E Green, Andrea Kress, Richard Allman, Tuan A Dinh.   

Abstract

Genetic testing of seven single-nucleotide polymorphisms (7SNP) can improve estimates of risk of breast cancer relative to the Gail risk test alone, for the purpose of recommending MRI screening for women at high risk. A simulation of breast cancer and health care processes was used to conduct a virtual trial comparing the use of the 7SNP test with the Gail risk test to categorize patients by risk. Average-risk patients received annual mammogram, whereas high-risk patients received annual MRI. Cancer incidence was based on Surveillance, Epidemiology, and End Results data and validated to Cancer Prevention Study II Nutrition Cohort data. Risk factor values were drawn from National Health and Nutrition Examination Survey (NHANES-4) and Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial data. Mammogram characteristics were derived from Breast Cancer Surveillance Consortium data. The test was most cost-effective when given to patients at an intermediate lifetime risk of breast cancer. For patients with a risk of 16% to 28%, it resulted in a 1.91% reduction in cancer deaths, saving 0.005 quality-adjusted life years per person at a cost of $163,264 per QALY. These results were sensitive to the age at which the test is given, the discount rate, and the costs of the genetic test and MRI. The cost effectiveness of using the 7SNP test for patients with intermediate Gail risk is similar to that of other recommended strategies, including annual MRI for patients with a lifetime risk greater than 20% or BRCA1/2 mutations.

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Year:  2013        PMID: 24309564     DOI: 10.1158/1940-6207.CAPR-13-0056

Source DB:  PubMed          Journal:  Cancer Prev Res (Phila)        ISSN: 1940-6215


  2 in total

1.  Defining health-related quality of life in localized and advanced stages of breast cancer - the first step towards hereditary cancer genetic counseling.

Authors:  Tamara Žigman; Ivana Lukša; Gloria Mihaljević; Maša Žarković; Iva Kirac; Danko Velimir Vrdoljak; Ljiljana Šerman
Journal:  Acta Clin Croat       Date:  2020-06       Impact factor: 0.780

Review 2.  Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

Authors:  Matthias Arnold
Journal:  BMC Health Serv Res       Date:  2017-12-02       Impact factor: 2.655

  2 in total

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