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Psychosocial and Behavioral Impact of Breast Cancer Risk Assessed by Testing for Common Risk Variants: Protocol of a Prospective Study

Overview
Journal BMC Cancer
Publisher Biomed Central
Specialty Oncology
Date 2017 Jul 20
PMID 28720130
Citations 4
Authors
Affiliations
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Abstract

Background: The 'common variant, common disease' model predicts that a significant component of hereditary breast cancer unexplained by pathogenic variants in moderate or high-penetrance genes is due to the cumulative effect of common risk variants in DNA (polygenic risk). Assessing a woman's breast cancer risk by testing for common risk variants can provide useful information for women who would otherwise receive uninformative results by traditional monogenic testing. Despite increasing support for the utility of common risk variants in hereditary breast cancer, research findings have not yet been integrated into clinical practice. Translational research is therefore critical to ensure results are effectively communicated, and that women do not experience undue adverse psychological outcomes.

Methods: In this prospective study, 400 women with a personal and/or high risk family history of breast cancer will be recruited from six familial cancer centers (FCCs) in Australia. Eligible women will be invited to attend a FCC and receive their personal polygenic risk result for breast cancer. Genetic health professionals participating in the study will receive training on the return of polygenic risk information and a training manual and visual aids will be developed to facilitate patient communication. Participants will complete up to three self-administered questionnaires over a 12-months period to assess the short-and long-term psychological and behavioral outcomes of receiving or not receiving their personal polygenic risk result.

Discussion: This is the world's first study to assess the psychological and behavioral impact of offering polygenic risk information to women from families at high risk of breast cancer. Findings from this research will provide the basis for the development of a new service model to provide polygenic risk information in familial cancer clinics.

Trial Registration: The study was retrospectively registered on 27th April 2017 with the Australian and New Zealand Clinical Trials Group (Registration no: ACTRN12617000594325; clinical trial URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372743 ).

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References
1.
Muranen T, Mavaddat N, Khan S, Fagerholm R, Pelttari L, Lee A . Polygenic risk score is associated with increased disease risk in 52 Finnish breast cancer families. Breast Cancer Res Treat. 2016; 158(3):463-9. PMC: 4963452. DOI: 10.1007/s10549-016-3897-6. View

2.
Dite G, MacInnis R, Bickerstaffe A, Dowty J, Allman R, Apicella C . Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry. Cancer Epidemiol Biomarkers Prev. 2015; 25(2):359-65. PMC: 4767544. DOI: 10.1158/1055-9965.EPI-15-0838. View

3.
Schwartz M, Peshkin B, Hughes C, Main D, Isaacs C, Lerman C . Impact of BRCA1/BRCA2 mutation testing on psychologic distress in a clinic-based sample. J Clin Oncol. 2002; 20(2):514-20. DOI: 10.1200/JCO.2002.20.2.514. View

4.
Mavaddat N, Pharoah P, Michailidou K, Tyrer J, Brook M, Bolla M . Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst. 2015; 107(5). PMC: 4754625. DOI: 10.1093/jnci/djv036. View

5.
Li H, Feng B, Miron A, Chen X, Beesley J, Bimeh E . Breast cancer risk prediction using a polygenic risk score in the familial setting: a prospective study from the Breast Cancer Family Registry and kConFab. Genet Med. 2016; 19(1):30-35. PMC: 5107177. DOI: 10.1038/gim.2016.43. View