Advertisement

Familial Cancer

, Volume 18, Issue 2, pp 147–152 | Cite as

Development and pilot testing of a leaflet informing women with breast cancer about genomic testing for polygenic risk

  • Rajneesh KaurEmail author
  • Bettina Meiser
  • Tatiane Yanes
  • Mary-Anne Young
  • Kristine Barlow-Stewart
  • Tony Roscioli
  • Sian Smith
  • Paul A. James
Original Article
  • 183 Downloads

Abstract

The inclusion of polygenic risk scores in breast cancer risk prediction models provides a more personalised and accurate prediction of breast cancer risk for women with and without breast cancer, who would otherwise receive negative results from traditional testing of moderate- and high-risk genes. This study aimed to develop, and pilot test a leaflet with a sample of women participating in a large prospective cohort study. The leaflet aimed to provide information about polygenic risk to assist women to decide whether or not to learn results from genomic testing for common risk variants associated with breast cancer risk. A prototype of the leaflet was developed based on published literature and with the expertise from a multidisciplinary team. The acceptability of the leaflet was assessed by self-report questionnaire among 29 women participating in the prospective cohort study. More than 80% participants stated that the leaflet was clear, informative and easy to understand and increased their understanding of polygenic risk information. While low to moderate levels of distress/worry were reported around implications of the test results for the next generation, 71% felt reassured and agreed that the information provided in the leaflet had helped them cope. Pilot-test results indicate the leaflet is acceptable to the participants and the revised leaflet can be used as an information tool for women undergoing genomic testing. This educational leaflet will become a useful information source to meet the information needs of women undergoing genomic testing.

Keywords

Breast cancer Polygenic risk score Genomic testing Leaflet 

Notes

Acknowledgements

We would like to thank all the ViP participants, who agreed to take part in this study and for their ongoing participation in the study.

Funding

The Variants in Practice study was supported by a National Medical and Research Council (NHMRC) Grant (ID 1023698). Bettina Meiser was supported by an NHMRC Senior Research Fellowship Grant (ID 1078523) and Tatiane Yanes was supported by an NHMRC and National Breast Cancer Foundation postgraduate scholarship during the duration of the study.

Compliance with ethical standards

Conflict of interest

Bettina Meiser has a remunerated consultant role with the company Astrazeneca with respect to an unrelated project.

References

  1. 1.
    Collaborative Group on Hormonal Factors in Breast Cancer (2001) Familial breast cancer: collaborative reanalysis of individual data from 52 epidemiological studies including 58,209 women with breast cancer and 101,986 women without the disease. Lancet 358(9291):1389–1399CrossRefGoogle Scholar
  2. 2.
    Domchek S, Friebel T, Singer C (2010) Association of risk-reducing surgery in BRCA1 or BRCA2 mutation carriers with cancer risk and mortality. J Amer Med Assoc 304(9):967–975CrossRefGoogle Scholar
  3. 3.
    Visvanathan K et al (2009) American Society of Clinical Oncology clinical practice guideline update on the use of pharmacological interventions including tamoxifen, raloxifene, and aromatase inhibition for breast cancer risk reduction. J Clin Oncol 27(19):3235–3258CrossRefGoogle Scholar
  4. 4.
    Rebbeck T, Kauff N, Domchek S (2009) Meta-analysis of risk reduction estimates associated with risk-reducing salpingooophorectomy in BRCA1 or BRCA2 mutation carriers. J Natl Cancer Inst 101:80–87CrossRefGoogle Scholar
  5. 5.
    Thompson D, Easton D (2004) The genetic epidemiology of breast cancer genes. J Mammary Gland Biol Neoplasia 9(3):221–236CrossRefGoogle Scholar
  6. 6.
    Riley BD et al (2012) Essential elements of genetic cancer risk assessment, counseling, and testing: updated recommendations of the National Society of Genetic Counselors. J Genet Couns 21(2):151–161CrossRefGoogle Scholar
  7. 7.
    Sawyer S et al (2012) A role for common genomic variants in the assessment of familial breast cancer. J Clin Oncol 30(35):4330–4336CrossRefGoogle Scholar
  8. 8.
    Muranen TA et al (2016) Polygenic risk score is associated with increased disease risk in 52 Finnish breast cancer families. Breast Cancer Res Treat 158(3):463–469CrossRefGoogle Scholar
  9. 9.
    Michailidou K et al (2017) Association analysis identifies 65 new breast cancer risk loci. Nature 551(7678):92–94CrossRefGoogle Scholar
  10. 10.
    Michailidou K et al (2015) Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer. Nat Genet 47(4):373–380CrossRefGoogle Scholar
  11. 11.
    Michailidou K et al (2013) Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet 45(4):353–361, 361e1–361e2CrossRefGoogle Scholar
  12. 12.
    Mavaddat N et al (2015) Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst 107(5):1–15CrossRefGoogle Scholar
  13. 13.
    Kuchenbaecker KB et al (2017) Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA 317(23):2402–2416CrossRefGoogle Scholar
  14. 14.
    Li H et al (2017) 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 19(1):30–35CrossRefGoogle Scholar
  15. 15.
    Dite GS et al (2016) 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 Biomark Prev 25:359–365CrossRefGoogle Scholar
  16. 16.
    Yanes T et al (2017) Psychosocial and behavioral impact of breast cancer risk assessed by testing for common risk variants: protocol of a prospective study. BMC Cancer 17(1):491CrossRefGoogle Scholar
  17. 17.
    Clerehan R, Buchbinder R, Moodie J (2005) A linguistic framework for assessing the quality of written patient information: its use in assessing methotrexate information for rheumatoid arthritis. Health Educ Res 20(3):334–344CrossRefGoogle Scholar
  18. 18.
    Clerehan R, Hirsh D, Buchbinder R (2009) Medication information leaflets for patients: the further validation of an analytic linguistic framework. Commun Med 6(2):117–127Google Scholar
  19. 19.
    Flesch-Kincaid readability score. Readability Scores: Flesch-Kincaid readability score (2018) http://www.rfp-templates.com/Readability-Scores/Flesch-Kincaid
  20. 20.
    Wakefield CE et al (2008) A randomized trial of a breast/ovarian cancer genetic testing decision aid used as a communication aid during genetic counseling. Psychooncology 17(8):844–854CrossRefGoogle Scholar
  21. 21.
    Wakefield CE et al (2007) Development and pilot testing of two decision aids for individuals considering genetic testing for cancer risk. J Genet Couns 16(3):325–339CrossRefGoogle Scholar
  22. 22.
    Wakefield CE et al (2011) Development and pilot testing of an online screening decision aid for men with a family history of prostate cancer. Patient Educ Couns 83(1):64–72CrossRefGoogle Scholar
  23. 23.
    McPherson CJ, Higginson IJ, Hearn J (2001) Effective methods of giving information in cancer: a systematic literature review of randomized controlled trials. J Public Health Med 23(3):227–234CrossRefGoogle Scholar
  24. 24.
    Metcalfe A et al (2007) Psychosocial impact of the lack of information given at referral about familial risk for cancer. Psychooncology 16(5):458–465CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Psychosocial Research Group, Prince of Wales Clinical School, Faculty of MedicineUniversity of New South WalesSydneyAustralia
  2. 2.School of Psychiatry, Faculty of MedicineUniversity of New South WalesSydneyAustralia
  3. 3.Genome.OneGarvan Institute of Medical ResearchSydneyAustralia
  4. 4.Sydney Medical School NorthernUniversity of SydneySydneyAustralia
  5. 5.Department of Medical GeneticsSydney Children’s HospitalSydneyAustralia
  6. 6.Familial Cancer CentrePeter MacCallum Cancer CentreMelbourneAustralia
  7. 7.Sir Peter MacCallum Department of OncologyUniversity of MelbourneMelbourneAustralia

Personalised recommendations