Prof D French
Prof Anthony Howell
Dr Lorna McWilliams
Prof G Evans
No more applications being accepted
Competition Funded PhD Project (European/UK Students Only)
Risk estimation models for common multifactorial diseases such as breast cancer are often used, e.g. in Family History Clinics to inform decisions about prevention options. Their use is increasing, e.g. 58,000 women who attended routine breast-screening were provided risk estimates in the PROCAS study (1).
A challenge for the use of these risk estimation models in clinical practice is that an individual’s risk estimate can change, for several reasons. First, new versions of risk estimation algorithms, e.g., Tyrer-Cuzick model are updated. Second, these models can include more information sources: historically, they were based on self-reported family history and hormone-related factors, e.g. parity. They can now include information about breast density and Single Nucleotide Polymorphisms (SNPs) (2). Thirdly, estimates of lifetime breast cancer risk decrease with age, as each individual is older at later timepoints.
The extent of change can be large. In the Family History Risk (FH-Risk) study, 914 Manchester-based women received risk estimates between 1993-2010. They were told their risk was “high”, “moderate”, “average” or “below average”; women at high or moderate risk were offered prevention options, i.e. enhanced screening or chemoprevention (3). A sub-sample of 106 women had their risks re-evaluated using the latest version of the Tyrer-Cuzick model, including mammographic density and 18 SNPs. Of these 106 women, the lifetime risk of 53 women decreased by one or more risk categories (e.g. from high to moderate). Forty women did not change category whilst the risk of 13 women increased.
There is a dearth of research exploring the impact of receiving revised risk estimates for any disease: a scoping search failed to identify any such studies. Whilst there appears to be little emotional impact of receiving breast cancer risk estimates (4), many people do not trust the estimates they received (5). Receiving revised risk estimates may further undermine trust in healthcare professionals or credibility of risk estimation, as changes may produce revised management plans.
This PhD will: (a) identify the key issues for women who receive revised risk estimates; (b) develop materials to support consultations involving revised risk estimates, and (c) assess emotional impact, understanding of risk information, trust in healthcare professionals, and views of prevention options of women in the Family History Risk study. This research will produce an evidence base to help healthcare professionals communicate better with women about changes in estimated breast cancer risk, and more widely, changing risk of other diseases, e.g. Cardiovascular Disease.
Information on the NIHR BRC Cancer Prevention and Early Detection theme is provided here:
Personal pages of the supervisory team at the University of Manchester are provided here:
Applications are invited from UK/EU nationals only. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.
This project is to be funded under the MRC Doctoral Training Partnership. If you are interested in this project, please make direct contact with the Principal Supervisor to arrange to discuss the project further as soon as possible. You MUST also submit an online application form - full details on how to apply can be found on the MRC DTP website www.manchester.ac.uk/mrcdtpstudentships
As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
(1) Evans DG et al, Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study. NIHR Programme Grants for Applied Research, 2016: 4(11).
(2) Evans DGR et al, Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants. Breast Cancer Res Tr 2019; 176(1): 141-148.
(3) Evans DG et al, The impact of a panel of 18 SNPs on breast cancer risk in women attending a UK familial screening clinic: a case-control study. J Med Genet. 2017; 54(2):111-113.
(4) French DP et al. Psychological impact of providing women with personalised 10-year breast cancer risk estimates. Br J Cancer 2018; 118(12): 1648-1657.
(5) Bayne M et al. (in press) Effect of interventions including provision of personalised cancer risk information on accuracy of risk perception and psychological responses: a systematic review and meta-analysis. Pat Ed Couns. DOI: 10.1016/j.pec.2019/08/010