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(MRC DTP) Developing cancer risk prediction models for disease prevention and screening utilising the UKBiobank cohort.

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  • Full or part time
    Prof K Muir
    Dr A Lophatananon
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

The future NHS plans to incorporate a much greater emphasis on screening and prevention as the increasing costs of treating the chronic disease burden of an ageing population is predicted to place even greater strain on health budgets. Risk prediction models are rapidly gaining popularity as a way of identifying an individual’s risk before diseases develop (screening), or before the disease takes on its more serious forms (early detection). Such strategies open up the possibilities for prevention or earlier and more effective intervention. Utilising risk prediction models has been identified by the American Association of Cancer Research as an area of “extraordinary opportunity”.

Prevention and/or early detection are particularly important in cancer as 40% of cancers can be prevented. Risk prediction models can be used to assess individual risk and to inform people on their risk and then to support them to reduce their risk. So far, most risk prediction models for such diseases often include clinical indices with only very limited basic epidemiological factors such as family history, age, diet and other lifestyle factors. Nearly all cancer risk prediction models are built around a single cancer type and do not integrate risk across multiple cancers or focus on modifiable risks. Integrating risk across multiple cancers is important as it is known to increase motivation to change lifestyle based on the larger resulting risk reduction benefit. Furthermore, adding in genetic risk (as assessed by panels of genetic markers (SNP’s) allow for increased precision of such models. The UK Biobank is a unique national cohort study that has recruited 500,000 individuals and is following their disease development over their lifetime. All participants have also had their full genotype determined from a collected blood samples.

This Ph.D. proposal therefore aims to build a series of risk calculators for a series of common cancers by utilising data on lifestyle/environmental factors and genetic markers available in the UK Biobank cohort. Such models will involve at an early stage involvement of potential end users to ensure their usability and applicability.
Applications to UKBiobank have been approved for all cancers. We plan to develop the models using the UK Biobank data and validate the models using non-UK Biobank data of which we have access to.

This Ph.D. project will provide a great opportunity for a student with interest in cancer epidemiology and statistics and provide an excellent training platform.

Entry Requirements
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.

Funding Notes

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

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.


Gail, M. H. & Pfeiffer, R. M. (2018) Breast Cancer Risk Model Requirements for Counselling, Prevention, and Screening. JNCI: Journal of the National Cancer Institute, 110(9), 994-1002.

Usher-Smith, J. A., Silarova, B., Lophatananon, A., Duschinsky, R., Campbell, J., Warcaba, J. & Muir, K. (2017) Responses to provision of personalised cancer risk information: a qualitative interview study with members of the public. BMC Public Health, 17(1), 977.

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