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Background

Cardiovascular disease (CVD) is the leading cause of premature death and a major cause of disability worldwide. In many Western countries national policies now support targeting of interventions to reduce risk of cardiovascular disease among high risk individuals. Validated risk prediction scores are used in such programmes in order to identify participants for intervention when they are at high risk (defined by a 10-year cardiovascular disease threshold of 20% or more). In China, disease patterns may differ importantly from Western countries, and currently there are no such tools that have been developed in a single Chinese cohort. We aim to use data from the China Kadoorie Biobank (CKB) to develop both a short-term and long-term CVD risk prediction score. 

The CKB is a prospective cohort study of 0.5M adults recruited during 2004-2008 from 10 diverse regions of China, with extensive data collection of lifestyle information (e.g., smoking, physical activity), and physical measurements (e.g. BMI, blood pressure). Currently the CKB has ~ 50K CVD events recorded as well as large-scale genotyping, biochemical and metabolic data on 100K, 18k and 5K of participants respectively.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

This project aims to provide a robust cardiovascular risk prediction tool that can be used in both urban and rural Chinese populations:

The general aims of this DPhil project will be to:

  1. Review the literature on short-term risk prediction tools for CVD risk.
  2. Develop a risk prediction tool of CVD risk, and assess the calibration, discrimination, internal and external validity of this using standard metrics.
  3. Develop estimates of lifetime risk of CVD taking into account competing risks (such as death from cancer).
  4. Develop novel approaches to communicate risk to a non-technical audience.

This project will involve working within a multi-disciplinary team and the candidate will gain research experience in systematic reviews, study design and planning, epidemiological and statistical methods. 

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING 

By the end of their DPhil studies it is expected that the student will be able to plan, undertake, interpret, and report their findings in a clear and concise manner. The student will have acquired transferable skills such as the writing of project proposals and presenting the research findings at local, national, and international meetings. The student will be expected to publish at least two peer-reviewed papers as the lead author by the end of their DPhil.

Prospective candidate

The student should have a good degree in a quantitative subject and an MSc in Epidemiology or Medical Statistics. The student should also have a strong interest in cardiovascular disease epidemiology.

Supervisors