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Dynamic risk prediction of cardiovascular disease using primary care data from New Zealand

  • Full or part time
    Dr J Barrett
    Dr A Wood
  • Application Deadline
    Thursday, January 03, 2019
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Cardiovascular disease is a leading cause of morbidity and mortality worldwide. National guidelines recommend reducing the risk of cardiovascular disease in high and medium-risk individuals through lifestyle advice and the prescription of lipid-lowering medication. But in order to target those at greatest risk of the disease we need to be able to accurately predict the probability an individual will experience a cardiovascular event. Methods for dynamic risk prediction of cardiovascular disease have recently been developed for data from UK primary care records1. These methods allow risk predictions to be updated dynamically in response to new information, e.g. new measurements of cardiovascular risk factors such as blood pressure or cholesterol levels. This project would involve adapting the landmarking method used for the UK data to primary care record data from New Zealand using data from the PREDICT cohort2. In landmarking we take each age an individual might be at risk and in two stages we first model past repeated measurements of cardiovascular risk factors and then model future risk of an event. The project would involve the use of longitudinal data analysis to model repeated measurements and survival analysis to model the future risk of cardiovascular disease. As well as the primary supervisor Dr Jessica Barrett from the MRC Biostatistics Unit, the successful candidate will collaborate with Dr Angela Wood from the Cardiovascular Epidemiology Unit and Dr Katrina Poppe from the University of Auckland.

Funding Notes

The MRC Biostatistics Unit offers at least 6 fulltime PhDs funded by the Medical Research Council or NIHR for commencement in April 2019 or October 2019.

Academic and Residence eligibility criteria apply.

More details are available at
(View Website )

In order to be formally considered all applicants must also complete a University of Cambridge application form- full details can be found here (View Website )

However informal enquiries are welcome to

Projects will remain open until the studentships are filled but priority will be given to applications received by the 3rd January 2019


References

1. Paige et al. Landmark models for optimizing the use of repeated measurements of risk factors in electronic health records to predict future disease risk. American Journal of Epidemiology 2018; 187(7): 1530-1538.
2. Wells et al. Cohort profile: The PREDICT cardiovascular disease cohort in New Zealand primary care. International Journal of Epidemiology 2017; 46(1): 22.

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