Using patient-level data to model long-term trajectories of renal function decline
Renal function declines over time, and models are required to assess long-term effects of management strategies and treatments in different patients. Several models exist, including two developed by the supervisors, but all have limitations, especially in modelling kidney function trajectories.
research experience, research methods and training
We suggest using UK’s Clinical Practice Research Datalink (CPRD, longitudinal primary care dataset), linked with the hospital admissions and mortality data, and further relevant data, to:
(1) Assess the performance of published models for trajectories of creatinine/estimated glomerular filtration rate (eGFR) and albuminuria, including progression to particular disease stages.
(2) Develop de-novo models of eGFR trajectories and albuminuria using CPRD and investigate effect of patient characteristics (eg cardiovascular disease, diabetes).
Investigate interactions of eGFR and albuminuria models overtime and combine them into a long-term kidney disease model validated on CPRD.
fieldwork, industry placements and training
Training will be offered in working with complex datasets, advanced statistical or epidemiological methods and statistical software. Attendance of seminars/conferences and interactions with other researchers will be encouraged.
The project would suit an applicant with a quantitative background, programming experience and interest in health research.