An ARC EM PhD opportunity is available and applicants can select from a range of projects listed below. Starting in September 2020, the PhD will be based within the University of Leicester Biostatistics and Health Sciences.
The studentship will undertake a PhD project aligned to the aims of the ARC EM's Data2Health theme, which will focus on methodological translation – ensuring that appropriate, innovative and fully evaluated methods are used to inform the design and analysis of ARC EM research studies. It will also ensure maximal use of existing large-scale linked data resources to address important questions for patients, the public and care services, both locally and nationally.
NOTE: There is only one studentship available.
Application deadline: 26th May 2020
Start date: 28th September 2020
- Applicants should select one or more of the following projects when applying.
- Applicants are encouraged to contact the lead supervisor for more information on the projects.
(1) What is the most clinically and cost-effective way of preventing type 2 diabetes? A systematic review, component network meta-analysis and economic evaluation of metformin and lifestyle interventions
Supervisors: Dr Suzanne Freeman, Professor Nicola Cooper, Professor Alex Sutton & Professor Kamlesh Khunti
This project will involve a systematic review and component network meta-analysis of randomised controlled trials of metformin, lifestyle interventions, combination of lifestyle with metformin and other relevant treatments for the prevention of type 2 diabetes followed by an economic evaluation to determine the cost-effectiveness of metformin and lifestyle interventions. Novel methods of visualising and communicating results of component network meta-analysis and cost-effectiveness models may also be explored.
(2) Addressing methodological issues associated with using the Kidney Disease Quality of Life (KDQOL) tool in a trial of nocturnal dialysis to estimate effectiveness and cost effectiveness.
Supervisors: Professor Laura Gray, Professor Nicola Cooper, Prof James Burton
This project will firstly involve investigating how to deal with participants who have either died or had a kidney transplant when analysing data from the KDQOL. This will incorporate a systematic review followed by a simulation study assessing methods. Secondly the project will involve assessing methods for using data from the KDQOL in cost-effectiveness analyses, specifically developing algorithms for mapping the KDQOL onto the EQ-5D.
(3) Diabetes remission: Using real world data to assess prevalence and incidence and factors associated with remission, relapse and longer term outcomes.
Supervisors: Professor Laura Gray, Dr Clare Gillies, Professor Kamlesh Khunti
This project will involve using data from the Clinical Practice Research Datalink (CPRD) to undertake extensive analyses related to diabetes remission. This includes: Calculation of prevalence and incidence; Assessment of factors associated with remission, such as weight loss, ethnicity, age and comorbidities; Modeling the longer-term outcomes of people who have achieved remission with those who have not and assess the impact of comorbidities on this; and assessment of the prevalence and the factors associated with relapse.
(4) Improving Prediction of End Stage Renal Disease (ESRD) in Diabetic Kidney Disease (DKD).
Supervisors: Dr Rupert Major, Professor Laura Gray
This project will involve performing a systematic review and, if appropriate, a meta-analysis of risk factors for the development of ESRD in individuals with DKD where at least age, gender, eGFR and ACR have been adjusted for in the analysis and performing an external validation of the Kidney Failure Risk Equation in an East Midlands primary care DKD cohort. The project will then assess the impact of using dynamic risk prediction on the predictive ability of the Kidney Failure Risk Equation.
(5) Exploring the use of meta-analysis of existing trial data to inform the design of future trials: Application to the use of biologic agents for Alzheimer’s disease.
Supervisors: Professor Alex Sutton, Professor Nicola Cooper, Dr Terry Quinn
This project will involve exploring the existing methods for using the synthesis of previous trial evidence to inform sample size and other features of future trials in biologics for Alzheimer’s disease with the aim of minimising research wastage. It will then extend existing methods and, where necessary, develop new methods, as required, by the clinical area (for example to accommodate the use of different continuous outcomes etc). Finally creating a web-app to implement the methods and data used to allow others to explore the potential implications of alternative trial designs in Alzheimer’s disease using an intuitive interface (using the Shiny package for R).
Published on: 22 Apr 2020