3 PhD Studentships in Medical Statistics and/or Clinical Trials Methodology. Tuition fees and stipend starting from at least £16,553 per annum tax-free
Applications open until 13 July 2018.
Three full-time MRC-funded PhD studentships are available at the MRC Clinical Trials Unit at University College London (UCL) in the Institute of Clinical Trials and Methodology (ICTM), commencing between March 2018 and September 2018 (by agreement). The studentships cover UK/EU tuition fees and a tax-free maintenance stipend over three years. In 2017-2018 the stipend was £16,553, it may increase from September 2018.
The following projects are available:
- Statistical methods for adjusting for treatment changes in randomised trials
- Assessing and creating impact of methodological research to improve clinical study design, conduct and analysis
- One-stage models for meta-analysis
- Exploring the implications of analysing time-to-event outcomes as binary in meta-analysis
- Design and analysis of trials with multiple primary outcomes
- Methodology to maximise the potential of evaluating many therapies within a single protocol and developing Living Trial Protocols
- Another project in methodology for clinical trials to be negotiated with potential supervisors at the unit
- Improving assessment and monitoring of neurocognitive function in clinical studies involving HIV+ participants
These projects will all allow the student to develop skills in the analysis of data in medical research, and in the methodology of clinical trials. Brief details of each project are provided at the end of this advert and further details of each are available from Dr Andrew Copas, who is also very happy to discuss projects with potential applicants, and to answer any queries about studying at the Institute.
You will join the group of PhD students within the ICTM at UCL. You will register for full-time MPhil/PhD study at UCL, and will benefit from the range of training provided through UCL.
The essential and desirable criteria you will have are as follows:
- Have (or will have completed by September 2018) an MSc in a field relevant to the preferred research project, or equivalent experience together with a BSc in a quantitative discipline.
- Experience in statistical programming and use of statistical software such as Stata, to the level required by the preferred research project
- Good communication skills
- Interest in preferred research project, with some understanding of the issues it addresses
- Understanding of the principles of clinical trials, medical statistics, research methods, epidemiology and meta-analysis if relevant to the preferred project
- Clear articulation of the reasons to wish to undertake a PhD
- Ability to work independently and manage own time
- Work experience in statistics or medical research
- Publication record appropriate to work experience
Under research council regulations all candidates are also required to have been resident in the UK for the past three years, and thereby qualify for home fees status.
More details on eligibility can be found on the MRC website: http://www.mrc.ac.uk/skills-careers/studentships/studentship-guidance/student-eligibility-requirements/
How to apply
The application requires:
- your CV including contact details of two referees, and
- a letter explaining why you wish to study for a PhD in the ICTM at UCL and how you meet the essential and desirable criteria listed above.
Please email your CV and letter of interest to email@example.com.
In your letter you may express a preference for one of the above listed projects, and briefly explain your preference. If you wish alternatively to propose your own project then details of the project should be provided with your letter. Candidates intending to propose their own project are encouraged to contact Dr Andrew Copas in advance of applying to discuss the suitability of the project and potential supervisors.
Please note that successful applicants will also be required to apply for MPhil/PhD admission via the UCL online application system.
For shortlisted candidates there will be an opportunity to discuss the nature of each project at interview.
Brief descriptions of proposed projects
More detailed descriptions of each project and the supervisors involved are available from Dr Andrew Copas, and candidates are strongly encouraged to obtain these detailed descriptions before making their application. Dr Andrew Copas will also send details of any further projects developed since this advert was prepared.
Statistical methods for adjusting for treatment changes in randomised trials
Many clinical trials have substantial numbers of participants who change treatments during follow-up. Treatment changes can mask any benefit of treatment and in this case it is often important to adjust for the treatment changes in the statistical analysis. This is particularly an issue in late-stage cancer trials. This project will develop appropriate statistical methods, drawing on causal inference methods, with particular emphasis on disseminating methods for example by producing user-friendly software.
Assessing and creating impact of methodological research to improve clinical study design, conduct and analysis
This novel project aims to explore ways to measure and improve the impact of clinical and methodological research.
Clinical research aims to identify the best ways to diagnose, treat and prevent diseases or other conditions. Their results have great potential to change clinical policy, practice, and future research, improving outcomes for patients, and benefitting society as a whole. Methodological research aims to improve the design, conduct or analysis of clinical research, for example, by speeding up the completion of clinical studies or improving the reliability of their results.
However, the pathway from study results to impact on policy, practice and research is not necessarily straightforward and can take time. New developments can have little or no impact on studies, and the rate of change can be particularly slow. Knowing which strategies are best at increasing the impact of clinical and methodological studies, and demonstrating such impact to research funders and evaluators remains a big challenge.
The student will use clinical and methodological case studies to better understand the factors that might increase or impede impact, and ultimately provide a package strategies that will guide researchers on how best to effect change, demonstrate the value of what they do and justify public funding
One-stage models for meta-analysis
Modern medicine aims to be based on evidence, and the highest quality evidence comes from systematic review of randomised trials. At the heart of systematic review is meta-analysis, the statistical method for combination of evidence about treatment effects from multiple randomised trials. Meta-analysis is usually done in a two-stage process: first estimate treatment effects in all studies, then form a weighted average. However, two-stage meta-analysis is approximate and inaccurate in many settings, especially with binary outcome data. This project instead explores one-stage meta-analysis, where all the data are analysed in a single model. Various problems in frequentist one-stage meta-analysis have recently come to light. This project will explore these issues and ultimately aims to offer guidance on how these models should be fitted and to provide convenient software for doing so.
Exploring the implications of analysing time-to-event outcomes as binary in meta-analysis
A meta-analysis combines evidence from a set of similar studies, using data extracted for a suitable effect measure. When combining data from trials evaluating time-to-event outcomes such as overall survival, the most appropriate effect measure is the hazard ratio. However, time-to-event outcomes are commonly dichotomised and analysed as binary outcomes in meta-analysis, using effect measures such as the risk ratio or odds ratio. This project is focused on exploring the implications of analysing time-to-event outcomes as binary in meta-analysis. Investigations will include large-scale analysis of a collection of published meta-analyses extracted from Cochrane reviews, detailed exploration of case study meta-analyses held by the MRC CTU at UCL, and simulation studies. The aim of this project is to provide information and guidance to researchers carrying out meta-analyses of time-to-event outcomes.
Design and analysis of trials with multiple primary outcomes
Trials sometimes assess interventions that are expected to improve two or more aspects of health, where the impact may vary across these aspects. The project will draw on example trials including (i) a trial of a contraception choice intervention in the UK hoping to increase use of a highly effective contraceptive method, or satisfaction with current method, or both, and (ii) a trial of an intervention in Kenya hoped to improve (some or all of) antenatal clinic attendance, delivery at a health centre, postnatal clinic attendance and infant vaccination. Specifying just one primary outcome for such a trial is illogical and risks drawing the wrong conclusion - missing the important benefit of an intervention on other outcomes or declaring an intervention a success when it is beneficial for the primary outcome but harmful for others. Handling multiple primary outcomes however is challenging. This project aims to review and offer guidance on the best ways of analysing and interpreting trial data to decide whether an intervention can be recommended, and with this in mind also guide how to calculate the sample size for trials.
Methodology to maximise the potential of evaluating many therapies within a single protocol and developing Living Trial Protocols
When faced with the need to evaluate a new therapy, we can either design set up and run a new trial, or we can seek to graft the new comparison onto an existing trial, by making appropriate adaptions. The latter approach gives rise to trials with ‘living protocols’ which adapt over time. Within the unit, the STAMPEDE trial in prostate cancer has a ‘living protocol’: it started out with five arms, and additional arms have been added, both from results of the STAMPEDE trial and from other trials. The purpose of this PhD is to address the methodological issues arising from living protocol trials, starting with a framework for control of the type one error and appropriate primary analysis. The goal is to provide guidance on when living protocols are appropriate, and how they should be designed and analysed.
- Improving assessment and monitoring of neurocognitive function in clinical studies involving HIV+ participants
Anti-retroviral therapy has proved to effectively suppress viral replication and halt disease progression in patients living with HIV. However, effectively suppressed patients seem to be at higher risk for specific end-organ disease, including cognitive impairment, which have become important endpoints for HIV treatment clinical trials. Assessing and monitoring cognitive function, in both clinical practice and research studies, is mostly based on neuropsychological testing performance and different scales and criteria have been proposed to define impairment. Large and well powered randomised and observational studies have prospectively investigated cognition in effectively suppressed, treatment naïve and vertically infected individuals. This project aims to further improve understanding on how cognitive function is being measured in HIV treatment trials and cohorts and to provide evidence-based recommendations for the analysis and interpretation of neuropsychological longitudinal data.
Another project in statistical methodology for clinical trials to be negotiated with potential supervisors at the unit
We also welcome expressions of interest to study projects related to our priority research areas, including: