Trial within cohort adaptive enrichment designs - leveraging cohort longitudinal trajectories for shorter and efficient trials

Traditional stand-alone clinical trials for prevention typically face challenges of: poor recruitment, poor assumptions about relevant parameters (i.e. the size of a treatment effect), poor generalisability of results, and long follow-up periods. Currently, there is an increase in recruiting trial populations from observational cohorts where the trail design has access to a breadth of information. Within the broad area of mater protocols [1], adaptive platform trials [2] with adaptive enrichment [3] typically utilise single time point biomarkers or subgroups. By modelling the cohort population we may identify individuals who are more likely to progress and recruit these individuals into a trial. This will address a key challenge within prevention trials that typically require long follow-up to accrue sufficient clinical events.

The project will develop novel trial within cohort designs, building on the design of the European Prevention of Alzheimer’s Dementia (EPAD) consortium. The project is focused on important clinical targets for prevention trials that typically involve long and costly recruitment. Novel trial with cohort designs have the potential to reduce participant burden. Firstly we will develop longitudinal models for disease progression using latent class models to account for multiple latent progression trajectories. The progression model will be used to explore trial enrichment to maximise efficiency and statistical power, while minimising expected follow-up. There are challenges linking progression models and optimising trial operating characteristics, and this will build on existing work using latent class linear mixed-models to optimise the efficiency of treatment effect estimates [4]. Finally, the project will explore adaptive designs to fully leverage the linked longitudinal progression model. Dr Tom will provide access to the EPAD Longitudinal Cohort Study (LCS) for recruitment into trials (designed to support platform trial designs [5]).

As a trial statistical methodology project there will be no fieldwork aspect. This project will build upon a completed study, so there is no opportunity for direct PPI in that regard. However, the University of Cambridge's Biomedical Campus is engaged in many active dementia focused research studies. Through Dr White's collaboration with the Department of Psychiatry, and the wider Clinical School, the applicant will have opportunities to observe and receive training around PPI. In addition there may be PPI training opportunities through the DTP network. Although focused on designing statistically efficient studies, the aim is to reduce patient burden; all study design should be in collaboration with patients and participants to ensure the research is acceptable, relevant, and informative.

Primary supervision by Dr White (Cambridge) will involve regular meetings, Dr Tom (Cambridge) will co-supervise and include the student within their broader statistical research group.

HOW TO APPLY

You are applying for a PhD studentship from the MRC TMRP DTP. A list of potential projects and the application form is available online at:

http://www.methodologyhubs.mrc.ac.uk/about/tmrp-doctoral-training-partnership/

Please complete the form fully. Incomplete forms will not be considered. CVs will not be accepted for this scheme.

Please apply giving details for your first choice project. You can provide details of up to two other TMRP DTP projects you may be interested in at section B of the application form.

Before making an application, applicants should contact the project supervisor to find out more about the project and to discuss their interests in the research before 09 January 2023.

The deadline for applications is 4pm (GMT) 16 January 2023. Late applications will not be considered.

Completed application forms must be returned to: [Email Address Removed]

Informal enquiries may be made to Dr White - [Email Address Removed]