The n-of-1 trial is a clinical trial conducted with an individual participant as the sole unit of observation. It can be used to assess of treatment effects in the individual by comparing the response to an intervention and a comparator, randomised in time. The n-of-1 design is particularly efficient and sensitive when considering outcomes which have large degrees of between-person variability, and relatively low within-person variability, such as changes in physical activity or pain, in a chronic degenerative condition, such as arthritis. Despite the definition requiring the study to be within a single individual, it is common to run a series of n-of-1 studies and analyse the data across a group of participants to draw conclusions about a wider population, much like a meta-analysis. That way, it is possible to learn what works for an individual, as well as seeing whether treatment response exists in the population overall. Additionally, by exploring heterogeneity in individual effects we may gain insight as to why and how patterns of treatment response vary within a population.su
The uptake of consumer technology offers an opportunity for a wider pool of patients to take part in n-of-1 studies, via real-time data entry plus the opportunity to receive feedback about one’s own results. This technology collects large amounts of data which has high temporal resolution within an individual, but relatively high between-person variability, and is therefore well suited to the n-of-1 design. To do this, studies must be designed so we can have confidence in the results, both at an individual and population-level.
When used to assess the efficacy of a particular treatment, it is also important that the trial can stop once a result is conclusive, saving the participants’ time and associated resource. Thus this project also intends to explore whether the inclusion of futility stopping rules within an n-of-1 design can allow those trials that show definitively unpromising results to be foreshortened, whilst still producing useful treatment estimates for those interventions that do show promise, and so making n-of-1 designs more resource efficient and yet still clinically useful.
Aims/Objectives:
The aim of this PhD will be to explore how population heterogeneity impacts the power of a series of n-of-1 trials to inform the design of n-of-1 studies. This will include developing methods to identify heterogeneity in such trials, investigating the impact of changing the number of particpants and cycles, and developing rules for stopping ineffective treatments.
https://www.research.manchester.ac.uk/portal/mark.lunt.html
https://www.research.manchester.ac.uk/portal/will.dixon.html
http://www.cfe.manchester.ac.uk/
Entry Requirements
Applicants must have obtained or be about to obtain a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science, engineering or technology.
How to Apply
To be considered for this project you MUST submit a formal online application form - full details on how to apply can be found on the MRC Doctoral Training Partnership (DTP) website www.manchester.ac.uk/mrcdtpstudentships
Applicants interested in this project should make direct contact with the Primary Supervisor to arrange to discuss the project further as soon as possible.
Equality, Diversity and Inclusion
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/
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