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Sheffield Hallam University Featured PhD Programmes
FindA University Ltd Featured PhD Programmes

Statistical Issues in Design and Analysis of Platform Trials in Cancer


PhD Programmes

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Prof C Yap , Prof J Bliss , Prof J Wason No more applications being accepted Competition Funded PhD Project (Students Worldwide)

About the Project

This is project 1 of 2.

This ICR PhD studentship will join a national cohort of PhD students from over 20 institutions as part of the MRC-NIHR Trials Methodology Research Partnership (TMRP), which brings together a number of national and international networks, institutions and partners undertaking clinical trials and trials methodology research. The overall aim being to improve patient care by improving the way in which the healthcare evidence base is developed.

Please decide on either Project 1 or 2 when applying for this studentship, only one place will be available.
The second project can be seen here: https://www.findaphd.com/phds/project/development-of-innovative-adaptive-designs-to-improve-efficiency-in-early-phase-clinical-trials/?p109910

Project 1
Statistical Issues in Design and Analysis of Platform Trials in Cancer Here, the student will focus on improving design and analysis of adaptive platform trials in cancer. Traditionally, a trial will assess a new intervention treatment (often compared with the standard care) one at a time. However this is time-consuming and costly. Adaptive platform trials, on the other hand, allow for a more efficient strategy of evaluating several therapies for one (or more) diseases concurrently, and accept additions of new treatment arms or patient population during the trial [1]. Adaptive features could be implemented at the interim assessments, such as dropping of futile treatments, steering patients towards better performing treatments [2], or enriching a specific subgroup of patients who might benefit from the treatment better. Such designs indisputably can provide efficiency improvements, statistically or operationally or both. This work will be motivated by ongoing adaptive platform trials in cancer to assess several interesting methodological issues, such as the use of reliable short-term outcomes, decision criteria, sharing of control information, response-adaptive randomisation and pooling of information across arms using Bayesian techniques. There will be opportunities for the newly developed efficient methodologies to be applied to existing trials, as well as to influence the design and analysis of future such trials.

Download a PDF of the complete project proposal: https://d1ijoxngr27nfi.cloudfront.net/docs/default-source/studying-at-the-icr/yap_bliss_icr-studentship---website.pdf?sfvrsn=f1e55a69_2

Candidate profile
Either project would suit a candidate with strong statistical and computational skills. The candidate would be highly numerate with a keen interest in developing statistical methodology and implementing them in cancer clinical trials.
Candidate must already have been awarded a first-class or second upper class honours degree in Mathematics or Statistics. A Master’s degree or equivalent in medical statistics or a related quantitative discipline, or experience of working in clinical trials would be desirable.

How to apply
Full details about these studentship projects, and the online application form, are available on our website, at: www.icr.ac.uk/phds Applications for all projects should be made online. Please ensure that you read and follow the application instructions very carefully.
Closing date: 5pm UK time on Friday 28th June 2019
Interview date: 8th July 2019
Please apply via the ICR vacancies web portal : https://apply.icr.ac.uk/

Keywords: Biostatistics, Clinical Trials, Cancer, Trials Methodology, Adaptive Designs, Platform Trials

Funding Notes

Students receive an annual stipend, currently £21,000 per annum, as well as having tuition fees (both UK/EU and overseas) and project costs paid for the four-year duration. We are open to applications from any eligible candidates and are committed to attracting and developing the best minds in the world.


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