About the Project
Start date and duration:
September 2019 for three years.
This project will be suitable for statisticians who are interested in applying their technical skills to improve the efficiency of clinical trials and their benefit to patients.
In recent years, the failure rate of phase III oncology trials has led to the increased exploration of alternative designs for early phase oncology trials, which aim to better prioritise treatments for future study. Our group has worked on several problems relating to phase II oncology trials (e.g., [1-3]). This project will focus on further developing methods for such trials. It will include:
1.Extending methods for transition designs that efficiently switch between non-randomised and randomised comparisons.
2.Developing methods for small-sample group-sequential trials that can be applied when the different stages use different endpoints (e.g., binary and time-to-event).
3.Proposing new methods for adaptively enriching clinical trials to biomarker specified sub-groups of patients for whom a treatment appears to work best.
The student would be based within a supportive and dynamic environment where methodological development, the creation of user-friendly software, and statistical leadership of real clinical trials is valued. Required training on relevant statistical methods, statistical programming, and clinical trials will be provided.
1.Wason JM, Mander AP (2015) The choice of test in phase II cancer trials assessing continuous tumour shrinkage when complete responses are expected. Stat Meth Med Res 24:909-19.
2.Grayling MJ, Mander AP (2016) Do single-arm trials have a role in drug development plans incorporating randomised trials? Pharm Stat 15:143-151.
3.Grayling MJ, Wason JMS, Mander AP (2017) A two-stage Fisher exact test for multi-arm studies with binary outcome variables. arXiv:1711.10199.
Newcastle University (https://bit.ly/2DQiHRV), Faculty of Medical Sciences (https://bit.ly/2UtoDFO)
Name of supervisor(s):
Dr Michael Grayling, Institute of Health and Society (https://bit.ly/2G32IST)
(by the time of starting the PhD) a master’s degree in statistics or a subject with a substantial theoretical statistics component/equivalent research training/experience.
If English is not your first language, you must have an overall IELTS of more than 6.5 with no component less than 5.5, or equivalent.
The award is available to UK/EU applicants. Non-EU international applicants who are interested should contact the supervisor.
How to apply:
You must apply through the University’s online postgraduate application system. To do this please ‘Create a new account’ (https://bit.ly/2BdwfoY).
Only mandatory fields need to be completed. However, you will need to include the following information:
•insert the programme code 8300F in the programme of study section
•insert the studentship code HS035 in the studentship/partnership reference field
•attach a covering letter and CV no more than two pages for each. The covering letter must state the title of the studentship, quote the studentship reference code HS035 and state how your interests and experience relate to the project
•attach degree transcripts and certificates and, if English is not your first language, a copy of your English language qualifications.
Based on your current searches we recommend the following search filters.
Based on your current search criteria we thought you might be interested in these.