Λέσχη Φίλων Στατιστικής - GrStats forum
PhD in Biostatistics at University of Leicester Forumgrstats

Join the forum, it's quick and easy

Λέσχη Φίλων Στατιστικής - GrStats forum
PhD in Biostatistics at University of Leicester Forumgrstats
Λέσχη Φίλων Στατιστικής - GrStats forum
Would you like to react to this message? Create an account in a few clicks or log in to continue.
Για προβλήματα εγγραφής και άλλες πληροφορίες επικοινωνήστε με : grstats.forum@gmail.com ή grstats@stat-athens.aueb.gr

Go down
grstats
grstats
Posts : 856
Join date : 2009-10-21
http://stat-athens.aueb.gr/~grstats/

PhD in Biostatistics at University of Leicester Empty PhD in Biostatistics at University of Leicester

Sat 9 Jan 2016 - 21:49


PhD in Biostatistics
Biostatistics Research Group
Department of Health Sciences
University of Leicester

Deadline: 10 January 2016

Start date: October 2016

PhD project within the MRC Integrated Midlands Partnership for Biomedical
Training (IMPACT)
Title: "Bayesian evidence synthesis for surrogate endpoints in precision
medicine".
Supervisors: Dr Sylwia Bujkiewicz, Prof John Thompson and Prof Keith Abrams
Informal enquiries are welcome and should be made to Dr Sylwia Bujkiewicz
(http://www2.le.ac.uk/departments/health-sciences/research/biostats/staff-pages/sb309)
on sb309@le.ac.uk

For more information about the project, eligibility and how to apply follow
the link (this biostatistics project within the precision medicine theme):
http://www.birmingham.ac.uk/research/activity/mrc-impact/index.aspx

Project summary:
Biomarkers and surrogate endpoints are important in development of new
therapies and for government agencies in making decisions about whether they
should be licensed (e.g. European Medicines Agency) or reimbursed (e.g.
National Institute for Health and Care Excellence (NICE) in the UK). In
precision medicine, biomarkers, such as genetic factors in oncology, help to
identify subgroups of the population in which new therapies are most likely
to be effective, or at least more effective. Surrogate endpoints are used in
clinical trials to measure the effect of new treatments early in the disease
pathway compared to measuring effectiveness on a final clinical outcome,
which can require a long follow-up time. In order to ensure that the
surrogate endpoints can predict the treatment effect measured on the final
endpoint they need to be validated based on a number of clinical trials using
meta-analysis methods. Bayesian multivariate meta-analysis methods, developed
by the supervisors, provide a flexible approach to modelling correlated
outcomes, including surrogate endpoints. The aim of this project is to extend
the models used in our papers (Statistics in Medicine 2013; 32:3926-3943,
2015; early view 3 Nov) to model complex association patterns between
surrogate and final outcomes, and which may depend on biomarker status. The
PhD student will develop and evaluate Bayesian hierarchical meta-analytic
methods to model the relationship between the correlated endpoints including
information on the biomarker. The project will also explore modelling
different sources of evidence (from both randomised and observational
studies) by the use of appropriate Bayesian techniques; hierarchical models
and informative prior distributions. All methods will be implemented using
freely available software for Bayesian hierarchical modelling, e.g. OpenBUGS
(or STAN).

Dr Sylwia Bujkiewicz
Lecturer in Biostatistics

Biostatistics Research Group
Department of Health Sciences
University of Leicester
2nd Floor Adrian Building
University Road
LEICESTER LE1 7RH
Tel +44 (0)116 229 7258
FAX +44 (0)116 229 7250
Email: sb309@le.ac.uk

Back to top
Permissions in this forum:
You cannot reply to topics in this forum