Apologies for cross-posting

See below for details of two statistics PhD studentships in the Centre for
Health Sciences, Barts & The London School of Medicine & Dentistry, Queen
Mary University of London, based in Whitechapel. Please forward to anyone
who you think might be interested.

Applicants should have at least an upper second class bachelor’s degree with
a high level of statistical content, or a master’s degree in statistics, and
should have a strong interest in medical statistics.

These studentships offer an exciting opportunity to be part of a growing
team of highly motivated statisticians within a UK National Institute of
Health (NIHR) registered and funded Clinical Trials Unit, the Pragmatic
Clinical Trials Unit (PCTU) (www.ihse.qmul.ac.uk/chs/pctu/index.html). The
PCTU carries out a wide range of clinical trials but also conducts
methodological work mostly in practical applications to support the design,
conduct and analysis of pragmatic clinical trials. The Centre in which the
PCTU is situated has over 15 years’ experience in conducting trials and was
rated fourth in the UK in health services research in the 2008 Research
Assessment Exercise. The successful applicants will join a group of eight
statisticians, and will have extensive training opportunities both in
research and statistical methods as appropriate. The Centre currently hosts
14 PhD students across of range of disciplines within community health
sciences.

Both studentships are funded full-time for three years by the Medical
Research Council, and come with a tax-free stipend of £15,590 per annum.
They are open to UK Nationals, EEA/Swiss migrant workers and non UK
nationals with indefinite leave to remain in the UK who all have three
years’ ordinary residence in the UK prior to the start of the studentship.
Projects are due to commence on 1 October 2011.

Note the two projects have different arrangements for applying - please read
the information given below for the project you are interested in.

PROJECT 1

Title: Choosing covariates in the analysis of cluster randomised trials

Co-supervisors: Dr S Bremner & Professor S Eldridge

This studentship focuses on cluster randomised trials, which are
increasingly popular in health services research. A gap in knowledge in
relation to such trials is determining which covariates to include in the
trial analysis. Appropriate procedures are better understood in individually
randomised trials, but in cluster randomised trials covariates can occur at
two levels, the cluster and the individual level, and there may be
complicated relationships between covariates at different levels. There has
been a small amount of work in this area but a comprehensive review is
needed particularly for non-continuous and non-normally distributed
outcomes.

This studentship offers the chance to explore existing literature in this
area both for individually and cluster randomised trials, to use data from
some of the many cluster randomised trials within the PCTU to understand
empirically the relationships between different covariates and outcomes, and
use simulation to explore these relationships further. The student will gain
knowledge and experience in these three areas, and develop highly relevant
guidelines for clinical trial investigators, a priority area for NIHR
research.

For an informal discussion about this project, please contact Dr Stephen
Bremner
Tel: 020 7882 2547  Email: [log in to unmask]

The closing date for applications is 14 February 2011. To apply, please
download the School of Medicine & Dentistry application form from our
website:   http://www.qmul.ac.uk/postgraduate/apply/index.html 
and return to the Graduate School Office - email: [log in to unmask]  
Please note that we accept postal and electronic applications.
Referees may email references directly to [log in to unmask]

PROJECT 2

Title: Statistical methods for analysing discordance trials of biomarkers or
other diagnostic tests

Co-supervisors: Professor Sandra Eldridge & Dr Richard Hooper

Diagnostic tests are usually studied in terms of their accuracy – how often
they correctly diagnose disease – but in practice the test result will be
used to make decisions about the management of patients, and a clinical
trial may therefore be the most appropriate way to compare two diagnostic
tests. There is a rapidly growing interest in the use of tests to guide
treatment choices rather than specifically to diagnose: biological tests of
this kind are called biomarkers, and are seen as a key element of an
approach to healthcare known as stratified medicine, in which a treatment is
matched to a patient in order to optimise its effect.  It has been suggested
that an efficient approach to trialling is to give both tests to all
participants, and to randomise and follow up those with discordant results.
We are interested in putting these ideas into a more formal framework.

The regulatory authorities who oversee new treatments require that any new
treatment tool – including a biomarker – must be validated using a large
Phase III clinical trial before it can be accepted as the standard of care.
Although there have so far been relatively few such trials comparing the use
of a biomarker with a non-stratified control, and almost none comparing two
biomarkers, this sort of application is likely to blossom as stratified
medicine takes off, and more and more biomarkers begin to be investigated
for their use in treatment decision-making. Our theoretical work has already
allowed us to put a figure on the huge efficiency saving of a discordance
trial design over a conventional trial for comparing two biomarkers or other
diagnostic tests. We found a four-fold reduction in the number of trial
participants required using figures from one published protocol as an
example (with a further reduction in the number whom it was necessary to
follow up). There are clear ethical and financial imperatives to adopting
such an efficient design in trials, but the details of the statistical
methods that should be used are still unclear, creating an obstacle to the
development of trials of this kind. Much more work is needed to show how to
extend the standard generalised linear modelling approach used for binary,
continuous and survival outcomes in conventional trials to the context of a
discordance trial. This would provide the focus of the PhD project.

For an informal discussion about this project, please contact Dr Richard
Hooper
Tel: 020 7882 7324  Email: [log in to unmask]

This is one of a number of studentships being advertised together by Barts &
The London School of Medicine & Dentistry, for which students will be
selected by competition. The closing date for applications is 20 February,
and interviews will be held on 14 March. To apply, go to
http://www.smd.qmul.ac.uk/graduatestudies/index.html, click on the button
marked "PhD studentships currently available", and follow the instructions.

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