Dear all,

Due to unforeseen reasons we now have a PhD studentship available at MRC Biostatistics starting in January 2013

Project details are below. For details of the application process please see http://www.mrc-bsu.cam.ac.uk/Education/PhD.html

Best wishes

> Statistical issues in the design and analysis of multi-arm multi-stage (MAMS) clinical trials
> Supervisors: Jack Bowden and James Wason
>
> The drug development process is extremely long and costly. Techniques that allow improvement in efficiency are of keen interest to pharmaceutical companies and public research institutions. When multiple treatments are available for testing that treat the same condition, the traditional approach is to test them one-by-one in a series of trials, each one with a separate control group. A multi-arm trial simultaneously tests a set of new treatments against a shared control group, thus requiring fewer patients. In addition, interim analyses can be included that allow early stopping of treatments if they are not effective, or early stopping of the trial if an effective treatment is found. A trial with multiple arms and interim analyses is called a multi-arm multi-stage (MAMS) trial; they are a recent innovation but many statistical issues remain, both in their design and analysis.
>
> Firstly, accurate estimation of a treatment's effect is vital for expressing its true worth. The standard maximum likelihood estimate ignores the sequential nature of a multi-stage trial, and can exhibit severe bias. Several alternative classes of estimation procedures have been proposed to address this issue. However, their application to MAMS designs is not immediate; most of the methods to date have only focused on two-stage designs and none consider multiple treatments at the end of the study.
>
> Secondly, it is often necessary to collect information on multiple outcomes (or 'endpoints') in a clinical trial. For example, in certain disease areas such as cancer, toxicity is common and it is desirable to ensure that a new treatment is both more effective and not significantly more toxic than an existing treatment. In other areas, such as mental health, there may be several possible available endpoints, and no obvious choice for a primary endpoint. Limited literature exists for multiple endpoints for traditional group-sequential studies, but not when there are multiple treatment arms too.
>
> This project will therefore focus on the development of statistical methodology in these two key areas. Firstly, for bias adjusted estimation of treatment effects in MAMS trials and secondly, for the analysis of MAMS trials with multiple endpoints.
> The project will be jointly supervised by Jack Bowden and James Wason. We are looking for a student with a keen interest in developing statistical methodology useful for and in the context of real-life applications. This project will involve collaborating with clinical experts and clinical trialists with the results being of interest to clinical trials units currently designing and conducting MAMS trials (for example in London and Leeds).

--
Dr Angela Talbot

PhD Programme Manager
MRC Biostatistics Unit
Institute of Public Health
University Forvie Site
Robinson Way
Cambridge CB2 0SR

Tel:- +44 1223 330376
email:- [log in to unmask]

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