In practice, many interventions may be used more than once. For instance, IVF treatment may be given again if the first cycle is unsuccessful; patients may become re-infected with certain diseases, requiring re-treatment; or patients may suffer an underlying condition such as sickle cell disease which causes repeated pain episodes, each require a new round of treatment to manage. These interventions are typically evaluated using a parallel group design, where only the first treatment administration is tested, however this approach may not be sufficient to fully inform the intervention’s use in practice, as the treatment may become less effective the more often it is used, or may work differently in those who require treatment more often.
Key questions around the evaluation of such interventions are: (a) which question about the treatment effect (estimand) is most relevant for evaluation and clinical decision making (e.g. the average effect across each administration of the intervention vs. the effect of the 1st vs. 2nd vs. 3rd administration, etc); (b) which trials designs support estimation of such estimands (e.g. a re-randomisation design where participants are re-randomised amongst available treatments, or a cluster design where participants are re-enrolled to the same intervention for each episode, etc); and (c) how such designs should be analysed in order to estimate relevant estimands.
This project will involve key topics such as estimands, novel trial designs, causal inference methods, and handling of terminating events (e.g. in an IVF trial where the intervention is successful, participants no longer require further treatment administration). The PhD aims to: define relevant estimands for such multi-use interventions; evaluate a number of novel trial designs (including re-randomisation, and cluster designs) using simulation and re-analysis of published datasets to identify which are most appropriate in this setting; and evaluate different methods of analysis (independence estimating equations, mixed-effects models, generalised estimating equations) using a combination of simulation and re-analysis of published datasets to determine which are best.
The MRC CTU at UCL is at the forefront of resolving internationally important questions in infectious diseases and cancer, and delivering swifter and more effective translation of scientific research into patient benefits. It does this by carrying out challenging and innovative studies, and developing and implementing methodological advances in study design, conduct and analysis. You will be joining a team of renowned experts in the field of clinical trials.
Ideally, the candidate would be numerate with a strength for developing statistical methodology and an enthusiasm for applying those methods into practice, e.g. a degree in mathematics, (medical) statistics, or a related quantitative field.
Who are the supervisors? The supervisory teams is Professor James Carpenter and Dr Brennan Kahan. You will also be supported by a Thesis Committee (TC), which will provide degree-spanning support and advice about academic and training progress for the successful candidate over the course of the Doctoral study.
When can I start? Successful candidates are expected to commence studies in October 2021
What funding is available? We have funding available for up to 3 full time studentships in line with the current UKRI PhD studentship level. Successful candidates will be eligible to receive the equivalent of (UK) student fees and stipend.
How do I apply? We would encourage you to speak to Dr Brennan Kahan (email: firstname.lastname@example.org) in the first instance for further information. Applications by CV and covering letter should be sent to ICTM.email@example.com
Deadline for applications: 17 May 2021.
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