Background. In several therapeutic areas, it is important to identify the minimal effective duration of treatment, for a variety of reasons. For example, reducing antibiotics use might counter antimicrobial resistance. Reducing TB therapy might improve adherence. Reducing Hepatitis C treatment might limit costs and make it possible to treat more patients. It is important, though, that this is not done at the expense of treatment effectiveness.
The DURATIONS design is a recently developed trial design to optimise treatment duration. While classic 2-arm trials randomise patients to receive either the standard or an experimental treatment (duration), in order to compare them in terms of a primary outcome of interest, the DURATIONS design builds on two ideas: first, patients are randomised to multiple arms, generally corresponding to different durations or doses; second, the whole duration-response curve is modelled, by means of flexible regression methods.
The DURATIONS design is being implemented in a number of trials, both at the MRC-CTU and more broadly. As it is standard in the development of new statistical methods, each application opens up new questions and requires methodological work to adapt the novel method to the specific challenges faced. Hence, the main aim of this Ph.D. project is to solve methodological issues around the DURATIONS design motivated by these applications.
What the studentship will encompass. The Ph.D. project will focus on one specific application of the DURATIONS design: the REFINE clinical trial. REFINE’s goal is to seek the optimal frequency of immunotherapy treatment for patients with either lung, skin, renal or bladder cancer. The motivation is that reducing treatment frequency may improve patients` quality of life and reduce side effects. While the trial has been designed with 2-year landmark overall survival as primary outcome, using time-to-event outcomes could potentially improve the efficiency of the trial, by making better use of all the available data. However, the DURATIONS design has been currently developed for binary outcomes only. Therefore, the main objective of the Ph.D will be to extend the design to make use of time-to-event outcomes. The student will compare different modelling strategies, seeking the most efficient option. They will then compare power and type 1 error of two trials designed under similar assumptions but using either a binary or a time-to-event outcome. This will inform on the relative advantage of using time-to-event data in terms of efficiency.
REFINE will be a so-called basket trial, meaning that different cancer types will be evaluated altogether, in the same basket, because of the expected similarity of treatment effect across conditions. There is considerable debate in the literature on what is the best way of combining different cancer types in the same basket. The student will study the relevant literature and compare different approaches, specifically in the case of a DURATIONS trial. Possible solutions could include adding a main effect for cancer type in the frequency-response model, adding an interaction, designing separate trials for different cancer types, or adopting Bayesian methods to borrow information across cancer types. The goal will be to compare the different methods both in terms of resilience of the design to assumptions made and of efficiency in identifying the optimal frequency.
Finally, the student will investigate possible ways of implementing adaptive steps into the design, in order to maximise the chance to focus recruitment on the most promising durations.
Dr Matteo Quartagno will be the main supervisor, co-adjuvated by Professor James Carpenter and Professor Max Parmar. All three supervisors were involved in the development of the novel trial design that the student is expected to extend.
As DURATIONS trials are a particular type of non-inferiority study, involvement of PPI representatives will be particularly important, in order to learn what are the main features of the design that might attract, or discourage, potential patients. The student will be expected to organise meetings with PPI representatives to discuss possible actions to be taken for REFINE or more broadly for future DURATIONS trials.
Candidates should hold either a B.Sc. or a M.Sc. in statistics, epidemiology or any related discipline. Prior knowledge of statistical programming languages such as R and/or Stata is required.
HOW TO APPLY
You are applying for a PhD studentship from the MRC TMRP DTP. A list of potential projects and the application form is available online at:
Please complete the form fully. Incomplete forms will not be considered. CVs will not be accepted for this scheme.
Please apply giving details for your first choice project. You can provide details of up to two other TMRP DTP projects you may be interested in at section B of the application form.
Before making an application, applicants should contact the project primary supervisor to find out more about the project and to discuss their interests in the research.
The deadline for applications is 4pm (GMT) 18 February 2022. Late applications will not be considered.
Completed application forms must be returned to: [Email Address Removed]
Informal enquiries may be made to [Email Address Removed]