Clinical trials are crucial for improving outcomes of patients. This includes a plethora of trials of new cancer drugs and treatment protocols that are slowly transforming cancer from a fatal to a chronic disease. A key outcome measure in many of these trials, along with overall survival, is progression-free survival (PFS). The latter is used as a surrogate of overall survival and in evaluating new treatment schedules/drugs and cost-benefit decisions on care provision.
Knowledge of recurrence status is essential for accurately calculating PFS. Currently, recurrence status can only be reliably confirmed by manual review of patient notes. This usually involves central coordination by the trial management team, retrieval of copies of hospital notes by the local trial teams followed by independent blinded review of the redacted notes by a clinical expert committee. All of this is time-consuming, resource intensive and substantially increases the costs of trial follow up. It also introduces a potential source of bias as members of the trial team can become unblinded to treatment group.
Health data is routinely collected by disease registries and national statutory bodies including NHS Digital, who collate Hospital Episodes Statistics and other national datasets. However this system has not been designed to routinely record cancer progression. Increasingly this data is being used by clinical trialists to augment or replace traditional trial-collected data, especially clinical outcomes, as it saves significant amounts of time and resources, enables long-term follow up, and improves external validity.
This PhD aims to develop and validate an algorithm for the detection of recurrence of selected cancer sites from routinely-collected health datasets available in England. New algorithms will be developed for ovarian and endometrial cancers, and we aim to validate an externally developed algorithm for breast and colorectal cancers.
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 highly numerate with an interest in clinical trials. Clinical experience, in particular in the field of oncology is desirable.
Who are the supervisors? The supervisory team includes Profesor Usha Menon and Dr Macey Murray. 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 Macey Murray (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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