Disease Free Survival: handling survival and quality of life data in clinical trials

PROJECT OVERVIEW

Traditionally, randomised controlled trials in cancer have focussed predominantly on overall survival (OS) and progression free survival (PFS) as the main outcomes of interest and primary drivers or interpretation. However, increasingly, the quality of life (QoL) of patients is being recognised as a critical outcome in these studies, alongside OS and PFS. QoL is particularly important when the cancer treatments given have substantial negative impacts upon health and when anticipated survival benefit are lower. Statistical approaches exist that deal with assessing quality of life and standard oncology outcomes (OS, PFS) together but approaches vary and the appropriateness of these methods, particularly within a clinical trial framework, is unclear.

This DPhil will review practice in contemporary oncology trials and explore the use of deterioration free survival approach (where deterioration of quality of life is an event) and the approaches to analysis used. Real, and simulated, datasets will be used to explore the value of these methods under varying scenarios. Importantly, there is scope of modify the specific objectives of this project to align to any specific interests of the student. 

TRAINING OPPORTUNITIES

The proposed project will be part of the statistical methodology work in the Oxford Clinical Trials Research Unit (OCTRU)’s Statistics Team and the Centre for Statistics in Medicine (CSM).  As such, students will have the opportunity to work closely with the OCTRU Statistics Team and members of the CSM. Alongside departmental training opportunities listed below, training will be provided on relevant techniques including systematic reviewing, statistical modelling, critiquing clinical trial methodology, and evaluating the value of statistical methods in practice.

A core curriculum of lectures will be taken to provide a solid foundation in a broad range of subjects including statistics and clinical trial methodology. Students will also be required to attend regular seminars within the Department and those relevant in the wider University. Students will have access to various courses run by the Medical Sciences Division Skills Training Team and other Departments. All students are required to attend a 2-day Statistical and Experimental Design course at NDORMS and run by the IT department (information will be provided once accepted to the programme).

Students will be expected to present data in Departmental seminars, to the OCTRU Statistics Team and the Centre for Statistics in Medicine, and to attend external conferences to present their research globally; limited financial support is available from the Department.

KEY PUBLICATIONS

• Collett, D. (2023). Modelling Survival Data in Medical Research (4th ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781003282525
• Elashoff R, Li N. Joint modelling of longitudinal and time-to-event data. Chapman and Hall/CRC; 2016 Oct 4. https://doi.org/10.1201/9781315374871
• Henderson R, Diggle P, Dobson A. Joint modelling of longitudinal measurements and event time data. Biostatistics Dec 2000; 1(4):465480. https://doi.org/10.1093/biostatistics/1.4.465

KEYWORDS

Clinical trials; oncology; statistics; overall survival; progression free survival

HOW TO APPLY

Please contact the named supervisor(s) to express your interest in this project. You should also contact the Graduate Studies Office (graduate.studies@ndorms.ox.ac.uk) who will be able to advise you of the essential requirements for this programme and provide further information on how to make an official application. Interested applicants should have, or expect to obtain, a first or upper second-class BSc degree or equivalent in a relevant subject and will also need to provide evidence of English language competence (where applicable).

The application guide and form is found online and the D.Phil will commence in October 2025.

Applications should be made to the following programme, using the specified course code:

DPhil in Clinical Epidemiology and Medical Statistics (RD_NNRA1). 

For further information, please visit: http://www.ox.ac.uk/admissions/graduate/applying-to-oxford.

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