PhD Studentship: Chemoprevention of Barrett’s Oesophagus: Target Trial Emulation

This PhD is an exciting springboard from which to develop a career in cancer research and pharmaco-epidemiology.

Background  

Barrett’s oesophagus is the precursor to oesophageal adenocarcinoma (OAC), an aggressive malignancy with a poor prognosis. There is intense interest in the potential role of chemoprevention in the management of Barrett’s oesophagus to reduce the burden of OAC. Preclinical and observational research suggest several promising candidate chemopreventive medications (CCMs), such as proton pump inhibitors, aspirin and statins. Unfortunately, most observational studies are either at serious or critical risk of bias. This research aims to estimate the causal associations between CCMs and malignant progression in Barrett’s oesophagus using a “target trial” emulation using routinely collected health record data.

Research methodology

Series of longitudinal observational cohort studies using the Clinical Practice Research Datalink (CPRD), the world’s largest primary care dataset of 63 million anonymised patient records. The protocol will explicitly align the eligibility criteria, treatment strategies, assignment procedures, outcomes, causal contrasts of interest (intention-to-treat and per-protocol effects) and the analysis plan to that of a hypothetical “target” trial to improve causal inference.

Training

The PhD project will be jointly supervised by Dr Leo Alexandre, Dr Kathryn Richardson and Prof Yoon Loke in collaboration with Dr Allan Clark from Norwich Medical School. The group have strong collaborative links across Norwich Research Park including the Norwich Epidemiology Centre (NEC), department of Gastroenterology (Norfolk and Norwich University Hospital) and the Quadram Institute.

The candidate will be hosted by the NEC, a joint venture between Norwich Medical School and the School of Computing sciences, UEA, specialising in the conduct of high-quality observational research using routinely collected health data. Training will be provided in the clinical area, relevant research methodology, dataset construction and analysis of large health datasets, contemporary evaluation of sources of bias, and cutting-edge statistical techniques. Attendance at formal training courses and conferences is expected.

Person specification

This PhD is suitable for a candidate with any good first degree (minimum 2:1) and a PGDiP/MSc in statistics, epidemiology, public health, data/computer science or applied mathematics.

Please contact Dr Leo Alexandre (leo.alexandre@uea.ac.uk ) for further details.

Funding

This PhD project is in a Faculty of Medicine and Health Sciences competition for funded studentships.  These studentships are funded for 3 years and comprise UK fees, an annual stipend of £17,668 and £1,000 per annum for research training (RTSG). Overseas applicants (including EU) may apply but are required to fund the difference between Home and International tuition fees.