Pancreatic Cancer Epidemiology V0001
Research type
Research Study
Full title
Epidemiology of Pancreatic Cancer Using Longitudinal Electronic Health Record Data
IRAS ID
249837
Contact name
Abu Zafer M Dayem Ullah
Contact email
Sponsor organisation
Queen Mary University of London
Duration of Study in the UK
4 years, 11 months, 31 days
Research summary
Pancreatic Cancer (PaC) is projected to be one of the leading causes of cancer-related death by 2030, second only to lung cancer. Meta-analyses of heterogeneous small case-control studies have implied a number of potential risk factors for PaC, such as age, diabetes, smoking, alcohol and being overweight. Most of these works have taken place in Europe or USA on predominantly Caucasian populations. As such, the risk factors for PaC in multi-ethnic populations have not been well-defined. This study takes the unique opportunity to study PaC risk factors on a truly diverse multi-ethnic population of East London. The study primarily aims to discover and evaluate novel and known risk factors associated with PaC, and lay the foundation for potential integration with molecular data for further stratification of PaC patients.
The research will use linked electronic health records (EHR), including primary and secondary/tertiary care data, of the patients diagnosed/reported with pancreatic and biliary diseases within Barts Health NHS Trust since 2007. Patients' so-far-complete clinical history in the form of Hospital Episode Statistics (HES)/Commissioning Data Sets (CDS) and GP records will be collected from various sources. The cut-off date for data collection is projected at December 2021. A case-control study will be conducted, based on the retrospective data, between PaC diagnosed and other patients, matched by the appropriate demographics, focusing on various epidemiological factors and clinical data. The association between various exposures and outcomes will be measured, odds ratios will be derived, with length and dose of exposure to known risk factors as stratification categories. The study data will also be utilised by various machine learning techniques to develop prototype predictive models for effective decision making of future onset, progression or outcomes of PaC.
REC name
East of England - Essex Research Ethics Committee
REC reference
19/EE/0163
Date of REC Opinion
17 May 2019
REC opinion
Favourable Opinion