Status
Completed
Title
DELTA - integrated Diagnostic solution for Early detection of Oesophageal cAncer
What were the objectives of the study?
Oesophageal cancer is the sixth most common cause for cancer related deaths worldwide. Compared to the rest of the European countries, UK has some of the worst outcomes mainly due to late diagnosis. The main risk factor for oesophageal cancer is chronic reflux and due to the high prevalence and non-specific nature of reflux symptoms, most patients are treated with acid-suppressant medications without referral for endoscopy. Three- to six- percent of individuals with reflux may have Barrett’s oesophagus, which is a health condition that may cause oesophageal cancer. Barrett’s oesophagus can be treated but only 20% of patients with Barrett’s oesophagus are diagnosed. It is estimated that burden of oesophageal cancer could be reduced by up to 50% if all patients with chronic reflux are investigated. This is a formidable task since the NHS only has limited testing capacity and heartburn is common in the UK population. Currently, GPs are advised to treat their patients with antacid medications unless the patient present with “alarm” symptoms. Patient without alarm symptoms often continue to take the antacid medications life-long and there are increasing concerns about long-term side effects of antacids.
The output of this study will allow GPs to better identify patients who may benefit from endoscopy either as a result of early cancer detection or detection of Barrett’s oesophagus, based on patterns of prescription acid-suppressant use as well as other characteristics of the patients.
HOW IS THE RESEARCH BEING DONE?
We will use a large population based database called QResearch to identify a group of people who are 40 years and over and have never had a diagnosis of oesophageal cancer. We will determine the pattern of prescription antacid use in this population and evaluate the risk of oesophageal cancers associated with the duration, dose, and type of the antacids along with other traits of the patients.
How was the research done?
We will use a large population based database called QResearch to identify a group of people who have never had a diagnosis of oesophageal cancer. We will determine the pattern of prescription antacid use in this population and evaluate the risk of oesophageal cancers associated with the duration, dose, and type of the antacids along with other traits of the patients.
Chief Investigator
Professor Julia Hippisley-Cox (Work Package 1)
Lead Applicant Organisation Name
Sponsor
Oxford
Location of research
University of Oxford
Date on which research approved
02-Nov-2020
Project reference ID
OX39
Generic ethics approval reference
18/EM/0400
Are all data accessed are in anonymised form?
Yes
Brief summary of the dataset to be released (including any sensitive data)
GP data will be used to identify the main exposure prescription acid-suppressant use and related drug interactions as well as potential risk factors including age, gender, comorbidities, other medication use, BMI and smoking. GP data will also be used to identify prescription patterns of acid suppressants, duration of use, and hospital specialist referrals.
HES data will be used to identify diagnoses of cancer and associated risk factors.
Mortality data will be used to identify the primary outcome death with the oesophageal cancer as the cause of death.
Cancer registry data will be used identify incident cancers. Information on grade, stage, morphology and route to diagnosis will be extracted for descriptive purposes.
What were the main findings?
The team developed the new tool by analysing the anonymised medical records from over 12 million patients from GP practices contributing to the QResearch database across England and identified over 16,000 cases of oesophageal cancer. The researchers incorporated key factors like age, lifestyle habits, medical history and medication use into the CanPredict algorithm.
Once developed, CanPredict was checked by testing it in a separate set of QResearch practices (over 4 million patients) and the Clinical Practice Research Database (over 2.5 million patients). In testing, CanPredict accurately predicted an individual’s risk of oesophageal cancer within the next decade. It outperformed existing models for estimating oesophageal cancer risk.
The study also highlighted the importance of factors such as age, body mass index, smoking, alcohol consumption, and previous medical conditions in determining the risk of developing oesophageal cancer. The algorithm’s ability to integrate these factors offers a comprehensive and personalised risk assessment for patients and can also help the NHS optimise the use of its resources by targeting those at highest risk who are most likely to benefit from screening.
Funding Source
Project DELTA, funded by INNOVATE UK, aims to improve the diagnosis of oesophageal cancer. It is a collaboration between the Universities of Cambridge, Oxford, King's College London, the PHG Foundation and Cyted. Advisory Board support is provided by Action Against Heartburn, Heartburn Cancer UK, the West Yorkshire and Harrogate Cancer Alliance and Newcastle University.
Public Benefit Statement
Research Team
Professor Julia Hippisley-Cox, Ms Winnie Mei, Dr Pui San Tan Professor Carol Coupland (University of Oxford)
Professor Rebecca Fitzgerald (University of Cambridge)
Professor Peter Sasieni (Kings College London)
Project DELTA, funded by Innovate UK, is a collaboration between the Universities of Cambridge, Oxford, King's College London, the PHG Foundation and Cyted. Advisory Board support is provided by Action Against Heartburn, Heartburn Cancer UK, the West Yorkshire and Harrogate Cancer Alliance and Newcastle University. For further details of the DELTA project consortium, see here
Publications
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Project DELTA - integrateD diagnostic solution for EarLy deTection of oesophageal cAncer:
Authors: hippisley-Cox J, Fitzgerald R, Mei W, Tan PS, Coupland S, Saseini P.
Ref:
https://www.qresearch.org/media/1284/ox39-delta-wp1-protocol_20210211.pdf -
Development and validation of a novel risk prediction algorithm to estimate 10-year risk of oesophageal cancer in primary care: prospective cohort study and evaluation of performance against two other risk prediction models
Authors: Hippisley-Cox J, Mei W, Fitzgerald, Coupland CAC
Ref:
https://www.sciencedirect.com/science/article/pii/S2666776223001199?via%3Dihub -
Ethical and legal implications of implementing risk algorithms for early detection and screening for oesophageal cancer, now and in the future
Authors: Brigden T, Mitchell C, Redrup Hill E, Hall A
Ref:
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0293576
Press Releases
- QResearch database researchers collaboration on two major cancer projects 07/07/2020
- UKRI invests £13m in life saving projects 03/07/2020
- DELTA project Cambridge and Oxford awarded government funding to speed up cancer diagnoses 03/07/2020
- New study offers hope in early detection of oesophageal cancer
- New tool to predict people’s risks of getting oesophageal cancer
Access Type
Trusted Research Environment (TRE)