Core Projects | CanTest

Are common blood tests being optimally used for early cancer diagnosis? (PhD)

This PhD project will seek to understand how common (non-biomarker) blood tests are currently used in primary care for cancer investigations with the aim of identifying opportunities to optimise their use for achieving earlier diagnosis.
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Optimising diagnostic strategies for patients presenting to primary care with upper abdominal symptoms to improve the pathway to the early detection of pancreatic cancer (PhD)

By exploring how GPs interpret and act on non-specific upper GI symptoms this project aims to optimise diagnostic strategies for upper abdominal symptoms to improve pathways to the early detection of pancreatic cancer.
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CanTest Social Network Analysis

A study to demonstrate the impact of the CanTest Collaborative in strengthening the research community for early cancer diagnosis in primary care – quantitative and qualitative research techniques used in Social Network Analysis will be used to track the growth and development of the CanTest Network throughout the 5-year collaboration
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Diagnostic accuracy of FIT in patients urgently referred for colorectal cancer

Colorectal cancer (CRC) is among the most frequent types of cancer worldwide, and a leading cause of cancer death. Patients presenting with ‘alarm’ symptoms may be referred by their general practitioner. We aim to evaluate the diagnostic accuracy and applicability of FIT in this group of patients.
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The management of patients with anaemia, the risk of cancer and cancer-related anaemia subtypes (PhD)

This project will provide new insight into the management of anaemic patients, the cancer risk for selected anaemia subtypes and the distribution of cancer-related anaemia.
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Establishing which modalities of artificial intelligence (AI) for early detection and diagnosis of cancer are ready for implementation in the NHS: A Scoping Review

There is accumulating evidence that AI can assist clinicians to make better clinical decisions or even replace human judgement in certain areas of healthcare. In this scoping review we will focus on which modalities of AI for early detection and diagnosis of cancer are ready for possible implementation in the NHS.
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Diagnostic processes and use of investigations before a cancer diagnosis in patients with comorbidities: optimising testing strategies to improve diagnostic timeliness and reduce emergency presentations

Diagnostic processes and use of investigations before a cancer diagnosis in patients with comorbidities: optimising testing strategies to improve diagnostic timeliness and reduce emergency presentations

This project aims to generate evidence for optimising diagnostic strategies in patients with comorbidities experiencing possible cancer symptoms, in order to improve diagnostic timeliness.
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Exploring patient, practitioner and general population preferences towards diagnostic tests for cancer (PhD)

This PhD project will develop a set of choice based experiments to explore the preferences of patients, practitioners and the general public towards different diagnostic test strategies and to assess the risk-benefit trade-offs.
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