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Active EARLY DETECTION AND DIAGNOSIS COMMITTEE - PROJECT Europe PMC

Unpicking drivers of inequalities in cancer diagnostic outcomes in England with a focus on primary care


Funder Cancer Research UK
Recipient Organization The University of Manchester
Country United Kingdom
Start Date Jan 01, 2025
End Date Dec 31, 2027
Duration 1,094 days
Number of Grantees 1
Roles Award Holder
Data Source Europe PMC
Grant ID EDDAMC-2023/100009
Grant Description

Background Most patients with cancer in the UK are diagnosed following presentation to and referral from primary care.

Inequalities in cancer diagnostic outcomes for populations in high-income countries persist and were exacerbated by the COVID-19 pandemic. There are many drivers of cancer inequalities, and they often intersect.

Aim The main aim is to unpick the key drivers of inequalities in early cancer detection and understand how they intersect.

Methods A range of methodologies will be used to triangulate an understanding of the key drivers of cancer inequalities.

Statistical analyses of routinely collected primary healthcare data with linkage to cancer registry, hospital and administrative data will determine which sociodemographic factors worsen inequalities and at what stage of the diagnostic pathway.

Semi-structured, qualitative interviews with patients, carers and GPs will explore the influence of these factors on symptom recognition, access to primary care, and GP referrals and how they intersect.

Online vignette experiments will measure the impact of adjusting different factors on decision-making by patients and clinicians.

Patient & Public Involvement The investigator team includes a PPI member who will help to ensure the patient voice informs and influences the research throughout.

Patients, members of the public, health policy makers and clinicians will all be part of a co-production workshop to review the key findings of the research and agree on targets for intervention development.

Impact This project will expand our understanding of the key drivers of inequalities in cancer detection and how they interact to identify potential targets for intervention development.

All Grantees

The University of Manchester

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