Risk-stratified early detection and diagnosis of cancer using linked electronic health records (RREDD-HER)
Approved Research ID: 64351
Approval date: November 25th 2020
Why is this research important: Most patients with cancer initially present with symptoms to their doctor, but half of them have symptoms that are vague or not cancer specific. Therefore, large numbers of individuals experience long diagnostic pathways and many are diagnosed through emergency presentations and with advanced stage cancer at diagnosis. This can lead to poor cancer survival. To diagnose cancer earlier, we need to improve our ability to assess the risk of cancer in these patients. The tools currently available to doctors are limited and doctors mainly have to rely on the presence or absence of typical cancer symptoms. The patient's medical history, such as the previous use of medications and diagnostic tests (and their findings) and whether a patient suffers from long-term conditions, and their underlying susceptibility to cancer, are not fully taken into account.
Aims: We propose a 36-month programme of work to substantially improve our ability to calculate the risk of as-yet-undiagnosed cancer in patients presenting to primary care. In particular, we will:
* Analyse data on symptoms combined with treatment and diagnostic test history
* Update risk calculations at different times as more information on clinical events accumulates along the diagnostic pathway
* Include detailed information on other long-term conditions to improve risk estimates
* Use information on underlying risk of developing cancer, including genetic and lifestyle information to improve risk estimates.
Study Population and Data Sources: We will use the UK Biobank data linked to primary care, hospital care, diagnostic imaging and cancer registration data.
Impact: Our work will support doctors in their assessment of cancer risk and enable earlier diagnosis of cancer. The findings will also inform the development of clinical guidelines and healthcare policies.