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PAN-META-COVA

Patient-level data to understand patients' care

There are over 450,000 new cases of cancer in the UK year, with an estimate of about half of the patients being still alive ten years post diagnosis. Survival has significantly improved over the last decades, and cancer has become a “chronic” disease according to NHS England, and other countries. However, with people living longer with a primary cancer, the risks of developing a secondary tumour (known as metastasis) are influenced by many factors and the development of metastasis affects survival, treatment, and quality of life. Metastases appear when the primary cancer has spread to other areas of the body and are estimated to be responsible of 50-90% of cancer deaths. In addition to patients relapsing with metastatic disease there are a significant proportion of patients who present with metastasis at the time of the diagnosis of their primary tumour and amounts to about 26% of patients at the time of diagnosis in the UK.

There is little to no research of incidence and management of secondary tumours (= metastases) on a national level across different ethnicity groups and geographically. Without knowing how patients are managed and what are the outcomes, it is difficult to understand what’s the best practice to apply to newly diagnosed patients. Nationally, the NICE guidelines used clinical trials to understand outcomes. However, clinical trials do not reflect the routinely treated cancer population. Clinical research teams enrol fitter and younger patients than the national cancer population. Therefore, it is difficult to apply outcomes from a young population to an older population.

The principal research objective is to provide a comprehensive view of patterns of care for adult patients with cancer in England, with the intention of providing a firm evidential basis to improve care and reduce mortality and suffering. This includes an analysis of treatment (e.g. surgery, chemotherapy, and radiotherapy), patient events and experiences (e.g. hospital admissions, death, patient experience), outcomes (e.g. overall survival, admission and complications) and costs of care (in-patient, outpatient; direct and indirect care costs). We also aim to assess variations in care, systematic drivers of variation in care, and associations between variations in care and outcomes and costs.

Big data and artificial intelligence: Research
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