How can we better predict those at greatest risk of developing depression following a cancer diagnosis? (360G-Wellcome-324038_Z_25_Z)

Depression is common, yet remains both under-diagnosed and under-treated in people living with cancer. It is estimated that between 8 to 24% of people go onto experience a depressive illness following a cancer diagnosis. There is a pressing public health need to better predict and identify individuals with cancer who are at risk of developing depression. The stigma associated with depression, lack of physical–mental healthcare integration, and fragmentation of care have been identified as barriers towards targeted screening and diagnosis. The aim of this PhD is to improve the identification and understanding of the impact of depressive disorders in people living with cancer. We will use routinely collected data (including the Clinical Practice Research Datalink) to discover clinically relevant risk factors, develop and evaluate statistical models to estimate individualised risk, and then undertake early translational research using a mixed-methods approach. The specific objectives are to: 1) Collate data on risk factors for developing depression following a cancer diagnosis using routinely collected data, 2) Develop statistical models to estimate individualised risk of depression following a cancer diagnosis and an adverse outcome, and 3) Understand how risk estimates can be used to improve under detection.