Five million people in England have blood glucose levels which are higher than normal but not high enough to be diagnosed with Type 2 Diabetes - this is called pre-diabetes. People with pre-diabetes are likely to develop diabetes. However, diabetes can be prevented for many people with pre-diabetes if they attend a diabetes prevention programme. These programmes are usually delivered to groups and support people to follow a healthy lifestyle. In 2016, the NHS launched the NHS Diabetes Prevention Programme for people with pre-diabetes. The programme delivers multiple sessions over 9 months and is therefore expensive to provide. Of those with pre-diabetes, some people are at very high risk of developing diabetes and would benefit from attending a prevention programme. Whereas, others are at lower risk and their blood glucose levels may even return to normal, healthy levels. Our proposed work will develop a tool for calculating this risk so that programmes can be targeted at those who would most benefit. We will develop a risk tool using factors such as glucose level, body mass index, age, and ethnicity and test how well the tool works using electronic health records from the Clinical Practice Research Datalink.
It is estimated that five million people have non-diabetic hyperglycaemia (HbA1c 42-47 mmol/mol (6.0-6.4%) or fasting plasma glucose 5.5-6.9 mmol/l) in England. Epidemiological studies show that only some of these people will progress to Type 2 Diabetes (T2DM). The NHS Diabetes Prevention Programme is currently open to all those with non-diabetic hyperglycaemia. We aim to develop and validate a prognostic model which calculates the risk of developing T2DM in those with non-diabetic hyperglycaemia, using factors such as glucose level, body mass index, age, ethnicity, smoking status, medications, blood pressure, history of cardiovascular disease, family history of type 2 diabetes. To derive the prognostic model, we will use data from primary care medical records from the Clinical Practice Research Datalink to fit a time to event model with time to T2DM as the dependent variable (using either a Cox proportional hazards model or a flexible parametric model). We will assess risk of T2DM at a clinically-relevant time points (5- and 10-year risk) and validate the model using bootstrapping. The baseline survival and coefficients from the final model will be used to form the prognostic score. This score could then be used to target diabetes prevention programmes to those at greatest risk.
Progression to Type 2 diabetes
Laura Gray - Chief Investigator - University of Leicester
Laura Gray - Corresponding Applicant - University of Leicester
Briana Coles - Collaborator - University of Leicester
Francesco Zaccardi - Collaborator - University of Leicester
Kamlesh Khunti - Collaborator - University of Leicester
Melanie Davies - Collaborator - University of Leicester
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation