Diabetes treatment calculators developed
Two risk calculators have been developed which could help healthcare professionals prescribe better combination treatment for people wth diabetes.
The research into personalised treatments was presented at this year’s Diabetes UK Professional Conference in Manchester.
One of the risk calculators, which was developed by teams from Exeter, Dundee, Oxford and Glasgow Universities, can predict how well someone’s blood glucose levels will be controlled by two drugs used to treat type 2 diabetes. Sulfonylureas and thiazolidinedione are second-line treatments for the condition, but there is currently little guidance about which therapies work best and for who.
The Exeter team are also working on another risk calculator which could improve diabetes diagnoses as it is sometimes quite difficult for the type to be classified, resulting in a delay of treatment. It is also important the correct type of diabetes is diagnosed from the start so the right treatment can be prescribed.
Dr Angus Jones, lead researcher based at the University of Exeter Medical School, said: “An accurate diagnosis of type 1 or type 2 diabetes is hugely important, as the treatment of these two conditions is very different.
“Unfortunately it can be difficult to tell what type of diabetes someone has when they’re first diagnosed, as there’s no single feature that confirms a diabetes type.
“By using a simple website programme or smartphone app called a clinical calculator, we can combine different features to give an accurate probability of whether a person has type 1 or type 2 diabetes. This will help doctors and patients to decide on the best initial treatment and whether extra tests are needed.
“We are currently testing this calculator in a large study of 1500 people newly diagnosed with diabetes, funded by the National Institute of Health Research. We hope research like this will help people with diabetes answer two important questions: what type of diabetes do I have and what treatment works best for me?”
Both risk calculators will help doctors prescribe the best possible treatment, as different people respond to treatments in different ways. This should also help to improve people’s health outcomes, as tailored diagnosis and treatments should mean the right therapy is given to the right person sooner, based on more accurate predictions of how someone will respond.
Data from more 70,000 people with type 2 diabetes was collected from clinics and a further 2,000 took part in clinical trials who were taking either sulfonylureas or thiazolidinedione. They examined how their blood glucose levels were influenced by simple characteristics including gender, age and Body Mass Index (BMI).
Using this information, they created a risk calculator that predicts how well a person’s blood glucose levels will be controlled by each drug. Extending the calculator to include other medication could help clinicians to develop a personalised treatment regime for their type 2 diabetes patients.
The Exeter research team’s type 1 diabetes classification calculator uses clinical information (like age of diagnosis or BMI) together with indicators of type 1 diabetes (like levels of autoantibodies and a new genetic test of Type 1 diabetes risk) to accurately predict the type of diabetes. This helps to decide if a person should receive insulin or tablets at diagnosis. The calculator has been developed using information from 1,187 people who have taken part in previous studies.
Dr Elizabeth Robertson, director of research at Diabetes UK, said:”Diabetes is an incredibly complex condition and people respond to different therapies in different ways. What works for one person may not work for another. We need to move away from a ‘one size fits all’ approach to both treatments and diagnosis.
“Research like this is helping us to manage that complexity and move towards a more personalised approach to caring for people with different types of diabetes. People with diabetes face the risk of life-changing, and life-limiting, complications, unless they are given the very best care and the support they need to manage their condition well alongside the right treatment at the point of diagnosis.”