Routine clinical measurements such as age and weight may be the best way to choose the right treatment for people diagnosed with type 2 diabetes, according to a new UK study.
Research by the University of Exeter Medical School found looking at simple clinical characteristics on an individual basis was a more effective and practical way of selecting the appropriate diabetes drug than dividing people into subgroups.
“We need to move beyond a one-size-fits-all approach to treatment”
The study, published in The Lancet Diabetes and Endocrinology, looked at data from more than 8,500 people who took part in two separate clinical trials.
The research team compared the effectiveness of using routine measures available in any diabetes clinic, with a model developed by Swedish researchers, which divides adults with diabetes into five subgroups to help determine the best course of treatment.
Their findings show the use of basic clinical measurements such as age, sex and kidney function “markedly outperformed” the cluster model when it came to choosing the right treatment.
It was widely recognised that not everyone with type 2 diabetes should be treated the same, explained lead author Dr John Dennis.
However, he added that there had previously been no way to tell which medication was likely to be best for a particular person.
“Our research shows that really simple clinical features such as age at diagnosis, sex and kidney function provide a very effective and practical way to identify the best tablet for a particular person and to identify people at high risk of complications,” said Dr Dennis.
“Crucially, this approach does not mean reclassifying people into discrete subtypes of diabetes,” he added. “Instead, we were able to use a person’s exact characteristics to provide more precise information to guide treatment.”
The paper found using simple clinical features “worked as well or better to predict disease progression”.
“This approach does not mean reclassifying people into discrete subtypes of diabetes”
Meanwhile, clusters were “markedly outperformed by models that used simple clinical feature for the prediction of glucose-lowering response and for treatment selection,” the paper said.
Responding to the research, Diabetes UK said there was a need to move away from a “one-size-fits-all” approach to treating type 2 diabetes.
“Type 2 diabetes is a complex condition and we need to move beyond a one-size-fits-all approach to treatment,” said Dr Emily Burns, head of research communication at Diabetes UK.
“This research suggests that healthcare professionals can use simple measurements readily available to them now, including BMI and age of diagnosis, to determine the best treatments for each individual person,” she added. “This could also potentially help them to work out who is most at risk of serious diabetes complications, so they can intervene early.
“Personalising medicine for people with type 2 diabetes is so important, and this research – expanding our understanding of how best to choose the right treatment for each person – takes us one step closer,” Dr Burns said.