Using simple, routine measures that are easy to obtain in a diabetes clinic, such as age at diagnosis and body mass index, can be an effective way to choose the best treatment for a person with type 2 diabetes.

Share on Pinterest New research points to a very simple method of personalizing treatment for type 2 diabetes.

This was the conclusion that researchers at the University of Exeter, in the United Kingdom, came to after they compared the simple approach to a “subgroup model” that researchers in Sweden and Finland had proposed in an earlier study.

They report their findings in a paper that now features in The Lancet Diabetes & Endocrinology journal.

“It’s recognized,” says lead study author John M. Dennis, Ph.D., who is a research fellow in medical statistics at the University of Exeter College of Medicine and Health, “that not everyone with type 2 diabetes should be treated the same, yet there is currently no way to tell which tablet is likely to be the best for a particular person.”

The earlier study identified “five replicable clusters” of adults with diabetes. The five clusters differed by “disease progression and risk of diabetic complications.” The authors suggested that these could be a useful way to guide the treatment of diabetes.

However, the new study reveals that using very straightforward clinical features, such as age at diagnosis, sex, body mass index (BMI), and a measure of kidney function, is a more practical and effective method of choosing treatments and identifying which patients are most likely to experience complications such as kidney disease.

“Crucially, this approach does not mean reclassifying people into discrete subtypes of diabetes,” Dennis explains, adding that, in their study, they “were able to use a person’s exact characteristics to provide more precise information to guide treatment.”