Choosing Diabetes Treatment: A Simpler Way

Using measures easily obtained in a clinic, such as age at diagnosis, body-mass index (BMI) and sex can help health-care providers determine what type of treatment might be best for a person with type 2 diabetes, according to new research in the journal The Lancet Diabetes & Endocrinology.

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“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.” So says John M. Dennis, PhD, co-author of the study investigating the best way to choose diabetes treatment.

Dennis, a research fellow at the University of Exeter College of Medicine and Health in Great Britain, wanted, along with his colleagues, to test the efficacy of an earlier study that had been done by researchers in Norway and Sweden. That study had identified five clusters, or subgroups, of diabetes patients, categorized by such things as obesity and insulin resistance or deficiency, and had assigned patients to different subgroups. This categorization, it was hoped, would help physicians determine optimal treatment.

For their new study, the British researchers examined data from more than 8,500 diabetes patients recruited between April 2000 and June 2002 and followed until June 2006. The researchers compared the earlier subgroup classification strategy with what they described as “simpler approaches based on routine clinical measures available in any diabetes clinic.” These measures included age at diagnosis, BMI, sex and kidney function as measured by a standard method of analysis. According to study co-author Andrew Hattersley, MD, “Our research tested whether simple clinical characteristics are useful to help clinicians manage their patients.”

The researchers found that the earlier subgroup/cluster method “suggested but did not show that the clusters could be useful to guide choice of therapy.” In contrast, said Dr. Hattersley, “We found that using simpler measurements available freely in clinics can lead to improved prediction of patient outcomes.”

The researchers summed up their conclusions by stating, “Patients with type 2 diabetes differ in treatment response and risk of disease progression….” Because “clinical features outperformed the clusters for treatment selection, the results suggest that there will be greater clinical utility from modeling clinical features directly, rather than from using clinical features to place patients into subgroups.”

Want to learn more about type 2 diabetes research? Read “Type 2 Diabetes Research: What’s New?” “Tight Blood Pressure Control Benefits Type 2 Diabetes: Study” and “Low-Carb Breakfast for Diabetes Control.”

Joseph Gustaitis

A freelance writer and editor based in the Chicago area, Gustaitis has a degree in journalism from Columbia University.

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