The Best Way to Predict Diabetes?
Researchers have just developed a “precision medicine” approach to diabetes prevention that could use existing information like blood sugar levels and waist-to-hip ratios, and without needing new genetic tests.
The new model looked at 17 different health factors, in an effort to predict who would gain the most from a diabetes-preventing drug, or from lifestyle changes such as weight loss and exercise. Seven factors were especially important: fasting blood sugar, long-term blood sugar (A1C level), total triglycerides, family history of high blood sugar, waist measurement, height, and waist-to-hip ratio. They developed a scoring scale using the clinical trial data, assigning points to each measure to calculate total score.
The model is published in the British Medical Journal by a team from the University of Michigan, VA Ann Arbor Healthcare System and Tufts Medical Center in Boston.
The researchers hope to turn it into a tool for doctor to use with patients who had “pre-diabetes,” defined as abnormal results on a blood-sugar test after fasting.
“Simply having pre-diabetes is not everything,” says lead author Jeremy Sussman, M.D., M.S. “This really shows that within the realm of pre-diabetes there’s a lot of variation, and that we need to go beyond single risk factors and look holistically at who are the people in whom a particular approach works best.” Sussman is an assistant professor of general medicine at the U-M Medical School and a research scientist at the VA Center for Clinical Management Research.
Fewer than one in 10 of trial participants who scored in the lowest quarter would develop diabetes in the next three years, according to a news release from the University of Michigan, while almost half of those in the top quarter would develop diabetes in that time.