Researchers Develop Precision Medicine Model for Diabetes Prevention

Researchers have released a precision medicine approach to diabetes prevention that could identify individuals at the highest risk for developing the disease and who stand to gain the most from a diabetes-preventing drug.

A new model examined 17 different health factors, in an effort to predict who is likely to gain the most from a preventive drug or who can instead benefit from lifestyle changes like weight loss and regular exercise. The researchers found that seven of those factors mattered most.

Twenty-nine million Americans are already diagnosed with diabetes. Being able to identify who is at the highest risk of developing the disease and what preventive steps are most likely to help each of them individually could serve as an important tool.

The model, published in the British Medical Journal, is by a team from the University of Michigan, VA Ann Arbor Healthcare System and Tufts Medical Center in Boston. The researchers hope this model can become a tool for physicians to use with patients who have “pre-diabetes,” currently defined by abnormal results on a test of blood sugar after fasting. Diagnosis of pre-diabetes has led to significant increases in costs due to unnecessary medication.

“Simply having pre-diabetes is not everything,” said lead author Jeremy Sussman, MD, MS, assistant professor of general medicine and the U-M Medical School and research scientists at the VA Center for Clinical Management Research. “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.”

The team of researchers developed the model using data from a gold-standard clinical trial of diabetes prevention: the Diabetes Prevention Program, which randomly assigned people with an increased risk of diabetes to placebo, metformin, or a lifestyle modification program. The model was tested by analyzing data from more than 3,000 people in the study, which consisted of individuals with a high body mass index and abnormal results on two fasting blood sugars. Most of the participants had a family history of the disease, and more than one-third were African American or Latino, all known to be associated with an increased risk of developing diabetes.

The seven factors that the team found were most useful included fasting blood sugar, long-term blood sugary (A1C level), total triglycerides, family history of high blood sugar, waist measurement, height, and waist-to-hip ratio. The researchers developed a scoring scale using the data from the trial, assigning points to each measure to calculate total score.

Fewer than one in 10 participants who scored in the lowest quarter would develop diabetes in the next three years, while almost half of those in the top quarter would develop the disease in that time. The team then looked at what impact the two diabetes-preventing approaches had.

“Our research has found that it is common that, although the average benefit in a clinical trial might be moderate, in reality those patients at high risk for a bad outcome get a lot of benefit, the average patient has modest chance of benefiting, and lower-risk patients may have little to no chance of benefitting or being harmed,” said co-author Rod Hayward, MD, professor of medicine and public health at U-M and a senior research scientist at the VA Center for Clinical Management Research. “In this instance, a more rigorous analysis of this important trial found that three-quarters of patients took a drug with non-trivial side effects without receiving any benefit, but that the average benefit found in the trial also greatly under-estimated the benefits for those at very high risk of developing diabetes in the next five years.”

The team found that metformin benefited only the people who the model showed had the very highest risk of developing diabetes. However, taking the preventive drug significantly brought down this groups’ risk of disease, with a 21 percent reduction in risk.

On the other hand, exercise and weight loss, with encouragement from a health coach, benefited all study participants to a certain extent, according to the new model. For the participants who the model deemed at highest risk of developing the disease, this lifestyle intervention reduced their chance of developing diabetes by 28 percentage points. For those with the lowest diabetes risk, this same intensive lifestyle change reduced their risk as well, but only by five points.

Using this model to identify patients at the highest risk of developing diabetes could help guide physicians in determining who should receive diabetes preventing drugs, especially since metformin is associated with side effects.

“We think this approach should be broadly applicable, since one of the main determinants of any patient’s likelihood of benefiting from a therapy is their risk of having the bad outcome that we are trying to prevent,” said co-author David M. Kent, MD, MSc, professor at Tufts University and director of the Predictive Analytics and Comparative Effectiveness Center at the Tufts Medical Center. “It is poorly appreciated how many patients receive treatments unnecessarily – when the possibility of benefit is very low, and may well be exceeded by the burdens of treatment. If these types of analyses were incorporated routinely into trial design, we believe we would have a much clearer understanding of this issue.”

Source: University of Michigan Health System

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