Precision medicine could prevent the flawed 'one size fits all' diet recommendations we currently get from the federal government and self-professed nutrition experts who latch onto the latest fad to sell books.

29 million Americans already already have diabetes and the way to separate those with the highest risk of developing the disease from those with lower risk, and channel resources into areas most likely to help each of them individually, is the goal of the "precision medicine" approach.

It is still rudimentary, relying on systematic review of epidemiology to claim causation by blood sugar levels and waist-to-hip ratios, but the more factors the better. A new model examined 17 different health factors, in an effort to predict who stands to gain the most from a diabetes-preventing drug or who can instead benefit from lifestyle changes like weight loss and regular exercise. 7 of those factors turned out to matter most.

That is good news, because one of the latest health crazes is diagnosing people with "pre-diabetes", a term which should be eliminated from the vocabulary of reputable people and is currently defined by abnormal results on a test of blood sugar after fasting, which has led to significant surges in costs due to unnecessary medications.

The team developed the model using data from a clinical trial of diabetes prevention: the Diabetes Prevention Program, which randomly assigned people with an elevated risk of diabetes to placebo, the drug metformin, or a lifestyle-modification program. After analyzing data from more than 3,000 people in the study, they found that all had a high body mass index and abnormal results on two fasting blood sugar tests. Most also had a family history of diabetes, and more than a third were African American or Latino - all known to be associated with higher risks of diabetes.  You see the problem with epidemiology in that. They are also more overweight, on average, but the study makes it seem like ethnicity is associated with it, even though people of those ethnicities in other countries don't have higher rates, nor do thin people.

In all, they looked at 17 factors that together predicted a person's risk of diabetes - and his or her chance of benefiting from diabetes-preventing steps. They found seven factors were most useful:

1)  fasting blood sugar
2) long-term blood sugar (A1C level)
3) total triglycerides
4) family history of high blood sugar
5) waist measurement
6) height
7) waist-to-hip ratio.

They developed a scoring scale using the clinical trial data, assigning points to each measure to calculate total score. Fewer than 10 percent of trial 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 diabetes in that time. Then, the team 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 benefiting, or are being harmed," says co-author Rod Hayward, M.D. "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 three to five years."

The team found that metformin benefited only the people who the model showed had the very highest risk of developing diabetes. But for them, it really made a difference, bringing down their risk of the disease by 21 percentage points.

By contrast, exercise and weight loss, with encouragement from a health coach, benefited everyone in the DPP study to some extent, the new model shows.

For the one-quarter of study participants who the model says had the highest risk of diabetes, this lifestyle intervention cut their chance of developing the disease by 28 percentage points. For those who had the lowed diabetes risk, this same intensive lifestyle change brought down their risk too - but only by 5 points.

Figuring out who is in the highest-risk group, by applying the new model to members of the general population, could really help guide doctors - especially since metformin does come with side effects, but also can help some patients get a jump start on losing weight.

Exercise and weight loss didn't make a huge dent in the diabetes risk of those who were on the lower end of the risk scale to begin with, but exercise and weight loss have many benefits besides lowering diabetes risk. 

"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," says co-author David M. Kent, M.D., M.Sc., a 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."

Citation: BMJ Online, February 19, 2015, doi:10.1136/bmj.h454.  The study was funded by the Patient-Centered Outcomes Research Institute (1IP2PI000722), the National Institute of Neurological Disorders and Stroke (U01 AA022802), the Department of Veterans Affairs Quality Enhancement Research Initiative (QUERI DIB 98-001), and the National Institute of Diabetes and Digestive and Kidney Diseases (P60 DK-20572).