‘Precision Medicine’ Approach Helps Predict Who Will Develop Diabetes

ANN ARBOR, MI – A new “precision medicine” approach to diabetes prevention uses existing information such as blood sugar levels and waist-to-hip ratios, rather than a genetic test, to determine who has the highest risk of developing the disease.

The model, published recently in the British Medical Journal, also can help design individualized preventive measures.

When the research team from the VA Ann Arbor, MI, Heathcare System, the University of Michigan and Tufts Medical Center in Boston examined 17 health factors to help determine the effectiveness of diabetes preventing drugs or lifestyle changes, they found that seven seemed to matter the most.

Those are:

  • 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.

Clinical trial data was used to develop a scoring scale which assigns points to each measure to calculate total score. The authors said they hope to turn the scale into a tool that can be used for patients with pre-diabetes or even with other diseases or treatments.

“Simply having pre-diabetes is not everything,” explained lead author Jeremy Sussman, MD, MS. “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 developed the model using data from the Diabetes Prevention Program, which randomly assigned people with an elevated risk of diabetes to placebo, the drug metformin, or a lifestyle-modification program.

Fewer than one in 10 of trial participants who scored in the lowest quarter would be expected to develop diabetes in the next three years, while nearly half of those in the top quarter could expect a diabetes diagnosis in that time period.

“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 are being harmed,” suggested co-author Rod Hayward, MD. “In this instance, a more rigorous analysis of this important trial found that three-quarters of patients took a drug with nontrivial side effects without receiving any benefit, but that the average benefit found in the trial also greatly underestimated 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, although the drug made a significant difference for them, bringing down their risk of the disease by 21%.

Exercise and weight loss, with encouragement from a health coach, benefited everyone in the study to some extent  — 28% for the one-quarter of participants with the highest risk and 5% for those with low diabetes risk.

Using the model to determine which patients have the highest risk of developing diabetes can help healthcare providers choose the correct preventive treatment, the authors pointed out.

1 Sussman JB, Kent DM, Nelson JP, Hayward RA. Improving diabetes prevention with benefit-based tailored treatment: risk-based reanalysis of Diabetes Prevention Program. BMJ. 2015 Feb 19;350:h454. doi: 10.1136/bmj.h454. PubMed PMID: 25697494.

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