The Particulars: The ability to predict patients who are most likely to develop type 1 diabetes would allow for identification of the disease in its earliest stages of development, interventions to preserve beta cell function, and possible prevention of the onset of symptomatic diabetes.
Data Breakdown: For a study, variables were identified that are most predictive of type 1 diabetes development—BMI, age, fasting C-peptide levels, a measure of overall C-peptide production and a measure of overall glucose—and used to create the “DPTI Risk Score.” When applied to data from the TrialNet Natural History Study, which focused on delaying and preventing the onset of type 1 diabetes in high-risk individuals. The risk score was found to be highly predictive of type 1 diabetes development among TrialNet participants. The DPTI risk score even identified those with normal glucose tolerance who were nonetheless at risk.
Take Home Pearl: A risk score called the DPTI Risk Score appears to be highly predictive of type 1 diabetes development.
