Background: Given the increasing worldwide incidence of diabetes, methods to assess diabetes risk which would identify
those at highest risk are needed. We compared two risk-stratification approaches for incident type 2 diabetes mellitus
(T2DM); factors of metabolic syndrome (MetS) and a previously developed diabetes risk score, PreDxH Diabetes Risk Score
(DRS). DRS assesses 5 yr risk of incident T2DM based on the measurement of 7 biomarkers in fasting blood.
Methodology/Principal Findings: DRS was evaluated in baseline serum samples from 4,128 non-diabetic subjects in
the Inter99 cohort (Danes aged 30–60) for whom diabetes outcomes at 5 years were known. Subjects were classified
as having MetS based on the presence of at least 3 MetS risk factors in baseline clinical data. The sensitivity and false
positive rate for predicting diabetes using MetS was compared to DRS. When the sensitivity was fixed to match
MetS, DRS had a significantly lower false positive rate. Similarly, when the false positive rate was fixed to match
MetS, DRS had a significantly higher specificity. In further analyses, subjects were classified by presence of 0–2, 3 or
4–5 risk factors with matching proportions of subjects distributed among three DRS groups. Comparison between
the two risk stratification schemes, MetS risk factors and DRS, were evaluated using Net Reclassification
Improvement (NRI). Comparing risk stratification by DRS to MetS factors in the total population, the NRI was 0.146
(p = 0.008) demonstrating DRS provides significantly improved stratification. Additionally, the relative risk of T2DM
differed by 15 fold between the low and high DRS risk groups, but only 8-fold between the low and high risk MetS
groups.
Conclusions/Significance: DRS provides a more accurate assessment of risk for diabetes than MetS. This improved
performance may allow clinicians to focus preventive strategies on those most in need of urgent intervention.