METHODS: Seventy-six participants developed diabetes over 5.3 years (median). All five
biomarkers significantly improved the log-likelihood of diabetes in a clinical diabetes prediction (
CDP) model including age, sex, family history of diabetes, smoking, physical activity,
hypertension, waist circumference, fasting
glucose and dyslipidaemia. In ROC curve analysis, "
adiponectin + TNF-α R2" improved the area under ROC curve (AUC) of the
CDP model from 0.802 to 0.830 (P = 0.03), rendering its performance comparable to the "
CDP + 2-hour post-OGTT
glucose" model (AUC = 0.852, P = 0.30). A
biomarker risk score, derived from the number of
biomarkers predictive of diabetes (low
adiponectin, high TNF-α R2), had similar performance when added to the
CDP model (AUC = 0.829 [95% CI: 0.808-0.849]).
CONCLUSIONS: