ROC curves for assessment of protein panel to discriminate between low and high disposition index measures.

ROC curves to determine the predictive ability of the protein panel (17 proteins associated with the disposition index (p ≤ 0.01)), age, BMI, waist to hip ratio and fasting glucose, for classification of low and high disposition index values of MECHE participants (n = 30). Par scaling was used as a scaling method and random forest method was employed for classification of variables. Using all 21 variables, the best ROC curve was produced with an AUC of 0.918. AUC: area under the curve. Var: variable. CI: Confidence interval. Tertile 1: low beta-cell function Tertile 3: high beta-cell function.