Discriminatory ability of simple OGTT-based beta cell function indices for prediction of prediabetes and type 2 diabetes: the CODAM study

Glucose metabolism status was assessed by 2 h 75 g OGTT at baseline (n = 476, mean age 59.2 years, 38.7% women) and after 7 years of follow-up (n = 416) in the Cohort on Diabetes and Atherosclerosis Maastricht (CODAM) study (1999-2009). Baseline plasma glucose, insulin and C-peptide values during OGTTs were used to calculate 21 simple indices of BCF. Disposition indices (BCF index × Matsuda index), to compensate for the prevailing level of insulin resistance, were calculated for the BCF indices with the best discriminatory abilities. The discriminatory ability of the BCF indices was estimated by the area under the receiver operating characteristics curve (ROC AUC) with an outcome of incident prediabetes (n = 73) or type 2 diabetes (n = 60 and n = 18 cases, respectively, in individuals who were non-diabetic or had normal glucose metabolism at baseline). Results For incident prediabetes (n = 73), all ROC AUCs were less than 70%, whereas for incident type 2 diabetes, I30/I0, CP30/CP0, ?I30/?G30, ?CP30/?G30 (where I, CP and G are the plasma concentrations of insulin, C-peptide and glucose, respectively, at the times indicated), and corrected insulin response at 30 min had ROC AUCs over 70%. In at-baseline non-diabetic individuals, disposition indices ?I30/?G30, ?CP30/?G30 and corrected insulin response at 30 min had ROC AUCs of over 80% for incident type 2 diabetes. Moreover, these BCF disposition indices had significantly better discriminatory abilities for incident type 2 diabetes than the Matsuda index alone. Conclusions/interpretation BCF indices reflecting early-phase insulin secretion have the best ability to discriminate individuals who will develop prediabetes and type 2 diabetes. Of these, ?CP30/?G30, often referred to as the C-peptidogenic index, performed consistently well.