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. 2013 Jul 15;5(1):36.
doi: 10.1186/1758-5996-5-36.

Predictive models for type 2 diabetes onset in middle-aged subjects with the metabolic syndrome

Michal Ozery-Flato  1 , Naama Parush, Tal El-Hay, Zydrūnė Visockienė, Ligita Ryliškytė, Jolita Badarienė, Svetlana Solovjova, Milda Kovaitė, Rokas Navickas, Aleksandras Laucevičius
Affiliations

Predictive models for type 2 diabetes onset in middle-aged subjects with the metabolic syndrome

Michal Ozery-Flato et al. Diabetol Metab Syndr. .

Abstract

Objective: To investigate the predictive value of different biomarkers for the incidence of type 2 diabetes mellitus (T2DM) in subjects with metabolic syndrome.

Methods: A prospective study of 525 non-diabetic, middle-aged Lithuanian men and women with metabolic syndrome but without overt atherosclerotic diseases during a follow-up period of two to four years. We used logistic regression to develop predictive models for incident cases and to investigate the association between various markers and the onset of T2DM.

Results: Fasting plasma glucose (FPG), body mass index (BMI), and glycosylated haemoglobin can be used to predict diabetes onset with a high level of accuracy and each was shown to have a cumulative predictive value. The estimated area under the receiver-operating characteristic curve (AUC) for this combination was 0.92. The oral glucose tolerance test (OGTT) did not show cumulative predictive value. Additionally, progression to diabetes was associated with high values of aortic pulse-wave velocity (aPWV).

Conclusion: T2DM onset in middle-aged metabolic syndrome subjects can be predicted with remarkable accuracy using the combination of FPG, BMI, and HbA1c, and is related to elevated aPWV measurements.

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Figures

Figure 1
Figure 1
Comparison of prediction models. ROC curves of four diabetes onset prediction models: FPG-model, BMI-model, HbA1c-model, and a FPG-BMI-HbA1c-model. All models were adjusted for the gender variable.
See this image and copyright information in PMC

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