Machine Learning and Data Mining group, IBM Research - Haifa, Mount Carmel, Haifa 3498825, Israel.
Diabetol Metab Syndr. 2013 Jul 15;5(1):36. doi: 10.1186/1758-5996-5-36.
To investigate the predictive value of different biomarkers for the incidence of type 2 diabetes mellitus (T2DM) in subjects with metabolic syndrome.
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.
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).
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.
探讨代谢综合征患者不同生物标志物对 2 型糖尿病（T2DM）发病的预测价值。
对 525 名无糖尿病的中年立陶宛男女进行前瞻性研究，这些人患有代谢综合征，但在两年至四年的随访期间没有明显的动脉粥样硬化疾病。我们使用逻辑回归来为新发病例建立预测模型，并研究各种标志物与 T2DM 发病之间的关系。
空腹血糖（FPG）、体重指数（BMI）和糖化血红蛋白可以高度准确地预测糖尿病的发病，并且每个标志物都显示出累积的预测价值。这种组合的估计接收者操作特征曲线下面积（AUC）为 0.92。口服葡萄糖耐量试验（OGTT）没有显示出累积的预测价值。此外，向糖尿病的进展与主动脉脉搏波速度（aPWV）的高值相关。
使用 FPG、BMI 和 HbA1c 的组合，可以非常准确地预测中年代谢综合征患者 T2DM 的发病，并且与升高的 aPWV 测量值相关。
