Department of Internal Medicine and Medical Specialties (DIMIS), University of Palermo, Palermo, Italy.
Acta Diabetol. 2012 Apr;49(2):145-51. doi: 10.1007/s00592-011-0305-x. Epub 2011 Jun 23.
A novel algorithm to predict incident type 2 diabetes mellitus (iT2DM) is presented considering data from a 20-year prospective study in a Southern Italy population. Eight hundred and fifty-eight out of 1,351 subjects (24-85 years range of age) were selected. Incident type 2 diabetes was diagnosed in 103 patients in a 20-year follow-up. The Finnish Diabetes Risk Score (FINDRISC) and the Framingham Offspring Study simple clinical model (FOS) have been used as reference algorithms. Two custom algorithms have been created using Cox parametric hazard models followed by PROBIT analyses: the first one (VHSRISK) includes all the study subjects and the second one (VHS95RISK) evaluates separately subjects with baseline fasting blood glucose (FBG) above/below 5.2 mmol/L (95 mg/dL). The 44 iT2DM cases below 5.2 mmol/L of baseline FBG were predicted by high LDL cholesterol, metabolic syndrome (ATPIII criteria), BMI > 30 kg/m(2), and high factor VII activity. The 59 cases above the FBG threshold were predicted by FBG classes, hypertension, and age. ROC areas for iT2DM prediction were: FINDRISC = 0.759, FOS = 0.762, VHSRISK = 0.789, and VHS95RISK = 0.803. In a Mediterranean population, the use of a custom generated algorithm evaluating separately low/high FBG subjects improves the prediction of iT2DM in subjects classified at lower risk by common estimation algorithms.
提出了一种预测 2 型糖尿病(iT2DM)发病的新算法,该算法考虑了意大利南部一项为期 20 年的前瞻性研究的数据。从 1351 名受试者中选择了 858 名(年龄 24-85 岁)。在 20 年的随访中,103 名患者被诊断为 2 型糖尿病。芬兰糖尿病风险评分(FINDRISC)和弗雷明汉后代研究简单临床模型(FOS)被用作参考算法。使用 Cox 参数风险模型和 PROBIT 分析创建了两个自定义算法:第一个(VHSRISK)包括所有研究对象,第二个(VHS95RISK)分别评估基线空腹血糖(FBG)高于/低于 5.2mmol/L(95mg/dL)的对象。通过高 LDL 胆固醇、代谢综合征(ATPIII 标准)、BMI>30kg/m(2)和高因子 VII 活性预测了 44 例基线 FBG 低于 5.2mmol/L 的 iT2DM 病例。59 例高于 FBG 阈值的病例由 FBG 分类、高血压和年龄预测。iT2DM 预测的 ROC 面积分别为:FINDRISC=0.759、FOS=0.762、VHSRISK=0.789 和 VHS95RISK=0.803。在一个地中海人群中,使用单独评估低/高 FBG 受试者的自定义生成算法可提高对低风险人群中常见估计算法分类的 iT2DM 的预测。