Li J, Bergmann A, Reimann M, Bornstein S R, Schwarz P E H
Department of Medicine, Carl Gustav Carus, Technical University Dresden, Dresden, Germany.
Horm Metab Res. 2009 Feb;41(2):98-103. doi: 10.1055/s-0028-1087191. Epub 2008 Oct 29.
The aim of the present study was to evaluate the performance of the Finnish diabetes risk score (FINDRISC) for identifying undiagnosed type 2 diabetes in a German population and to develop a more simplified alternative model. We invited 921 individuals with a family history of the metabolic syndrome in a cross-sectional survey. Of these, 771 subjects completed the FINDRISC questionnaire and underwent an oral glucose tolerance test. The performance of the FINDRISC was assessed using the area under the receiver operating characteristics curve (ROC-AUC). The ROC-AUC of the FINDRISC was 0.81 (0.76-0.87). We detected no difference in diabetes prevalence between individuals with or without a family history of diabetes. Two logistic regression models (continuous- and categorical-model) were developed using the diagnosis of diabetes as the dependent variable, and age, body mass index (BMI), waist circumference, use of blood pressure medication, and history of high blood glucose as independent variables. After stepwise backward elimination of the insignificant variables, the following variables remained: age, BMI, and history of high blood glucose. The ROC-AUCs for the continuous- and categorical-models were 0.88 (0.85-0.92) and 0.86 (0.82-0.90), respectively, and were significantly larger than the ROC-AUC of the FINDRISC. There was no significant difference between the ROC-AUC of fasting plasma glucose and those of the two regression models. The FINDRISC questionnaire can be used to identify undetected diabetes in a German population. The simplified version, the categorical-model, may be a useful alternative for identifying asymptomatic type 2 diabetes.
本研究的目的是评估芬兰糖尿病风险评分(FINDRISC)在德国人群中识别未诊断的2型糖尿病的性能,并开发一种更简化的替代模型。在一项横断面调查中,我们邀请了921名有代谢综合征家族史的个体。其中,771名受试者完成了FINDRISC问卷并接受了口服葡萄糖耐量试验。使用受试者工作特征曲线下面积(ROC-AUC)评估FINDRISC的性能。FINDRISC的ROC-AUC为0.81(0.76-0.87)。我们发现有或没有糖尿病家族史的个体之间糖尿病患病率没有差异。以糖尿病诊断为因变量,年龄、体重指数(BMI)、腰围、血压药物使用情况和高血糖病史为自变量,建立了两个逻辑回归模型(连续模型和分类模型)。在逐步向后剔除无显著意义的变量后,剩下的变量如下:年龄、BMI和高血糖病史。连续模型和分类模型的ROC-AUC分别为0.88(0.85-0.92)和0.86(0.82-0.90),均显著大于FINDRISC的ROC-AUC。空腹血糖的ROC-AUC与两个回归模型的ROC-AUC之间没有显著差异。FINDRISC问卷可用于识别德国人群中未被发现的糖尿病。简化版的分类模型可能是识别无症状2型糖尿病的有用替代方法。