Development of a Type 2 Diabetes Risk Model From a Panel of Serum Biomarkers From the Inter99 Cohort
2009; American Diabetes Association; Volume: 32; Issue: 7 Linguagem: Inglês
10.2337/dc08-1935
ISSN1935-5548
AutoresJanice A. Kolberg, Torben Jørgensen, Robert Gerwien, Sarah Hamren, Michael P. McKenna, Edward J. Moler, Michael W. Rowe, Mickey S. Urdea, Xiaomei Xu, Torben Hansen, Oluf Pedersen, Knut Borch‐Johnsen,
Tópico(s)Metabolism, Diabetes, and Cancer
ResumoThe purpose of this study was to develop a model for assessing the 5-year risk of developing type 2 diabetes from a panel of 64 circulating candidate biomarkers.Subjects were selected from the Inter99 cohort, a longitudinal population-based study of approximately 6,600 Danes in a nested case-control design with the primary outcome of 5-year conversion to type 2 diabetes. Nondiabetic subjects, aged >or=39 years, with BMI >or=25 kg/m(2) at baseline were selected. Baseline fasting serum samples from 160 individuals who developed type 2 diabetes and from 472 who did not were tested. An ultrasensitive immunoassay was used to measure of 58 candidate biomarkers in multiple diabetes-associated pathways, along with six routine clinical variables. Statistical learning methods and permutation testing were used to select the most informative biomarkers. Risk model performance was estimated using a validated bootstrap bias-correction procedure.A model using six biomarkers (adiponectin, C-reactive protein, ferritin, interleukin-2 receptor A, glucose, and insulin) was developed for assessing an individual's 5-year risk of developing type 2 diabetes. This model has a bootstrap-estimated area under the curve of 0.76, which is greater than that for A1C, fasting plasma glucose, fasting serum insulin, BMI, sex-adjusted waist circumference, a model using fasting glucose and insulin, and a noninvasive clinical model.A model incorporating six circulating biomarkers provides an objective and quantitative estimate of the 5-year risk of developing type 2 diabetes, performs better than single risk indicators and a noninvasive clinical model, and provides better stratification than fasting plasma glucose alone.
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