Literature DB >> 22058089

Validation of a multi-marker model for the prediction of incident type 2 diabetes mellitus: combined results of the Inter99 and Botnia studies.

Valeria Lyssenko1, Torben Jørgensen, Robert W Gerwien, Torben Hansen, Michael W Rowe, Michael P McKenna, Janice Kolberg, Oluf Pedersen, Knut Borch-Johnsen, Leif Groop.   

Abstract

PURPOSE: To assess performance of a biomarker-based score that predicts the five-year risk of diabetes (Diabetes Risk Score, DRS) in an independent cohort that included 15-year follow-up.
METHOD: DRS was developed on the Inter99 cohort, and validated on the Botnia cohort. Performance was benchmarked against other risk-assessment tools comparing calibration, time to event analysis, and net reclassification.
RESULTS: The area under the receiver-operating characteristic curve (AUC) was 0.84 for the Inter99 cohort and 0.78 for the Botnia cohort. In the Botnia cohort, DRS provided better discrimination than fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance, oral glucose tolerance test or risk scores derived from Framingham or San Antonio Study cohorts. Overall reclassification with DRS was significantly better than using FPG and glucose tolerance status (p < 0.0001). In time to event analysis, rates of conversion to diabetes in low, moderate, and high DRS groups were significantly different (p < 0.001).
CONCLUSION: This study validates DRS performance in an independent population, and provides a more accurate assessment of T2DM risk than other methods.

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Year:  2011        PMID: 22058089     DOI: 10.1177/1479164111424762

Source DB:  PubMed          Journal:  Diab Vasc Dis Res        ISSN: 1479-1641            Impact factor:   3.291


  7 in total

Review 1.  The potential of novel biomarkers to improve risk prediction of type 2 diabetes.

Authors:  Christian Herder; Bernd Kowall; Adam G Tabak; Wolfgang Rathmann
Journal:  Diabetologia       Date:  2014-01       Impact factor: 10.122

2.  Biomarker models as surrogates for the disposition index in the Insulin Resistance Atherosclerosis Study.

Authors:  S M Watkins; M W Rowe; J A Kolberg; L E Wagenknecht; R N Bergman
Journal:  Diabet Med       Date:  2012-11       Impact factor: 4.359

3.  Performance of a multi-marker diabetes risk score in the Insulin Resistance Atherosclerosis Study (IRAS), a multi-ethnic US cohort.

Authors:  Michael W Rowe; Richard N Bergman; Lynne E Wagenknecht; Janice A Kolberg
Journal:  Diabetes Metab Res Rev       Date:  2012-09       Impact factor: 4.876

Review 4.  The potential use of DNA methylation biomarkers to identify risk and progression of type 2 diabetes.

Authors:  Linn Gillberg; Charlotte Ling
Journal:  Front Endocrinol (Lausanne)       Date:  2015-03-30       Impact factor: 5.555

5.  An exploratory retrospective assessment of a quantitative measure of diabetes risk: medical management and patient impact in a primary care setting.

Authors:  Maureen R Courtney; Edward J Moler; John A Osborne; Geoff Whitney; Scott E Conard
Journal:  Diabetes Metab Syndr Obes       Date:  2015-09-18       Impact factor: 3.168

6.  Poorly controlled type 2 diabetes is accompanied by significant morphological and ultrastructural changes in both erythrocytes and in thrombin-generated fibrin: implications for diagnostics.

Authors:  Etheresia Pretorius; Janette Bester; Natasha Vermeulen; Sajee Alummoottil; Prashilla Soma; Antoinette V Buys; Douglas B Kell
Journal:  Cardiovasc Diabetol       Date:  2015-03-08       Impact factor: 9.951

7.  Plasma adiponectin levels and type 2 diabetes risk: a nested case-control study in a Chinese population and an updated meta-analysis.

Authors:  Yeli Wang; Rui-Wei Meng; Setor K Kunutsor; Rajiv Chowdhury; Jian-Min Yuan; Woon-Puay Koh; An Pan
Journal:  Sci Rep       Date:  2018-01-10       Impact factor: 4.379

  7 in total

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