Literature DB >> 21947790

Prognostic value of haemoglobin A1c and fasting plasma glucose for incident diabetes and implications for screening.

Ben Schöttker1, Elke Raum, Dietrich Rothenbacher, Heiko Müller, Hermann Brenner.   

Abstract

The aim of this analysis is to compare screening strategies with haemoglobin A(1c) (HbA(1c)), fasting plasma glucose (FPG) or combined measures in the identification of individuals at high risk for diabetes. Applying American Diabetes Association thresholds for FPG and HbA(1c) screening, 6,803 subjects free of diabetes were classified as non-diabetic, pre-diabetic and possibly diabetic by FPG (<100, 100-125 and >125 mg/dl) and HbA(1c) (<5.7, 5.7-6.4 and >6.4%). Hazard ratios, sensitivity and specificity were estimated for individuals with pre-diabetes with respect to incident diabetes in the following 5 years. Areas under the receiver operating characteristic curves (AUC) were estimated for levels of FPG ≤ 125 mg/dl and HbA(1c) ≤ 6.4% in diabetes prediction. Although FPG and HbA(1c) screenings poorly agreed in classifying individuals as pre-diabetic, hazard ratios [95% confidence interval] for incident diabetes were similarly increased in univariate models in the two pre-diabetic groups: FPG 100-125 mg/dl, 4.72 [3.69; 6.05]; HbA(1c) 5.7-6.4%, 3.97 [3.05; 5.23]. HbA(1c) and FPG had comparable AUCs (FPG, 0.732; HbA(1c), 0.725) and consequently similar 5-year sensitivities and specificities for their pre-diabetes definitions (when the lower cut-off for HbA(1c)-defined pre-diabetes was increased to a level between 5.8 and 5.9%). Combining HbA(1c) and FPG increased the AUC to 0.778, and a further increase to 0.817 was seen with additional inclusion of conventional risk factors. FPG and HbA(1c) have comparable (yet insufficient) abilities in identifying individuals at high risk for diabetes. Effectiveness of a diabetes screening program could be improved by a risk score including FPG and HbA(1c).

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Year:  2011        PMID: 21947790     DOI: 10.1007/s10654-011-9619-9

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  34 in total

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10.  Common variants at 10 genomic loci influence hemoglobin A₁(C) levels via glycemic and nonglycemic pathways.

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Journal:  Diabetes       Date:  2010-09-21       Impact factor: 9.461

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2.  The Rotterdam Study: 2014 objectives and design update.

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Journal:  Eur J Epidemiol       Date:  2013-11-21       Impact factor: 8.082

3.  A novel test for IGT utilizing metabolite markers of glucose tolerance.

Authors:  Jeff Cobb; Andrea Eckhart; Regis Perichon; Jacob Wulff; Matthew Mitchell; Klaus-Peter Adam; Robert Wolfert; Eric Button; Kay Lawton; Robert Elverson; Bernadette Carr; Margaret Sinnott; Ele Ferrannini
Journal:  J Diabetes Sci Technol       Date:  2014-09-26

Review 4.  Metformin use among individuals at risk for type 2 diabetes.

Authors:  Lewis H Kuller
Journal:  Curr Diab Rep       Date:  2012-06       Impact factor: 4.810

5.  Serum 25-hydroxyvitamin D levels and incident diabetes mellitus type 2: a competing risk analysis in a large population-based cohort of older adults.

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Journal:  Eur J Epidemiol       Date:  2013-01-26       Impact factor: 8.082

6.  Fasting plasma glucose and HbA1c in cardiovascular risk prediction: a sex-specific comparison in individuals without diabetes mellitus.

Authors:  B Schöttker; H Müller; D Rothenbacher; H Brenner
Journal:  Diabetologia       Date:  2012-09-19       Impact factor: 10.122

Review 7.  Type 2 Diabetes Prevention: Implications of Hemoglobin A1c Genetics.

Authors:  Aaron Leong; James B Meigs
Journal:  Rev Diabet Stud       Date:  2016-02-10

8.  The Generation R Study: design and cohort update 2012.

Authors:  Vincent W V Jaddoe; Cornelia M van Duijn; Oscar H Franco; Albert J van der Heijden; Marinus H van Iizendoorn; Johan C de Jongste; Aad van der Lugt; Johan P Mackenbach; Henriëtte A Moll; Hein Raat; Fernando Rivadeneira; Eric A P Steegers; Henning Tiemeier; Andre G Uitterlinden; Frank C Verhulst; Albert Hofman
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9.  Development of a new scoring system for predicting the 5 year incidence of type 2 diabetes in Japan: the Toranomon Hospital Health Management Center Study 6 (TOPICS 6).

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