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Liver function tests and risk prediction of incident type 2 diabetes: evaluation in two independent cohorts

Abbasi, A., Bakker, S. J. L., Corpeleijn, E., van der A, D. L., Gansevoort, R. T., Gans, R. O. B., Peelen, L. M., van der Schouw, Y. T., Stolk, R. P., Navis, G., Spijkerman, A. M. W. & Beulens, J. W. J., 17-Dec-2012, In : PLoS ONE. 7, 12, 8 p., e51496.

Research output: Contribution to journalArticleAcademicpeer-review

Background: Liver function tests might predict the risk of type 2 diabetes. An independent study evaluating utility of these markers compared with an existing prediction model is yet lacking.

Methods and Findings: We performed a case-cohort study, including random subcohort (6.5%) from 38,379 participants with 924 incident diabetes cases (the Dutch contribution to the European Prospective Investigation Into Cancer and Nutrition, EPIC-NL, the Netherlands), and another population-based cohort study including 7,952 participants with 503 incident cases (the Prevention of Renal and Vascular End-stage Disease, PREVEND, Groningen, the Netherlands). We examined predictive value of combination of the Liver function tests (gamma-glutamyltransferase, alanine aminotransferase, aspartate aminotransferase and albumin) above validated models for 7.5-year risk of diabetes (the Cooperative Health Research in the Region of Augsburg, the KORA study). Basic model includes age, sex, BMI, smoking, hypertension and parental diabetes. Clinical models additionally include glucose and uric acid (model1) and HbA1c (model2). In both studies, addition of Liver function tests to the basic model improved the prediction (C-statistic by similar to 0.020; NRI by similar to 9.0%; P

Conclusions: Liver function tests modestly improve prediction for medium-term risk of incident diabetes above basic and extended clinical prediction models, only if no HbA1c is incorporated. If data on HbA1c are available, Liver function tests have little incremental predictive value, although a small benefit may be present in men.

Original languageEnglish
Article numbere51496
Number of pages8
JournalPLoS ONE
Volume7
Issue number12
Publication statusPublished - 17-Dec-2012

    Keywords

  • GAMMA-GLUTAMYL-TRANSFERASE, CARDIOVASCULAR-DISEASE, METABOLIC SYNDROME, OLDER MEN, EPIC-NL, MODELS, BIOMARKERS, WOMEN, PERSPECTIVE, VALIDATION

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