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Discriminatory value of alanine aminotransferase for diabetes prediction: the Insulin Resistance Atherosclerosis Study
Author(s) -
Lorenzo C.,
Hanley A. J.,
Rewers M. J.,
Haffner S. M.
Publication year - 2016
Publication title -
diabetic medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.474
H-Index - 145
eISSN - 1464-5491
pISSN - 0742-3071
DOI - 10.1111/dme.12835
Subject(s) - medicine , insulin resistance , diabetes mellitus , alanine aminotransferase , family history , endocrinology , type 2 diabetes , alanine transaminase , population , gastroenterology , environmental health
Aims To examine the incremental usefulness of adding alanine aminotransferase to established risk factors for predicting future diabetes. Methods The study population of the Insulin Resistance Atherosclerosis Study included 724 people aged 40–69 years. We excluded people who had excessive alcohol intake or were treated with lipid‐lowering agents. Incident diabetes was assessed after a mean follow‐up period of 5.2 years. Results Alanine aminotransferase had a non‐linear relationship with incident diabetes (Wald chi‐squared test, P < 0.001; P for linearity = 0.005) independent of demographic variables, family history of diabetes, BMI and fasting glucose; therefore, we used Youden's J statistic to dichotomize alanine aminotransferase [threshold ≥ 0.43 μkat/L ( ≥ 26 IU /l)]. Dichotomized alanine aminotransferase increased the area under the receiver‐operating characteristic curve (0.805 vs. 0.823; P = 0.007) of a model that included demographic variables, family history of diabetes, BMI and fasting glucose as independent variables. The net reclassification improvement was 9.6% (95% CI 1.8–17.4; P = 0.016), and the integrated discrimination improvement was 0.031 (95% CI 0.011–0.050; P = 0.002). Dichotomized alanine aminotransferase reclassified a net of 9.6% of individuals more appropriately. Conclusions Alanine aminotransferase may be useful for classifying individuals who are at risk of future diabetes after accounting for the effect of other risk factors, including family history, adiposity and plasma glucose.