C Lorenzo1, A J Hanley2,3, M J Rewers4, S M Haffner1,5. 1. Department of Medicine, University of Texas Health Science Center, San Antonio, TX, USA. 2. Departments of Medicine and Nutritional Sciences and Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada. 3. Leadership Sinai Centre for Diabetes, Mt. Sinai Hospital, Toronto, Ontario, Canada. 4. Barbara Davis Center for Childhood Diabetes, University Colorado School of Medicine, Aurora, CO, USA. 5. University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Abstract
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.
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.
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