Dysglycemia to Type 1 Diabetes: Evaluating the Association of Risk Factors with Disease Progression
CPS ePoster Library. Agarwal T. 06/01/17; 176593; 32
Tanvi Agarwal
Tanvi Agarwal
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Background: Type 1 diabetes (T1D) has long been recognized as an autoimmune disorder, likely stimulated by environmental factors and immune dysregulation in individuals with an increased genetic susceptibility. Accelerated beta cell function loss precedes disease detection, indicating a need to identify high-risk individuals prior to diagnosis. While parameters such as number of autoantibodies against beta cells, age, body-mass index, and measures of insulin and glucose response have been shown to be predictive of T1D, prediction of the timing of diagnosis remains challenging.

Objectives: To evaluate the association between risk factors for T1D and the rate of progression from an abnormal oral glucose tolerance test (OGTT) to the development of T1D.

Methods: Data from a prospective cohort study (n = 1127), Type 1 Diabetes TrialNet, was employed to perform a multivariate Cox regression using a forward stepwise approach to identify variables that increased risk of T1D. Cut points that defined high and low risk sub-populations based on identified variables of interest were selected through recursive partitioning analysis. C-statistics and life tables were then used to explore model discrimination and time from first abnormal OGTT to T1D.

Results: While there was some variability between study sub-groups (all ages, < 18 years, and > 18 years), ICA or ICA 512 positivity, DPTRS (Diabetes Prevention Trial-Type 1 Risk Score), number of antibodies, Index60 (metabolic index), and HbA1c were identified as being significant T1D risk factors. In the all ages group, DPTRS < 7 and <= 2 antibodies identified a lower risk population with slower progression to T1D compared to those with DPTRS > 7 and >= 3 antibodies (model C-statistic = 0.63). In the < 18 years group, DPTRS > 8 and HbA1c > 5.4 defined a faster progressing population (model C-statistic = 0.69). In the > 18 years group, ICA positivity and Index60 >= 1 identified a population at higher risk of progression to T1D (model C-statistic = 0.66).

Conclusion: Several T1D risk factors predict the rate of progression from dysglycemia to T1D onset. These may be used to identify individuals at a higher risk for disease development and may help inform efforts aimed at T1D prevention.

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