Models for predicting type 1 diabetes in siblings of affected children

Diabetes Care
Samy MrenaMikael Knip

Abstract

To generate predictive models for the assessment of risk of type 1 diabetes and age at diagnosis in siblings of children with newly diagnosed type 1 diabetes. Cox regression analysis was used to assess the risk of progression to type 1 diabetes, and multiple regression analysis was used to estimate the age at disease presentation in 701 siblings of affected children. Sociodemographic, genetic, and immunological variables were included in the analyses. Subanalyses were performed in a group of 77 autoantibody-positive siblings with additional metabolic data. A total of 47 siblings (6.7%) presented with type 1 diabetes during the 15-year observation period. Young age, an increasing number of detectable diabetes-associated autoantibodies at initial sampling and of affected first-degree relatives, and HLA DR-conferred disease susceptibility predicted progression to type 1 diabetes. In the subgroup of 77 autoantibody-positive siblings, young age, HLA DR-conferred susceptibility, an increasing number of autoantibodies, a reduced first-phase insulin response, and decreased insulin sensitivity in relation to first-phase insulin response were associated with increased risk of progression to type 1 diabetes. Age at diagnosis was predicted...Continue Reading

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