Predicting progression to type 1 diabetes from ages 3 to 6 in islet autoantibody positive TEDDY children.

ABSTRACT:

Objective

The capacity to precisely predict progression to type 1 diabetes (T1D) in young children over a short time span is an unmet need. We sought to develop a risk algorithm to predict progression in children with high-risk human leukocyte antigen (HLA) genes followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study.

Methods

Logistic regression and 4-fold cross-validation examined 38 candidate predictors of risk from clinical, immunologic, metabolic, and genetic data. TEDDY subjects with at least one persistent, confirmed autoantibody at age 3 were analyzed with progression to T1D by age 6 serving as the primary endpoint. The logistic regression prediction model was compared to two non-statistical predictors, multiple autoantibody status, and pres

SUBMITTER: Jacobsen LM 

PROVIDER: S-EPMC6456374 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature