Development and recalibration of a multivariable type 1 diabetes prediction model for type 1 diabetes across multiple screening studies.

ABSTRACT:

Background

Accurate type 1 diabetes prediction is important to facilitate screening for pre-clinical type 1 diabetes to enable potential early disease-modifying interventions and to reduce the risk of severe presentation with diabetic ketoacidosis. We aimed to assess the generalisability of a prediction model developed in children followed from birth. Additionally, we sought to create an application for easy calculation and visualisation of individualised risk prediction.

Methods

We developed and internally validated a stratified prediction model combining a genetic risk score, age, islet autoantibodies, and family history using data from children followed since birth by The Environmental Determinants of Diabetes in the Young (TEDDY) study. We tested the validity of the mode

SUBMITTER: Templeman EL 

PROVIDER: S-EPMC12281708 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature