作者
Laura M Jacobsen, Helena E Larsson, Roy N Tamura, Kendra Vehik, Joanna Clasen, Jay Sosenko, William A Hagopian, Jin‐Xiong She, Andrea K Steck, Marian Rewers, Olli Simell, Jorma Toppari, Riitta Veijola, Anette G Ziegler, Jeffrey P Krischer, Beena Akolkar, Michael J Haller, TEDDY Study Group
发表日期
2019/5
期刊
Pediatric diabetes
卷号
20
期号
3
页码范围
263-270
出版商
John Wiley & Sons A/S
简介
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 presence of insulinoma‐associated‐2 autoantibodies (IA‐2A).
Results
A total of 363 subjects had at least one autoantibody at age 3 …
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LM Jacobsen, HE Larsson, RN Tamura, K Vehik… - Pediatric diabetes, 2019