The prediction of type 1 diabetes by multiple autoantibody levels and their incorporation into an autoantibody risk score in relatives of type 1 diabetic patients.
Publication/Presentation Date
9-1-2013
Abstract
OBJECTIVE: We assessed whether a risk score that incorporates levels of multiple islet autoantibodies could enhance the prediction of type 1 diabetes (T1D).
RESEARCH DESIGN AND METHODS: TrialNet Natural History Study participants (n = 784) were tested for three autoantibodies (GADA, IA-2A, and mIAA) at their initial screening. Samples from those positive for at least one autoantibody were subsequently tested for ICA and ZnT8A. An autoantibody risk score (ABRS) was developed from a proportional hazards model that combined autoantibody levels from each autoantibody along with their designations of positivity and negativity.
RESULTS: The ABRS was strongly predictive of T1D (hazard ratio [with 95% CI] 2.72 [2.23-3.31], P < 0.001). Receiver operating characteristic curve areas (with 95% CI) for the ABRS revealed good predictability (0.84 [0.78-0.90] at 2 years, 0.81 [0.74-0.89] at 3 years, P < 0.001 for both). The composite of levels from the five autoantibodies was predictive of T1D before and after an adjustment for the positivity or negativity of autoantibodies (P < 0.001). The findings were almost identical when ICA was excluded from the risk score model. The combination of the ABRS and the previously validated Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) predicted T1D more accurately (0.93 [0.88-0.98] at 2 years, 0.91 [0.83-0.99] at 3 years) than either the DPTRS or the ABRS alone (P ≤ 0.01 for all comparisons).
CONCLUSIONS: These findings show the importance of considering autoantibody levels in assessing the risk of T1D. Moreover, levels of multiple autoantibodies can be incorporated into an ABRS that accurately predicts T1D.
Volume
36
Issue
9
First Page
2615
Last Page
2620
ISSN
1935-5548
Published In/Presented At
Sosenko, J. M., Skyler, J. S., Palmer, J. P., Krischer, J. P., Yu, L., Mahon, J., Beam, C. A., Boulware, D. C., Rafkin, L., Schatz, D., Eisenbarth, G., Type 1 Diabetes TrialNet Study Group, & Diabetes Prevention Trial-Type 1 Study Group (2013). The prediction of type 1 diabetes by multiple autoantibody levels and their incorporation into an autoantibody risk score in relatives of type 1 diabetic patients. Diabetes care, 36(9), 2615–2620. https://doi.org/10.2337/dc13-0425
Disciplines
Medicine and Health Sciences
PubMedID
23818528
Department(s)
Department of Medicine
Document Type
Article