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Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children
AIMS/HYPOTHESIS: The aim of this study was to explore the utility of islet autoantibody (IAb) levels for the prediction of type 1 diabetes in autoantibody-positive children. METHODS: Prospective cohort studies in Finland, Germany, Sweden and the USA followed 24,662 children at increased genetic or f...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9729160/ https://www.ncbi.nlm.nih.gov/pubmed/36195673 http://dx.doi.org/10.1007/s00125-022-05799-y |
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author | Ng, Kenney Anand, Vibha Stavropoulos, Harry Veijola, Riitta Toppari, Jorma Maziarz, Marlena Lundgren, Markus Waugh, Kathy Frohnert, Brigitte I. Martin, Frank Lou, Olivia Hagopian, William Achenbach, Peter |
author_facet | Ng, Kenney Anand, Vibha Stavropoulos, Harry Veijola, Riitta Toppari, Jorma Maziarz, Marlena Lundgren, Markus Waugh, Kathy Frohnert, Brigitte I. Martin, Frank Lou, Olivia Hagopian, William Achenbach, Peter |
author_sort | Ng, Kenney |
collection | PubMed |
description | AIMS/HYPOTHESIS: The aim of this study was to explore the utility of islet autoantibody (IAb) levels for the prediction of type 1 diabetes in autoantibody-positive children. METHODS: Prospective cohort studies in Finland, Germany, Sweden and the USA followed 24,662 children at increased genetic or familial risk of developing islet autoimmunity and diabetes. For the 1403 who developed IAbs (523 of whom developed diabetes), levels of autoantibodies against insulin (IAA), glutamic acid decarboxylase (GADA) and insulinoma-associated antigen-2 (IA-2A) were harmonised for analysis. Diabetes prediction models using multivariate logistic regression with inverse probability censored weighting (IPCW) were trained using 10-fold cross-validation. Discriminative power for disease was estimated using the IPCW concordance index (C index) with 95% CI estimated via bootstrap. RESULTS: A baseline model with covariates for data source, sex, diabetes family history, HLA risk group and age at seroconversion with a 10-year follow-up period yielded a C index of 0.61 (95% CI 0.58, 0.63). The performance improved after adding the IAb positivity status for IAA, GADA and IA-2A at seroconversion: C index 0.72 (95% CI 0.71, 0.74). Using the IAb levels instead of positivity indicators resulted in even better performance: C index 0.76 (95% CI 0.74, 0.77). The predictive power was maintained when using the IAb levels alone: C index 0.76 (95% CI 0.75, 0.76). The prediction was better for shorter follow-up periods, with a C index of 0.82 (95% CI 0.81, 0.83) at 2 years, and remained reasonable for longer follow-up periods, with a C index of 0.76 (95% CI 0.75, 0.76) at 11 years. Inclusion of the results of a third IAb test added to the predictive power, and a suitable interval between seroconversion and the third test was approximately 1.5 years, with a C index of 0.78 (95% CI 0.77, 0.78) at 10 years follow-up. CONCLUSIONS/INTERPRETATION: Consideration of quantitative patterns of IAb levels improved the predictive power for type 1 diabetes in IAb-positive children beyond qualitative IAb positivity status. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-022-05799-y. |
format | Online Article Text |
id | pubmed-9729160 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-97291602022-12-09 Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children Ng, Kenney Anand, Vibha Stavropoulos, Harry Veijola, Riitta Toppari, Jorma Maziarz, Marlena Lundgren, Markus Waugh, Kathy Frohnert, Brigitte I. Martin, Frank Lou, Olivia Hagopian, William Achenbach, Peter Diabetologia Article AIMS/HYPOTHESIS: The aim of this study was to explore the utility of islet autoantibody (IAb) levels for the prediction of type 1 diabetes in autoantibody-positive children. METHODS: Prospective cohort studies in Finland, Germany, Sweden and the USA followed 24,662 children at increased genetic or familial risk of developing islet autoimmunity and diabetes. For the 1403 who developed IAbs (523 of whom developed diabetes), levels of autoantibodies against insulin (IAA), glutamic acid decarboxylase (GADA) and insulinoma-associated antigen-2 (IA-2A) were harmonised for analysis. Diabetes prediction models using multivariate logistic regression with inverse probability censored weighting (IPCW) were trained using 10-fold cross-validation. Discriminative power for disease was estimated using the IPCW concordance index (C index) with 95% CI estimated via bootstrap. RESULTS: A baseline model with covariates for data source, sex, diabetes family history, HLA risk group and age at seroconversion with a 10-year follow-up period yielded a C index of 0.61 (95% CI 0.58, 0.63). The performance improved after adding the IAb positivity status for IAA, GADA and IA-2A at seroconversion: C index 0.72 (95% CI 0.71, 0.74). Using the IAb levels instead of positivity indicators resulted in even better performance: C index 0.76 (95% CI 0.74, 0.77). The predictive power was maintained when using the IAb levels alone: C index 0.76 (95% CI 0.75, 0.76). The prediction was better for shorter follow-up periods, with a C index of 0.82 (95% CI 0.81, 0.83) at 2 years, and remained reasonable for longer follow-up periods, with a C index of 0.76 (95% CI 0.75, 0.76) at 11 years. Inclusion of the results of a third IAb test added to the predictive power, and a suitable interval between seroconversion and the third test was approximately 1.5 years, with a C index of 0.78 (95% CI 0.77, 0.78) at 10 years follow-up. CONCLUSIONS/INTERPRETATION: Consideration of quantitative patterns of IAb levels improved the predictive power for type 1 diabetes in IAb-positive children beyond qualitative IAb positivity status. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-022-05799-y. Springer Berlin Heidelberg 2022-10-05 2023 /pmc/articles/PMC9729160/ /pubmed/36195673 http://dx.doi.org/10.1007/s00125-022-05799-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Ng, Kenney Anand, Vibha Stavropoulos, Harry Veijola, Riitta Toppari, Jorma Maziarz, Marlena Lundgren, Markus Waugh, Kathy Frohnert, Brigitte I. Martin, Frank Lou, Olivia Hagopian, William Achenbach, Peter Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children |
title | Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children |
title_full | Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children |
title_fullStr | Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children |
title_full_unstemmed | Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children |
title_short | Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children |
title_sort | quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9729160/ https://www.ncbi.nlm.nih.gov/pubmed/36195673 http://dx.doi.org/10.1007/s00125-022-05799-y |
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