Predicting Islet Cell Autoimmunity and Type 1 Diabetes : An 8-Year TEDDY Study Progress Report
Krischer, Jeffrey P ; Liu, Xiang ; Vehik, Kendra LU ; Akolkar, Beena ; Hagopian, William A ; Rewers, Marian J ; She, Jin-Xiong ; Toppari, Jorma ; Ziegler, Anette-G and Lernmark, Åke LU
(2019)
In Diabetes Care
42(6).
p.1051-1060
- Abstract
OBJECTIVE: Assessment of the predictive power of The Environmental Determinants of Diabetes in the Young (TEDDY)-identified risk factors for islet autoimmunity (IA), the type of autoantibody appearing first, and type 1 diabetes (T1D).
RESEARCH DESIGN AND METHODS: A total of 7,777 children were followed from birth to a median of 9.1 years of age for the development of islet autoantibodies and progression to T1D. Time-dependent sensitivity, specificity, and receiver operating characteristic (ROC) curves were calculated to provide estimates of their individual and collective ability to predict IA and T1D.
RESULTS: HLA genotype (DR3/4 vs. others) was the best predictor for IA (Youden's index J = 0.117) and single nucleotide... (More)
OBJECTIVE: Assessment of the predictive power of The Environmental Determinants of Diabetes in the Young (TEDDY)-identified risk factors for islet autoimmunity (IA), the type of autoantibody appearing first, and type 1 diabetes (T1D).
RESEARCH DESIGN AND METHODS: A total of 7,777 children were followed from birth to a median of 9.1 years of age for the development of islet autoantibodies and progression to T1D. Time-dependent sensitivity, specificity, and receiver operating characteristic (ROC) curves were calculated to provide estimates of their individual and collective ability to predict IA and T1D.
RESULTS: HLA genotype (DR3/4 vs. others) was the best predictor for IA (Youden's index J = 0.117) and single nucleotide polymorphism rs2476601, in PTPN22, was the best predictor for insulin autoantibodies (IAA) appearing first (IAA-first) (J = 0.123). For GAD autoantibodies (GADA)-first, weight at 1 year was the best predictor (J = 0.114). In a multivariate model, the area under the ROC curve (AUC) was 0.678 (95% CI 0.655, 0.701), 0.707 (95% CI 0.676, 0.739), and 0.686 (95% CI 0.651, 0.722) for IA, IAA-first, and GADA-first, respectively, at 6 years. The AUC of the prediction model for T1D at 3 years after the appearance of multiple autoantibodies reached 0.706 (95% CI 0.649, 0.762).
CONCLUSIONS: Prediction modeling statistics are valuable tools, when applied in a time-until-event setting, to evaluate the ability of risk factors to discriminate between those who will and those who will not get disease. Although significantly associated with IA and T1D, the TEDDY risk factors individually contribute little to prediction. However, in combination, these factors increased IA and T1D prediction substantially.
(Less)
- author
- Krischer, Jeffrey P
; Liu, Xiang
; Vehik, Kendra
LU
; Akolkar, Beena
; Hagopian, William A
; Rewers, Marian J
; She, Jin-Xiong
; Toppari, Jorma
; Ziegler, Anette-G
and Lernmark, Åke
LU
- contributor
- Agardh, Daniel
LU
; Andrén Aronsson, Carin
LU
; Ask, Maria
LU
; Bremer, Jenny
LU
; Ericson-Hallström, Emelie
LU
; Björne Fors, Annika
LU
; Fransson, Lina
LU
; Gard, Thomas
LU
; Bennet, Rasmus
LU
; Hyberg, Susanne
; Jisser, Hanna
LU
; Johansen, Fredrik
LU
; Jónsdóttir, Berglind
LU
; JOVIC, SILVIJA
LU
; Elding Larsson, Helena
LU
; Lindström, Marielle
LU
; Lundgren, Markus
LU
; Månsson Martinez, Maria
LU
; Markan, Maria
LU
; Melin, Marie Jessica
LU
; Mestan, Zeliha
LU
; Nilsson, Caroline N
LU
; Ottosson, Karin
LU
; Rahmati, Kobra
LU
; Ramelius, Anita
LU
; Salami, Falastin
LU
; Sjöberg, Anette
LU
; Sjöberg, Birgitta
LU
; Törn, Carina
LU
; Wallin, Anne
LU
; Wimar, Åsa
LU
and Åberg, Sofie
LU
- author collaboration
- organization
- publishing date
- 2019-06
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Diabetes Care
- volume
- 42
- issue
- 6
- pages
- 10 pages
- publisher
- American Diabetes Association
- external identifiers
-
- pmid:30967432
- scopus:85066448751
- ISSN
- 1935-5548
- DOI
- 10.2337/dc18-2282
- language
- English
- LU publication?
- yes
- additional info
- © 2019 by the American Diabetes Association.
- id
- d4a847df-2957-40fc-ad4a-d9c751d6e20d
- date added to LUP
- 2019-06-25 13:10:02
- date last changed
- 2024-04-16 11:34:10
@article{d4a847df-2957-40fc-ad4a-d9c751d6e20d,
abstract = {{<p>OBJECTIVE: Assessment of the predictive power of The Environmental Determinants of Diabetes in the Young (TEDDY)-identified risk factors for islet autoimmunity (IA), the type of autoantibody appearing first, and type 1 diabetes (T1D).</p><p>RESEARCH DESIGN AND METHODS: A total of 7,777 children were followed from birth to a median of 9.1 years of age for the development of islet autoantibodies and progression to T1D. Time-dependent sensitivity, specificity, and receiver operating characteristic (ROC) curves were calculated to provide estimates of their individual and collective ability to predict IA and T1D.</p><p>RESULTS: HLA genotype (DR3/4 vs. others) was the best predictor for IA (Youden's index J = 0.117) and single nucleotide polymorphism rs2476601, in PTPN22, was the best predictor for insulin autoantibodies (IAA) appearing first (IAA-first) (J = 0.123). For GAD autoantibodies (GADA)-first, weight at 1 year was the best predictor (J = 0.114). In a multivariate model, the area under the ROC curve (AUC) was 0.678 (95% CI 0.655, 0.701), 0.707 (95% CI 0.676, 0.739), and 0.686 (95% CI 0.651, 0.722) for IA, IAA-first, and GADA-first, respectively, at 6 years. The AUC of the prediction model for T1D at 3 years after the appearance of multiple autoantibodies reached 0.706 (95% CI 0.649, 0.762).</p><p>CONCLUSIONS: Prediction modeling statistics are valuable tools, when applied in a time-until-event setting, to evaluate the ability of risk factors to discriminate between those who will and those who will not get disease. Although significantly associated with IA and T1D, the TEDDY risk factors individually contribute little to prediction. However, in combination, these factors increased IA and T1D prediction substantially.</p>}},
author = {{Krischer, Jeffrey P and Liu, Xiang and Vehik, Kendra and Akolkar, Beena and Hagopian, William A and Rewers, Marian J and She, Jin-Xiong and Toppari, Jorma and Ziegler, Anette-G and Lernmark, Åke}},
issn = {{1935-5548}},
language = {{eng}},
number = {{6}},
pages = {{1051--1060}},
publisher = {{American Diabetes Association}},
series = {{Diabetes Care}},
title = {{Predicting Islet Cell Autoimmunity and Type 1 Diabetes : An 8-Year TEDDY Study Progress Report}},
url = {{http://dx.doi.org/10.2337/dc18-2282}},
doi = {{10.2337/dc18-2282}},
volume = {{42}},
year = {{2019}},
}