Predicting Islet Cell Autoimmunity and Type 1 Diabetes : An 8-Year TEDDY Study Progress Report
(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.
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- 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
-
- scopus:85066448751
- pmid:30967432
- 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
- 2024-09-19 01:33:53
@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}}, }