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A combined risk score enhances prediction of type 1 diabetes among susceptible children

Ferrat, L.A. ; Vehik, K. LU ; Sharp, S.A. ; Lernmark, Å. LU orcid ; Rewers, M.J. ; She, J.-X. ; Ziegler, A.-G. ; Toppari, J. ; Akolkar, B. and Krischer, J.P. , et al. (2020) In Nature Medicine 26(8). p.1247-1255
Abstract
Type 1 diabetes (T1D)-an autoimmune disease that destroys the pancreatic islets, resulting in insulin deficiency-often begins early in life when islet autoantibody appearance signals high risk1. However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common2,3 and is most severe in the very young4,5, in whom it can be life threatening and difficult to treat6-9. Autoantibody surveillance programs effectively prevent most ketoacidosis10-12 but require frequent evaluations whose expense limits public health adoption13. Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible14 because individuals at greatest risk of... (More)
Type 1 diabetes (T1D)-an autoimmune disease that destroys the pancreatic islets, resulting in insulin deficiency-often begins early in life when islet autoantibody appearance signals high risk1. However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common2,3 and is most severe in the very young4,5, in whom it can be life threatening and difficult to treat6-9. Autoantibody surveillance programs effectively prevent most ketoacidosis10-12 but require frequent evaluations whose expense limits public health adoption13. Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible14 because individuals at greatest risk of impending T1D are difficult to identify. To remedy this, we sought accurate, cost-effective estimation of future T1D risk by developing a combined risk score incorporating both fixed and variable factors (genetic, clinical and immunological) in 7,798 high-risk children followed closely from birth for 9.3 years. Compared with autoantibodies alone, the combined model dramatically improves T1D prediction at ≥2 years of age over horizons up to 8 years of age (area under the receiver operating characteristic curve ≥ 0.9), doubles the estimated efficiency of population-based newborn screening to prevent ketoacidosis, and enables individualized risk estimates for better prevention trial selection. (Less)
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author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Nature Medicine
volume
26
issue
8
pages
9 pages
publisher
Nature Publishing Group
external identifiers
  • scopus:85089358607
  • pmid:32770166
ISSN
1546-170X
DOI
10.1038/s41591-020-0930-4
language
English
LU publication?
yes
id
1e2840ed-c551-4175-9470-25f31afb3278
date added to LUP
2020-08-20 13:47:23
date last changed
2022-07-13 03:33:20
@article{1e2840ed-c551-4175-9470-25f31afb3278,
  abstract     = {{Type 1 diabetes (T1D)-an autoimmune disease that destroys the pancreatic islets, resulting in insulin deficiency-often begins early in life when islet autoantibody appearance signals high risk1. However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common2,3 and is most severe in the very young4,5, in whom it can be life threatening and difficult to treat6-9. Autoantibody surveillance programs effectively prevent most ketoacidosis10-12 but require frequent evaluations whose expense limits public health adoption13. Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible14 because individuals at greatest risk of impending T1D are difficult to identify. To remedy this, we sought accurate, cost-effective estimation of future T1D risk by developing a combined risk score incorporating both fixed and variable factors (genetic, clinical and immunological) in 7,798 high-risk children followed closely from birth for 9.3 years. Compared with autoantibodies alone, the combined model dramatically improves T1D prediction at ≥2 years of age over horizons up to 8 years of age (area under the receiver operating characteristic curve ≥ 0.9), doubles the estimated efficiency of population-based newborn screening to prevent ketoacidosis, and enables individualized risk estimates for better prevention trial selection.}},
  author       = {{Ferrat, L.A. and Vehik, K. and Sharp, S.A. and Lernmark, Å. and Rewers, M.J. and She, J.-X. and Ziegler, A.-G. and Toppari, J. and Akolkar, B. and Krischer, J.P. and Weedon, M.N. and Oram, R.A. and Hagopian, W.A.}},
  issn         = {{1546-170X}},
  language     = {{eng}},
  number       = {{8}},
  pages        = {{1247--1255}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Medicine}},
  title        = {{A combined risk score enhances prediction of type 1 diabetes among susceptible children}},
  url          = {{http://dx.doi.org/10.1038/s41591-020-0930-4}},
  doi          = {{10.1038/s41591-020-0930-4}},
  volume       = {{26}},
  year         = {{2020}},
}