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  • Köhler, MeikeHelmholtz Zentrum München (author)

Joint modeling of longitudinal autoantibody patterns and progression to type 1 diabetes : results from the TEDDY study

  • Article/chapterEnglish2017

Publisher, publication year, extent ...

  • 2017-08-30
  • Springer Science and Business Media LLC,2017

Numbers

  • LIBRIS-ID:oai:lup.lub.lu.se:d069a342-35b5-4fb4-a799-52f30fa96f2e
  • https://lup.lub.lu.se/record/d069a342-35b5-4fb4-a799-52f30fa96f2eURI
  • https://doi.org/10.1007/s00592-017-1033-7DOI

Supplementary language notes

  • Language:English
  • Summary in:English

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  • Subject category:art swepub-publicationtype
  • Subject category:ref swepub-contenttype

Notes

  • AIMS: The onset of clinical type 1 diabetes (T1D) is preceded by the occurrence of disease-specific autoantibodies. The level of autoantibody titers is known to be associated with progression time from the first emergence of autoantibodies to the onset of clinical symptoms, but detailed analyses of this complex relationship are lacking. We aimed to fill this gap by applying advanced statistical models.METHODS: We investigated data of 613 children from the prospective TEDDY study who were persistent positive for IAA, GADA and/or IA2A autoantibodies. We used a novel approach of Bayesian joint modeling of longitudinal and survival data to assess the potentially time- and covariate-dependent association between the longitudinal autoantibody titers and progression time to T1D.RESULTS: For all autoantibodies we observed a positive association between the titers and the T1D progression risk. This association was estimated as time-constant for IA2A, but decreased over time for IAA and GADA. For example the hazard ratio [95% credibility interval] for IAA (per transformed unit) was 3.38 [2.66, 4.38] at 6 months after seroconversion, and 2.02 [1.55, 2.68] at 36 months after seroconversion.CONCLUSIONS: These findings indicate that T1D progression risk stratification based on autoantibody titers should focus on time points early after seroconversion. Joint modeling techniques allow for new insights into these associations.

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Added entries (persons, corporate bodies, meetings, titles ...)

  • Beyerlein, AndreasHelmholtz Zentrum München (author)
  • Vehik, KendraUniversity of South Florida(Swepub:lu)med-krv (author)
  • Greven, SonjaLudwig-Maximilian University of Munich (author)
  • Umlauf, NikolausUniversity of Innsbruck (author)
  • Lernmark, ÅkeLund University,Lunds universitet,Celiaki och diabetes,Forskargrupper vid Lunds universitet,Celiac Disease and Diabetes Unit,Lund University Research Groups,Skåne University Hospital(Swepub:lu)endo-ale (author)
  • Hagopian, William A.Pacific Northwest Research Institute (author)
  • Rewers, MarianUniversity of Colorado (author)
  • She, Jin-XiongMedical College of Georgia (author)
  • Toppari, JormaTurku University Hospital (author)
  • Akolkar, BeenaNational Institute of Diabetes and Digestive and Kidney Diseases (author)
  • Krischer, Jeffrey P.University of South Florida (author)
  • Bonifacio, EzioDresden University of Technology (author)
  • Ziegler, Anette-GHelmholtz Zentrum München (author)
  • Helmholtz Zentrum MünchenUniversity of South Florida (creator_code:org_t)
  • TEDDY Study Group

Related titles

  • In:Acta Diabetologica: Springer Science and Business Media LLC54:11, s. 1009-10171432-52330940-5429

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