SwePub
Sök i LIBRIS databas

  Utökad sökning

(WFRF:(DiMeglio Linda A))
 

Sökning: (WFRF:(DiMeglio Linda A)) > Simplifying predict...

Simplifying prediction of disease progression in pre-symptomatic type 1 diabetes using a single blood sample

Bediaga, Naiara G (författare)
Walter and Eliza Hall Institute of Medical Research
Li-Wai-Suen, Connie S N (författare)
University of Melbourne
Haller, Michael J (författare)
University of Florida
visa fler...
Gitelman, Stephen E (författare)
University of California, San Francisco
Evans-Molina, Carmella (författare)
Indiana University
Gottlieb, Peter A (författare)
University of Colorado
Hippich, Markus (författare)
Helmholtz Zentrum München
Ziegler, Anette-Gabriele (författare)
Helmholtz Zentrum München
Lernmark, Ake (författare)
Lund University,Lunds universitet,Celiaki och diabetes,Forskargrupper vid Lunds universitet,Oftalmologi (Malmö),Celiac Disease and Diabetes Unit,Lund University Research Groups,Ophthalmology (Malmö),Skåne University Hospital
DiMeglio, Linda A (författare)
Indiana University
Wherrett, Diane K (författare)
University of Toronto
Colman, Peter G (författare)
Royal Melbourne Hospital
Harrison, Leonard C (författare)
Walter and Eliza Hall Institute of Medical Research
Wentworth, John M (författare)
Walter and Eliza Hall Institute of Medical Research
visa färre...
 (creator_code:org_t)
2021-08-02
2021
Engelska.
Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 64:11, s. 2432-2444
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • AIMS/HYPOTHESIS: Accurate prediction of disease progression in individuals with pre-symptomatic type 1 diabetes has potential to prevent ketoacidosis and accelerate development of disease-modifying therapies. Current tools for predicting risk require multiple blood samples taken during an OGTT. Our aim was to develop and validate a simpler tool based on a single blood draw.METHODS: Models to predict disease progression using a single OGTT time point (0, 30, 60, 90 or 120 min) were developed using TrialNet data collected from relatives with type 1 diabetes and validated in independent populations at high genetic risk of type 1 diabetes (TrialNet, Diabetes Prevention Trial-Type 1, The Environmental Determinants of Diabetes in the Young [1]) and in a general population of Bavarian children who participated in Fr1da.RESULTS: Cox proportional hazards models combining plasma glucose, C-peptide, sex, age, BMI, HbA1c and insulinoma antigen-2 autoantibody status predicted disease progression in all populations. In TrialNet, the AUC for receiver operating characteristic curves for models named M60, M90 and M120, based on sampling at 60, 90 and 120 min, was 0.760, 0.761 and 0.745, respectively. These were not significantly different from the AUC of 0.760 for the gold standard Diabetes Prevention Trial Risk Score, which requires five OGTT blood samples. In TEDDY, where only 120 min blood sampling had been performed, the M120 AUC was 0.865. In Fr1da, the M120 AUC of 0.742 was significantly greater than the M60 AUC of 0.615.CONCLUSIONS/INTERPRETATION: Prediction models based on a single OGTT blood draw accurately predict disease progression from stage 1 or 2 to stage 3 type 1 diabetes. The operational simplicity of M120, its validity across different at-risk populations and the requirement for 120 min sampling to stage type 1 diabetes suggest M120 could be readily applied to decrease the cost and complexity of risk stratification.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Endokrinologi och diabetes (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Endocrinology and Diabetes (hsv//eng)

Publikations- och innehållstyp

art (ämneskategori)
ref (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy