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Modelling of OGTT curve identifies 1 h plasma glucose level as a strong predictor of incident type 2 diabetes: results from two prospective cohorts

Alyass, Akram ; Almgren, Peter LU ; Åkerlund, Mikael LU ; Dushoff, Jonathan ; Isomaa, Bo ; Nilsson, Peter LU ; Tuomi, Tiinamaija ; Lyssenko, Valeriya LU ; Groop, Leif LU and Meyre, David (2015) In Diabetologia 58(1). p.87-97
Abstract
Aims/hypothesis The relevance of the OGTT in predicting type 2 diabetes is unclear. We assessed the performance of 14 OGTT glucose traits in type 2 diabetes prediction. Methods We studied 2,603 and 2,386 Europeans from the Botnia study and Malmo Prevention Project (MPP) cohorts with baseline OGTT data. Over a follow-up period of 4.94 years and 23.5 years, 155 (5.95%) and 467 (19.57%) participants, respectively, developed type 2 diabetes. The main outcome was incident type 2 diabetes. Results One-hour plasma glucose (1h-PG) was a fair/good predictor of incident type 2 diabetes in the Botnia study and MPP (AUC for receiver operating characteristic [AUC(ROC)] 0.80 [0.77, 0.84] and 0.70 [0.68, 0.73]). 1h-PG alone outperformed the prediction... (More)
Aims/hypothesis The relevance of the OGTT in predicting type 2 diabetes is unclear. We assessed the performance of 14 OGTT glucose traits in type 2 diabetes prediction. Methods We studied 2,603 and 2,386 Europeans from the Botnia study and Malmo Prevention Project (MPP) cohorts with baseline OGTT data. Over a follow-up period of 4.94 years and 23.5 years, 155 (5.95%) and 467 (19.57%) participants, respectively, developed type 2 diabetes. The main outcome was incident type 2 diabetes. Results One-hour plasma glucose (1h-PG) was a fair/good predictor of incident type 2 diabetes in the Botnia study and MPP (AUC for receiver operating characteristic [AUC(ROC)] 0.80 [0.77, 0.84] and 0.70 [0.68, 0.73]). 1h-PG alone outperformed the prediction model of multiple clinical risk factors (age, sex, BMI, family history of type 2 diabetes) in the Botnia study and MPP (AUC(ROC) 0.75 [0.72, 0.79] and 0.67 [0.64, 0.70]). The same clinical risk factors added to 1h-PG modestly increased prediction for incident type 2 diabetes (Botnia, AUC(ROC) 0.83 [0.80, 0.86]; MPP, AUC(ROC) 0.74 [0.72, 0.77]). 1h-PG also outperformed HbA(1c) in predicting type 2 diabetes in the Botnia cohort. A 1h-PG value of 8.9 mmol/l and 8.4 mmol/l was the optimal cut-point for initial screening and selection of high-risk individuals in the Botnia study and MPP, respectively, and represented 30% and 37% of all participants in these cohorts. High-risk individuals had a substantially increased risk of incident type 2 diabetes (OR 8.0 [5.5, 11.6] and 3.8 [3.1, 4.7]) and captured 75% and 62% of all incident type 2 diabetes in the Botnia study and MPP. Conclusions/interpretation1h-PG is a valuable prediction tool for identifying adults at risk for future type 2 diabetes. (Less)
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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Incident type 2 diabetes, Mathematical modelling, One-hour post-OGTT, plasma glucose, Oral glucose tolerance test, Prevention
in
Diabetologia
volume
58
issue
1
pages
87 - 97
publisher
Springer
external identifiers
  • wos:000346022300014
  • scopus:84916640700
  • pmid:25292440
ISSN
1432-0428
DOI
10.1007/s00125-014-3390-x
language
English
LU publication?
yes
id
4d11c320-9b10-47f2-9ce3-f737081fb853 (old id 4950730)
date added to LUP
2016-04-01 09:52:59
date last changed
2024-04-06 19:44:31
@article{4d11c320-9b10-47f2-9ce3-f737081fb853,
  abstract     = {{Aims/hypothesis The relevance of the OGTT in predicting type 2 diabetes is unclear. We assessed the performance of 14 OGTT glucose traits in type 2 diabetes prediction. Methods We studied 2,603 and 2,386 Europeans from the Botnia study and Malmo Prevention Project (MPP) cohorts with baseline OGTT data. Over a follow-up period of 4.94 years and 23.5 years, 155 (5.95%) and 467 (19.57%) participants, respectively, developed type 2 diabetes. The main outcome was incident type 2 diabetes. Results One-hour plasma glucose (1h-PG) was a fair/good predictor of incident type 2 diabetes in the Botnia study and MPP (AUC for receiver operating characteristic [AUC(ROC)] 0.80 [0.77, 0.84] and 0.70 [0.68, 0.73]). 1h-PG alone outperformed the prediction model of multiple clinical risk factors (age, sex, BMI, family history of type 2 diabetes) in the Botnia study and MPP (AUC(ROC) 0.75 [0.72, 0.79] and 0.67 [0.64, 0.70]). The same clinical risk factors added to 1h-PG modestly increased prediction for incident type 2 diabetes (Botnia, AUC(ROC) 0.83 [0.80, 0.86]; MPP, AUC(ROC) 0.74 [0.72, 0.77]). 1h-PG also outperformed HbA(1c) in predicting type 2 diabetes in the Botnia cohort. A 1h-PG value of 8.9 mmol/l and 8.4 mmol/l was the optimal cut-point for initial screening and selection of high-risk individuals in the Botnia study and MPP, respectively, and represented 30% and 37% of all participants in these cohorts. High-risk individuals had a substantially increased risk of incident type 2 diabetes (OR 8.0 [5.5, 11.6] and 3.8 [3.1, 4.7]) and captured 75% and 62% of all incident type 2 diabetes in the Botnia study and MPP. Conclusions/interpretation1h-PG is a valuable prediction tool for identifying adults at risk for future type 2 diabetes.}},
  author       = {{Alyass, Akram and Almgren, Peter and Åkerlund, Mikael and Dushoff, Jonathan and Isomaa, Bo and Nilsson, Peter and Tuomi, Tiinamaija and Lyssenko, Valeriya and Groop, Leif and Meyre, David}},
  issn         = {{1432-0428}},
  keywords     = {{Incident type 2 diabetes; Mathematical modelling; One-hour post-OGTT; plasma glucose; Oral glucose tolerance test; Prevention}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{87--97}},
  publisher    = {{Springer}},
  series       = {{Diabetologia}},
  title        = {{Modelling of OGTT curve identifies 1 h plasma glucose level as a strong predictor of incident type 2 diabetes: results from two prospective cohorts}},
  url          = {{http://dx.doi.org/10.1007/s00125-014-3390-x}},
  doi          = {{10.1007/s00125-014-3390-x}},
  volume       = {{58}},
  year         = {{2015}},
}