Abstract
OBJECTIVE - The accurate prediction of type 1 diabetes is essential for appropriately identifying prevention trial participants. Thus, we have developed a risk score for the prediction of type 1 diabetes. RESEARCH DESIGN AND METHODS - Diabetes Prevention Trial-Type 1 (DFT-1) participants, islet cell autoantibody (ICA)-positive relatives of type 1 diabetic patients (n = 670), were randomly divided into development and validation samples. Risk score values were calculated for the validation sample from development sample model coefficients obtained through forward stepwise proportional hazards regression. RESULTS - A risk score based on a model including log-BMI, age, log-fasting C-peptide, and postchallenge glucose and C-peptide sums from 2-h oral glucose tolerance tests (OGTTs) was derived from the development sample. The baseline risk score strongly predicted type 1 diabetes in the validation sample (χ 2 = 82.3, P < 0.001). Its strength of prediction was almost the same (χ 2 = 83.3) as a risk score additionally dependent on a decreased first-phase insulin response variable from intravenous glucose tolerance tests (IVGTTs). Biochemical autoantibodies did not contribute significantly to the risk score model. A final type 1 diabetes risk score was then derived from all participants with the same variables as those in the development sample model. The change in the type 1 diabetes risk score from baseline to 1 year was in itself also highly predictive of type 1 diabetes (P < 0.001). CONCLUSIONS - A risk score based on age, BMI, and OGTT indexes, without dependence on IVGTTs or additional autoantibodies, appears to accurately predict type 1 diabetes in ICA-positive relatives.
| Original language | English |
|---|---|
| Pages (from-to) | 528-533 |
| Number of pages | 6 |
| Journal | Diabetes Care |
| Volume | 31 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 1 2008 |
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ASJC Scopus subject areas
- Internal Medicine
- Endocrinology, Diabetes and Metabolism
- Advanced and Specialized Nursing
Cite this
A risk score for type 1 diabetes derived from autoantibody-positive participants in the diabetes prevention trial-type 1. / Sosenko, Jay M; Krischer, Jeffrey P.; Palmer, Jerry P.; Mahon, Jeffrey; Cowie, Catherine; Greenbaum, Carla J.; Cuthbertson, David; Lachin, John M.; Skyler, Jay S.
In: Diabetes Care, Vol. 31, No. 3, 01.03.2008, p. 528-533.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A risk score for type 1 diabetes derived from autoantibody-positive participants in the diabetes prevention trial-type 1
AU - Sosenko, Jay M
AU - Krischer, Jeffrey P.
AU - Palmer, Jerry P.
AU - Mahon, Jeffrey
AU - Cowie, Catherine
AU - Greenbaum, Carla J.
AU - Cuthbertson, David
AU - Lachin, John M.
AU - Skyler, Jay S
PY - 2008/3/1
Y1 - 2008/3/1
N2 - OBJECTIVE - The accurate prediction of type 1 diabetes is essential for appropriately identifying prevention trial participants. Thus, we have developed a risk score for the prediction of type 1 diabetes. RESEARCH DESIGN AND METHODS - Diabetes Prevention Trial-Type 1 (DFT-1) participants, islet cell autoantibody (ICA)-positive relatives of type 1 diabetic patients (n = 670), were randomly divided into development and validation samples. Risk score values were calculated for the validation sample from development sample model coefficients obtained through forward stepwise proportional hazards regression. RESULTS - A risk score based on a model including log-BMI, age, log-fasting C-peptide, and postchallenge glucose and C-peptide sums from 2-h oral glucose tolerance tests (OGTTs) was derived from the development sample. The baseline risk score strongly predicted type 1 diabetes in the validation sample (χ 2 = 82.3, P < 0.001). Its strength of prediction was almost the same (χ 2 = 83.3) as a risk score additionally dependent on a decreased first-phase insulin response variable from intravenous glucose tolerance tests (IVGTTs). Biochemical autoantibodies did not contribute significantly to the risk score model. A final type 1 diabetes risk score was then derived from all participants with the same variables as those in the development sample model. The change in the type 1 diabetes risk score from baseline to 1 year was in itself also highly predictive of type 1 diabetes (P < 0.001). CONCLUSIONS - A risk score based on age, BMI, and OGTT indexes, without dependence on IVGTTs or additional autoantibodies, appears to accurately predict type 1 diabetes in ICA-positive relatives.
AB - OBJECTIVE - The accurate prediction of type 1 diabetes is essential for appropriately identifying prevention trial participants. Thus, we have developed a risk score for the prediction of type 1 diabetes. RESEARCH DESIGN AND METHODS - Diabetes Prevention Trial-Type 1 (DFT-1) participants, islet cell autoantibody (ICA)-positive relatives of type 1 diabetic patients (n = 670), were randomly divided into development and validation samples. Risk score values were calculated for the validation sample from development sample model coefficients obtained through forward stepwise proportional hazards regression. RESULTS - A risk score based on a model including log-BMI, age, log-fasting C-peptide, and postchallenge glucose and C-peptide sums from 2-h oral glucose tolerance tests (OGTTs) was derived from the development sample. The baseline risk score strongly predicted type 1 diabetes in the validation sample (χ 2 = 82.3, P < 0.001). Its strength of prediction was almost the same (χ 2 = 83.3) as a risk score additionally dependent on a decreased first-phase insulin response variable from intravenous glucose tolerance tests (IVGTTs). Biochemical autoantibodies did not contribute significantly to the risk score model. A final type 1 diabetes risk score was then derived from all participants with the same variables as those in the development sample model. The change in the type 1 diabetes risk score from baseline to 1 year was in itself also highly predictive of type 1 diabetes (P < 0.001). CONCLUSIONS - A risk score based on age, BMI, and OGTT indexes, without dependence on IVGTTs or additional autoantibodies, appears to accurately predict type 1 diabetes in ICA-positive relatives.
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UR - http://www.scopus.com/inward/citedby.url?scp=44349193971&partnerID=8YFLogxK
U2 - 10.2337/dc07-1459
DO - 10.2337/dc07-1459
M3 - Article
C2 - 18000175
AN - SCOPUS:44349193971
VL - 31
SP - 528
EP - 533
JO - Diabetes Care
JF - Diabetes Care
SN - 1935-5548
IS - 3
ER -