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Diabetologia
Published in: Diabetologia 11/2014

01-11-2014 | Article

Predicting major outcomes in type 1 diabetes: a model development and validation study

Authors: Sabita S. Soedamah-Muthu, Yvonne Vergouwe, Tina Costacou, Rachel G. Miller, Janice Zgibor, Nish Chaturvedi, Janet K. Snell-Bergeon, David M. Maahs, Marian Rewers, Carol Forsblom, Valma Harjutsalo, Per-Henrik Groop, John H. Fuller, Karel G. M. Moons, Trevor J. Orchard

Published in: Diabetologia | Issue 11/2014

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Abstract

Aims/hypothesis

Type 1 diabetes is associated with a higher risk of major vascular complications and death. A reliable method that predicted these outcomes early in the disease process would help in risk classification. We therefore developed such a prognostic model and quantified its performance in independent cohorts.

Methods

Data were analysed from 1,973 participants with type 1 diabetes followed for 7 years in the EURODIAB Prospective Complications Study. Strong prognostic factors for major outcomes were combined in a Weibull regression model. The performance of the model was tested in three different prospective cohorts: the Pittsburgh Epidemiology of Diabetes Complications study (EDC, n = 554), the Finnish Diabetic Nephropathy study (FinnDiane, n = 2,999) and the Coronary Artery Calcification in Type 1 Diabetes study (CACTI, n = 580). Major outcomes included major CHD, stroke, end-stage renal failure, amputations, blindness and all-cause death.

Results

A total of 95 EURODIAB patients with type 1 diabetes developed major outcomes during follow-up. Prognostic factors were age, HbA1c, WHR, albumin/creatinine ratio and HDL-cholesterol level. The discriminative ability of the model was adequate, with a concordance statistic (C-statistic) of 0.74. Discrimination was similar or even better in the independent cohorts, the C-statistics being: EDC, 0.79; FinnDiane, 0.82; and CACTI, 0.73.

Conclusions/interpretation

Our prognostic model, which uses easily accessible clinical features can discriminate between type 1 diabetes patients who have a good or a poor prognosis. Such a prognostic model may be helpful in clinical practice and for risk stratification in clinical trials.
Appendix
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Metadata
Title
Predicting major outcomes in type 1 diabetes: a model development and validation study
Authors
Sabita S. Soedamah-Muthu
Yvonne Vergouwe
Tina Costacou
Rachel G. Miller
Janice Zgibor
Nish Chaturvedi
Janet K. Snell-Bergeon
David M. Maahs
Marian Rewers
Carol Forsblom
Valma Harjutsalo
Per-Henrik Groop
John H. Fuller
Karel G. M. Moons
Trevor J. Orchard
Publication date
01-11-2014
Publisher
Springer Berlin Heidelberg
Published in
Diabetologia / Issue 11/2014
Print ISSN: 0012-186X
Electronic ISSN: 1432-0428
DOI
https://doi.org/10.1007/s00125-014-3358-x

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