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Beta cell function in type 1 diabetes determined from clinical and fasting biochemical variables


Wentworth, JM; Bediaga, NG; Giles, LC; Ehlers, M; Gitelman, SE; Geyer, S; Evans-Molina, C; Harrison, LC; Type 1 Diabetes TrialNet Study Group,; Immune Tolerance Network Study Group,
2018-08-30
Diabetologia
Journal Article
62
1
33-40
AIMS/HYPOTHESIS: Beta cell function in type 1 diabetes is commonly assessed as the average plasma C-peptide concentration over 2 h following a mixed-meal test (CPAVE). Monitoring of disease progression and response to disease-modifying therapy would benefit from a simpler, more convenient and less costly measure. Therefore, we determined whether CPAVE could be reliably estimated from routine clinical variables. METHODS: Clinical and fasting biochemical data from eight randomised therapy trials involving participants with recently diagnosed type 1 diabetes were used to develop and validate linear models to estimate CPAVE and to test their accuracy in estimating loss of beta cell function and response to immune therapy. RESULTS: A model based on disease duration, BMI, insulin dose, HbA1c, fasting plasma C-peptide and fasting plasma glucose most accurately estimated loss of beta cell function (area under the receiver operating characteristic curve [AUROC] 0.89 [95% CI 0.87, 0.92]) and was superior to the commonly used insulin-dose-adjusted HbA1c (IDAA1c) measure (AUROC 0.72 [95% CI 0.68, 0.76]). Model-estimated CPAVE (CPEST) reliably identified treatment effects in randomised trials. CPEST, compared with CPAVE, required only a modest (up to 17%) increase in sample size for equivalent statistical power. CONCLUSIONS/INTERPRETATION: CPEST, approximated from six variables at a single time point, accurately identifies loss of beta cell function in type 1 diabetes and is comparable to CPAVE for identifying treatment effects. CPEST could serve as a convenient and economical measure of beta cell function in the clinic and as a primary outcome measure in trials of disease-modifying therapy in type 1 diabetes.
Springer
Population Health and Immunity
10.1007/s00125-018-4722-z
30167735
Refer to article for additional funding acknowledgements
Refer to copyright notice on published article.

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Creation Date 2018-09-06 03:42:37 Last Modified 2019-10-17 03:22:47