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

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 (CP AVE ). 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 CP AVE 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 CP AVE 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, HbA 1c , 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 HbA 1c (IDAA1c) measure (AUROC 0.72 [95% CI 0.68, 0.76]). Model-estimated CP AVE (CP EST ) reliably identified treatment effects in randomised trials. CP EST , compared with CP AVE , required only a modest (up to 17%) increase in sample size for equivalent statistical power. Conclusions/interpretation CP EST , approximated from six variables at a single time point, accurately identifies loss of beta cell function in type 1 diabetes and is comparable to CP AVE for identifying treatment effects. CP EST 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.