Beta cell function in type 1 diabetes determined from clinical and fasting biochemical variables
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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.
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.
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.
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.
KeywordsAdult Beta cell function Children Clinical trial Immune therapy Immune Tolerance Network Linear model TrialNet Type 1 diabetes
Akaike’s information criterion
Area under the ROC curve
Average plasma C-peptide concentration over 2 h following a mixed-meal test
Fasting plasma glucose
Immune Tolerance Network
Receiver operating characteristic
We are grateful to the trial participants and to M. Ritchie (Molecular Medicine Division, Walter and Eliza Hall Institute, Australia) and A. Gorelik (Epicentre, Royal Melbourne Hospital, Australia) for statistical advice. We also thank the ITN and TrialNet investigators who contributed to original data, listed in the ESM.
JMW devised the study. JMW, NGB, LCG and LCH analysed the data and prepared the manuscript. All named authors contributed to collection, collation, analysis and interpretation of the data, helped to revise the manuscript and approved it for publication. Authors listed in the ESM contributed by performing the TrialNet and ITN clinical trials. JMW is the guarantor and takes full responsibility for the work as a whole, including the study design, access to data and the decision to submit and publish the manuscript.
This work was supported by JDRF Australia (Clinical Practitioner Fellowship to JMW) and JDRF (Strategic Research Agreement to CE-M) and the Australian National Health and Medical Research Council (NHMRC) (Program Grant 1037321 to LCH and CRE 1078106 Fellowship to JMW). LCH is a Senior Principal Research Fellow of the NHMRC. This work was made possible through Victorian State Government Operational Infrastructure Support and Australian National Health and Medical Research Council Research Institute Infrastructure Support Scheme. This manuscript includes clinical and biochemical data provided by the TrialNet data repository from clinical trials TN-02, TN-05, TN-08, TN-09 and TN-14. TrialNet is currently funded by NIH grants U01 DK061010, U01 DK061034, U01 DK061042, U01 DK061058, U01 DK085461, U01 DK085465, U01 DK085466, U01 DK085476, U01 DK085499, U01 DK085509, U01 DK103180, U01 DK103153, U01 DK103266, U01 DK103282, U01 DK106984, U01 DK106994, U01 DK107013, U01 DK107014, UC4 DK106993, and the JDRF. Research reported in this publication was also performed as a project of the Immune Tolerance Network and was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health under Award Number UM1AI109565. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funding sources had no role in the writing of the manuscript or the decision to submit it for publication.
Duality of interest
SEG received funding from the Immune Tolerance Network (in turn funded by NIAID) for his role as principal investigator of the START trial (ITN-28). SG received a grant from NIDDK for unrelated work. All other authors declare that there is no duality of interest associated with their contribution to this manuscript.
- 15.Herold KC, Gitelman SE, Ehlers MR et al (2013) Teplizumab (anti-CD3 mAb) treatment preserves C-peptide responses in patients with new-onset type 1 diabetes in a randomized controlled trial: metabolic and immunologic features at baseline identify a subgroup of responders. Diabetes 62:3766–3774CrossRefPubMedPubMedCentralGoogle Scholar
- 23.Herold KC, Gitelman SE, Masharani U et al (2005) A single course of anti-CD3 monoclonal antibody hOKT3gamma1(Ala-Ala) results in improvement in C-peptide responses and clinical parameters for at least 2 years after onset of type 1 diabetes. Diabetes 54:1763–1769CrossRefPubMedPubMedCentralGoogle Scholar