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DOI: 10.1055/a-1998-6889
Comparability of C-Peptide Measurements – Current Status and Clinical Relevance
Abstract
C-peptide is an increasingly used and established marker for beta cell function by assessing endogenous insulin secretion. Accurate and comparable C-peptide measurements are needed in clinical practice and research studies. For example, to calculate HOMA-indices, the C-peptide/glucose ratio, and the classification of recently published novel subgroups of diabetes and prediabetes have used C-peptide measurements. Although the process for standardization of C-peptide measurements is advanced, its full implementation is still missing; therefore, the current status of the comparability of C-peptide measurements using different immunoassays is unclear. Here we compared five widely used C-peptide immunoassays on different analyzers (Abbott ALINITY i, DiaSorin Liaison XL, Roche Cobas e411, Siemens Healthineers ADVIA Centaur XPT, and Immulite 2000 XPi) using serum samples covering the clinically relevant C-peptide concentration range. Although all investigated immunoassays are traceable to the international reference reagent for C-peptide (NIBSC code: 84/510), results of C-peptide measurements showed significant differences between analyzers in the entire concentration range, especially with increasing C-peptide concentrations. The mean bias was largest (36.6%) between results of the immunoassays by Roche and Siemens Healthineers (ADVIA Centaur XPT), and both assays revealed large discrepancies compared to immunoassays by Abbott, DiaSorin, and Siemens Healthineers (Immulite 2000 XPi). In contrast, the three latter assays showed similar C-peptide results (mean bias: 2.3% to 4.2%). Consequently, C-peptide discrepancies might affect clinical diagnosis and the interpretation of study results. Therefore, there is an urgent need to implement and finalize the standardization process of C-peptide measurements to improve patient care and the comparability of research studies.
Publication History
Received: 06 September 2022
Received: 11 November 2022
Accepted: 26 October 2022
Article published online:
11 January 2023
© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Georg Thieme Verlag KG
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