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A pharmacokinetic model for the glycation of albumin
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Farmakologi)
2012 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 39, no 3, 273-282 p.Article in journal (Refereed) Published
Abstract [en]

Glycated haemoglobin (HbA1c) concentrations can be falsely lowered in circumstances when red blood cell (RBC) survival is reduced, e.g. in patients with chronic kidney disease (CKD). Glycated albumin (GA) has been suggested as an alternative marker of glycaemic control in these patients since it is independent of the RBC life span. The primary aim of this work was to develop a pharmacokinetic model that describes the time course of GA. The secondary aim was to assess the performance of GA as marker for glycaemic control in comparison to HbA1c based on simulations. For the second aim, three different scenarios were considered in the simulations: 1) assessment of the effect of large intra-day fluctuations in mean blood glucose on GA concentrations, 2) initiation of antidiabetic treatment on the GA profile, and 3) a hypothetical phase II study for a new antidiabetic compound. The GA model, as well as a previously developed HbA1c model described literature data well. GA concentrations appear to be stable even in the presence of high intra-day fluctuations in mean blood glucose concentrations. Simulation of a decrease in mean blood glucose concentrations resulted in a faster change in GA compared to HbA1c. GA also provided a time to 90 % power of the effect of a hypothetical antidiabetic drug that was 16 days shorter than when using HbA1c. These results indicate that GA could be used as alternative marker to assess blood glucose control in diabetic patients with CKD and also to follow an individual patient over time.

Place, publisher, year, edition, pages
2012. Vol. 39, no 3, 273-282 p.
Keyword [en]
Glycated albumin, HbA1c, Chronic kidney disease, NONMEM, Clinical trial simulations
National Category
Pharmaceutical Sciences
URN: urn:nbn:se:uu:diva-176818DOI: 10.1007/s10928-012-9249-1ISI: 000304617500005OAI: oai:DiVA.org:uu-176818DiVA: diva2:537723
Available from: 2012-06-27 Created: 2012-06-26 Last updated: 2012-06-27Bibliographically approved

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Alskär, Oskar
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