Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/34948
Title: Parameter estimation for leukocyte dynamics after chemotherapy
Author(s): Rinke, Kristine
Jost, FelixLook up in the Integrated Authority File of the German National Library
Findeisen, RolfLook up in the Integrated Authority File of the German National Library
Fischer, Thomas
Bartsch, Rainer
Schalk, Enrico
Sager, SebastianLook up in the Integrated Authority File of the German National Library
Issue Date: 2020
Extent: 1 Online-Ressource (6 Seiten, 553.97 kB)
Type: Article
Language: English
Publisher: Elsevier Ltd., Frankfurt/M.
URN: urn:nbn:de:gbv:ma9:1-1981185920-351486
Subjects: Leukopenia
Acute myeloid leukemia
Weighted least-squares method
Initial value analysis
Abstract: Leukopenia is one of the most harmful side effects during chemotherapy treatment, since leukocytes (L) are crucial in protecting patients against bacteria and fungi. A personalized mathematical model of dynamics of L would allow a glimpse into the future and the initiation of tailored countermeasures. We propose such a mathematical model and calibrate it based on a parameter estimation with real world data. For our study we used data of L during and after consolidation chemotherapy treatment (cytarabine) of six patients contracting acute myeloid leukemia. We compare two different ways to treat the unknown initial values of the system of ordinary differential equations, discuss patient-specificity of parameter values, and different scalings of the least squares formulation. These three comparisons are necessary considerations for all modeling approaches to biomedicine, and have thus a methodological scope beyond the specific case of leukopenia. In summary, we show that our approach is able to simulate L dynamics in response to chemotherapy treatment and allows to take patient-specific characteristics into account.
URI: https://opendata.uni-halle.de//handle/1981185920/35148
http://dx.doi.org/10.25673/34948
Open Access: Open access publication
License: (CC BY-NC-ND 4.0) Creative Commons Attribution NonCommercial NoDerivatives 4.0(CC BY-NC-ND 4.0) Creative Commons Attribution NonCommercial NoDerivatives 4.0
Journal Title: IFAC-PapersOnLine
Publisher: Elsevier
Publisher Place: Frankfurt/M.
Volume: 49
Issue: 26
Original Publication: 10.1016/j.ifacol.2016.12.101
Page Start: 044
Page End: 049
Appears in Collections:Fakultät für Mathematik (OA)

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