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Modelling chemotherapy effects on granulopoiesis

BACKGROUND: Although the growth-factor G-CSF is widely used to prevent granulotoxic side effects of cytotoxic chemotherapies, its optimal use is still unknown since treatment outcome depends on many parameters such as dosing and timing of chemotherapies, pharmaceutical derivative of G-CSF used and i...

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Autores principales: Schirm, Sibylle, Engel, Christoph, Loeffler, Markus, Scholz, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302124/
https://www.ncbi.nlm.nih.gov/pubmed/25539928
http://dx.doi.org/10.1186/s12918-014-0138-7
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author Schirm, Sibylle
Engel, Christoph
Loeffler, Markus
Scholz, Markus
author_facet Schirm, Sibylle
Engel, Christoph
Loeffler, Markus
Scholz, Markus
author_sort Schirm, Sibylle
collection PubMed
description BACKGROUND: Although the growth-factor G-CSF is widely used to prevent granulotoxic side effects of cytotoxic chemotherapies, its optimal use is still unknown since treatment outcome depends on many parameters such as dosing and timing of chemotherapies, pharmaceutical derivative of G-CSF used and individual risk factors. We showed in the past that a pharmacokinetic and –dynamic model of G-CSF and human granulopoiesis can be used to predict the performance of yet untested G-CSF schedules. However, only a single chemotherapy was considered so far. In the present paper, we propose a comprehensive model of chemotherapy toxicity and combine it with our cell kinetic model of granulopoiesis. Major assumptions are: proportionality of cell numbers and cell loss, delayed action of chemotherapy, drug, drug-dose and cell stage specific toxicities, no interaction of drugs and higher toxicity of drugs at the first time of application. Correspondingly, chemotherapies can be characterized by a set of toxicity parameters which can be estimated by fitting the predictions of our model to clinical time series data of patients under therapy. Data were either extracted from the literature or were received from cooperating clinical study groups. RESULTS: Model assumptions proved to be feasible in explaining granulotoxicity of 10 different chemotherapeutic drugs or drug-combinations applied in 33 different schedules with and without G-CSF. Risk groups of granulotoxicity were traced back to differences in toxicity parameters. CONCLUSION: We established a comprehensive model of combined G-CSF and chemotherapy action in humans which allows us to predict and compare the outcome of alternative G-CSF schedules. We aim to apply the model in different clinical contexts to optimize and individualize G-CSF treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-014-0138-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-43021242015-02-03 Modelling chemotherapy effects on granulopoiesis Schirm, Sibylle Engel, Christoph Loeffler, Markus Scholz, Markus BMC Syst Biol Research Article BACKGROUND: Although the growth-factor G-CSF is widely used to prevent granulotoxic side effects of cytotoxic chemotherapies, its optimal use is still unknown since treatment outcome depends on many parameters such as dosing and timing of chemotherapies, pharmaceutical derivative of G-CSF used and individual risk factors. We showed in the past that a pharmacokinetic and –dynamic model of G-CSF and human granulopoiesis can be used to predict the performance of yet untested G-CSF schedules. However, only a single chemotherapy was considered so far. In the present paper, we propose a comprehensive model of chemotherapy toxicity and combine it with our cell kinetic model of granulopoiesis. Major assumptions are: proportionality of cell numbers and cell loss, delayed action of chemotherapy, drug, drug-dose and cell stage specific toxicities, no interaction of drugs and higher toxicity of drugs at the first time of application. Correspondingly, chemotherapies can be characterized by a set of toxicity parameters which can be estimated by fitting the predictions of our model to clinical time series data of patients under therapy. Data were either extracted from the literature or were received from cooperating clinical study groups. RESULTS: Model assumptions proved to be feasible in explaining granulotoxicity of 10 different chemotherapeutic drugs or drug-combinations applied in 33 different schedules with and without G-CSF. Risk groups of granulotoxicity were traced back to differences in toxicity parameters. CONCLUSION: We established a comprehensive model of combined G-CSF and chemotherapy action in humans which allows us to predict and compare the outcome of alternative G-CSF schedules. We aim to apply the model in different clinical contexts to optimize and individualize G-CSF treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-014-0138-7) contains supplementary material, which is available to authorized users. BioMed Central 2014-12-24 /pmc/articles/PMC4302124/ /pubmed/25539928 http://dx.doi.org/10.1186/s12918-014-0138-7 Text en © Schirm et al.; licensee BioMed Central. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Schirm, Sibylle
Engel, Christoph
Loeffler, Markus
Scholz, Markus
Modelling chemotherapy effects on granulopoiesis
title Modelling chemotherapy effects on granulopoiesis
title_full Modelling chemotherapy effects on granulopoiesis
title_fullStr Modelling chemotherapy effects on granulopoiesis
title_full_unstemmed Modelling chemotherapy effects on granulopoiesis
title_short Modelling chemotherapy effects on granulopoiesis
title_sort modelling chemotherapy effects on granulopoiesis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302124/
https://www.ncbi.nlm.nih.gov/pubmed/25539928
http://dx.doi.org/10.1186/s12918-014-0138-7
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