Literature DB >> 19084287

A tool for neutrophil guided dose adaptation in chemotherapy.

Johan E Wallin1, Lena E Friberg, Mats O Karlsson.   

Abstract

Chemotherapy dosing in anticancer treatment is a balancing act between achieving concentrations that are effective towards the malignancy and that result in acceptable side-effects. Neutropenia is one major side-effect of many antitumor agents, and is related to an increased risk of infection. A model capable of describing the time-course of myelosuppression from administered drug could be used in individual dose selection. In this paper we describe the transfer of a previously developed semi-mechanistic model for myelosuppression from NONMEM to a dosing tool in MS Excel, with etoposide as an example. The tool proved capable to solve a differential equation system describing the pharmacokinetics and pharmacodynamics, with estimation performance comparable to NONMEM. In the dosing tool the user provides neutrophil measures from a previous treatment course and request for the dose that results in a desired nadir in the upcoming course through a Bayesian estimation procedure.

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Year:  2008        PMID: 19084287     DOI: 10.1016/j.cmpb.2008.10.011

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  13 in total

1.  Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data.

Authors:  João A Abrantes; Siv Jönsson; Mats O Karlsson; Elisabet I Nielsen
Journal:  Br J Clin Pharmacol       Date:  2019-04-29       Impact factor: 4.335

2.  Model-based approach to early predict prolonged high grade neutropenia in carboplatin-treated patients and guide G-CSF prophylactic treatment.

Authors:  Mélanie L Pastor; Céline M Laffont; Laurence Gladieff; Etienne Chatelut; Didier Concordet
Journal:  Pharm Res       Date:  2014-09-04       Impact factor: 4.200

3.  Population pharmacokinetic/dynamic model of lymphosuppression after fludarabine administration.

Authors:  Jeannine S McCune; Paolo Vicini; David H Salinger; Paul V O'Donnell; Brenda M Sandmaier; Claudio Anasetti; Donald E Mager
Journal:  Cancer Chemother Pharmacol       Date:  2014-11-06       Impact factor: 3.333

4.  A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children.

Authors:  Anna-Karin Hamberg; Jacob Hellman; Jonny Dahlberg; E Niclas Jonsson; Mia Wadelius
Journal:  BMC Med Inform Decis Mak       Date:  2015-02-07       Impact factor: 2.796

5.  Prediction of Response to Temozolomide in Low-Grade Glioma Patients Based on Tumor Size Dynamics and Genetic Characteristics.

Authors:  P Mazzocco; C Barthélémy; G Kaloshi; M Lavielle; D Ricard; A Idbaih; D Psimaras; M-A Renard; A Alentorn; J Honnorat; J-Y Delattre; F Ducray; B Ribba
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2015-10-10

6.  Model-based prediction of myelosuppression and recovery based on frequent neutrophil monitoring.

Authors:  Ida Netterberg; Elisabet I Nielsen; Lena E Friberg; Mats O Karlsson
Journal:  Cancer Chemother Pharmacol       Date:  2017-06-27       Impact factor: 3.333

7.  Modeling individual time courses of thrombopoiesis during multi-cyclic chemotherapy.

Authors:  Yuri Kheifetz; Markus Scholz
Journal:  PLoS Comput Biol       Date:  2019-03-06       Impact factor: 4.475

8.  Model-based adaptive phase I trial design of post-transplant decitabine maintenance in myelodysplastic syndrome.

Authors:  Seunghoon Han; Yoo-Jin Kim; Jongtae Lee; Sangil Jeon; Taegon Hong; Gab-Jin Park; Jae-Ho Yoon; Seung-Ah Yahng; Seung-Hwan Shin; Sung-Eun Lee; Ki-Seong Eom; Hee-Je Kim; Chang-Ki Min; Seok Lee; Dong-Seok Yim
Journal:  J Hematol Oncol       Date:  2015-10-23       Impact factor: 17.388

9.  Bayesian Data Assimilation to Support Informed Decision Making in Individualized Chemotherapy.

Authors:  Corinna Maier; Niklas Hartung; Jana de Wiljes; Charlotte Kloft; Wilhelm Huisinga
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2020-01-31

Review 10.  Understanding and applying pharmacometric modelling and simulation in clinical practice and research.

Authors:  Joseph F Standing
Journal:  Br J Clin Pharmacol       Date:  2016-09-29       Impact factor: 4.335

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