Literature DB >> 27329303

Improvement of Parameter Estimations in Tumor Growth Inhibition Models on Xenografted Animals: Handling Sacrifice Censoring and Error Caused by Experimental Measurement on Larger Tumor Sizes.

Philippe B Pierrillas1,2, Michel Tod3,4, Magali Amiel5, Marylore Chenel6, Emilie Henin3.   

Abstract

The purpose of this study was to explore the impact of censoring due to animal sacrifice on parameter estimates and tumor volume calculated from two diameters in larger tumors during tumor growth experiments in preclinical studies. The type of measurement error that can be expected was also investigated. Different scenarios were challenged using the stochastic simulation and estimation process. One thousand datasets were simulated under the design of a typical tumor growth study in xenografted mice, and then, eight approaches were used for parameter estimation with the simulated datasets. The distribution of estimates and simulation-based diagnostics were computed for comparison. The different approaches were robust regarding the choice of residual error and gave equivalent results. However, by not considering missing data induced by sacrificing the animal, parameter estimates were biased and led to false inferences in terms of compound potency; the threshold concentration for tumor eradication when ignoring censoring was 581 ng.ml(-1), but the true value was 240 ng.ml(-1).

Entities:  

Keywords:  missing data; sacrifice censoring; stochastic simulation and estimation; upper limit of quantification; xenograft model

Mesh:

Year:  2016        PMID: 27329303     DOI: 10.1208/s12248-016-9936-8

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  20 in total

1.  PsN-Toolkit--a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM.

Authors:  Lars Lindbom; Pontus Pihlgren; E Niclas Jonsson; Niclas Jonsson
Journal:  Comput Methods Programs Biomed       Date:  2005-09       Impact factor: 5.428

2.  Derivation of various NONMEM estimation methods.

Authors:  Yaning Wang
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-07-10       Impact factor: 2.745

3.  Likelihood based approaches to handling data below the quantification limit using NONMEM VI.

Authors:  Jae Eun Ahn; Mats O Karlsson; Adrian Dunne; Thomas M Ludden
Journal:  J Pharmacokinet Pharmacodyn       Date:  2008-08-07       Impact factor: 2.745

4.  Mathematical model approach to describe tumour response in mice after vaccine administration and its applicability to immune-stimulatory cytokine-based strategies.

Authors:  Zinnia P Parra-Guillen; Pedro Berraondo; Emmanuel Grenier; Benjamin Ribba; Iñaki F Troconiz
Journal:  AAPS J       Date:  2013-04-19       Impact factor: 4.009

5.  Repeated-measures models with constrained parameters for incomplete data in tumour xenograft experiments.

Authors:  Ming Tan; Hong-Bin Fang; Guo-Liang Tian; Peter J Houghton
Journal:  Stat Med       Date:  2005-01-15       Impact factor: 2.373

6.  Quantitative evaluation of the combination between cytotoxic drug and efflux transporter inhibitors based on a tumour growth inhibition model.

Authors:  Alexandre Sostelly; Léa Payen; Jérôme Guitton; Attilio Di Pietro; Pierre Falson; Mylène Honorat; Ahcène Boumendjel; Annabelle Gèze; Gilles Freyer; Michel Tod
Journal:  Fundam Clin Pharmacol       Date:  2013-02-06       Impact factor: 2.748

7.  Modeling of tumor growth and anticancer effects of combination therapy.

Authors:  Gilbert Koch; Antje Walz; Gezim Lahu; Johannes Schropp
Journal:  J Pharmacokinet Pharmacodyn       Date:  2009-04-22       Impact factor: 2.745

8.  Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents.

Authors:  Monica Simeoni; Paolo Magni; Cristiano Cammia; Giuseppe De Nicolao; Valter Croci; Enrico Pesenti; Massimiliano Germani; Italo Poggesi; Maurizio Rocchetti
Journal:  Cancer Res       Date:  2004-02-01       Impact factor: 12.701

9.  A mathematical model to study the effects of drugs administration on tumor growth dynamics.

Authors:  P Magni; M Simeoni; I Poggesi; M Rocchetti; G De Nicolao
Journal:  Math Biosci       Date:  2006-03-03       Impact factor: 2.144

10.  Modeling tumor response after combined administration of different immune-stimulatory agents.

Authors:  Zinnia P Parra-Guillen; Pedro Berraondo; Benjamin Ribba; Iñaki F Trocóniz
Journal:  J Pharmacol Exp Ther       Date:  2013-07-11       Impact factor: 4.030

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