Literature DB >> 26757730

Improvement of Parameter Estimations in Tumor Growth Inhibition Models on Xenografted Animals: a Novel Method to Handle the Interval Censoring Caused by Measurement of Smaller Tumors.

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

Abstract

The purpose of this study was to explore the interval censoring induced by caliper measurements on smaller tumors during tumor growth experiments in preclinical studies and to show its impact on parameter estimations. A new approach, the so-called interval-M3 method, is proposed to specifically handle this type of data. Thereby, the interval-M3 method was challenged with different methods (including classical methods for handling below quantification limit values) using Stochastic Simulation and Estimation process to take into account the censoring. In this way, 1000 datasets were simulated under the design of a typical of tumor growth study in xenografted mice, and then, each method was used for parameter estimation on the simulated datasets. Relative bias and relative root mean square error (relative RMSE) were consequently computed for comparison purpose. By not considering the censoring, parameter estimations appeared to be biased and particularly the cytotoxic effect parameter, k 2 , which is the parameter of interest to characterize the efficacy of a compound in oncology. The best performance was noted with the interval-M3 method which properly takes into account the interval censoring induced by caliper measurement, giving overall unbiased estimations for all parameters and especially for the antitumor effect parameter (relative bias = 0.49%, and relative RMSE = 4.06%).

Entities:  

Keywords:  below quantification limit; interval censoring; interval-M3 method; simultaneous modeling continuous and categorical data; xenograft model

Mesh:

Year:  2016        PMID: 26757730      PMCID: PMC4779108          DOI: 10.1208/s12248-015-9862-1

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


  15 in total

1.  Ways to fit a PK model with some data below the quantification limit.

Authors:  S L Beal
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-10       Impact factor: 2.745

2.  Perl-speaks-NONMEM (PsN)--a Perl module for NONMEM related programming.

Authors:  Lars Lindbom; Jakob Ribbing; E Niclas Jonsson
Journal:  Comput Methods Programs Biomed       Date:  2004-08       Impact factor: 5.428

3.  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

4.  Derivation of various NONMEM estimation methods.

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

5.  Predicting the active doses in humans from animal studies: a novel approach in oncology.

Authors:  M Rocchetti; M Simeoni; E Pesenti; G De Nicolao; I Poggesi
Journal:  Eur J Cancer       Date:  2007-07-02       Impact factor: 9.162

6.  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

7.  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

Review 8.  Contributions of human tumor xenografts to anticancer drug development.

Authors:  Edward A Sausville; Angelika M Burger
Journal:  Cancer Res       Date:  2006-04-01       Impact factor: 12.701

9.  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

10.  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

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  3 in total

1.  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.

Authors:  Philippe B Pierrillas; Michel Tod; Magali Amiel; Marylore Chenel; Emilie Henin
Journal:  AAPS J       Date:  2016-06-21       Impact factor: 4.009

2.  A replication-incompetent CD154/40L recombinant vaccinia virus induces direct and macrophage-mediated antitumor effects in vitro and in vivo.

Authors:  Valeria Governa; Alvaro Brittoli; Valentina Mele; Maurizio Pinamonti; Luigi Terracciano; Simone Muenst; Giandomenica Iezzi; Giulio Cesare Spagnoli; Paul Zajac; Emanuele Trella
Journal:  Oncoimmunology       Date:  2019-02-14       Impact factor: 8.110

3.  Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice.

Authors:  Won-Ho Kang; Hyo-Jeong Ryu; Seongsung Kwak; Hwi-Yeol Yun
Journal:  Front Pharmacol       Date:  2022-01-04       Impact factor: 5.810

  3 in total

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