Literature DB >> 11846637

Testing extrapolation of a biologically based exposure-response model from in vitro to in vivo conditions.

M Mebust1, D Crawford-Brown, W Hofmann, H Schöllnberger.   

Abstract

Models of carcinogenesis may become so flexible as to preclude the possibility of being falsified by data. This problem is removed in part by stronger biophysical specification of processes and parameters within the model prior to fitting to in vivo data on the relationship between exposure and cancer incidence. This paper explores the use of a biophysical model of chromosomal damage, cellular transformation, repair, mitosis, initiation, promotion, progression, and cytotoxicity in developing exposure-response models for radiation-induced cancer. Many of the aspects of model form and parameter values are developed from in vitro data, and the model then is extrapolated to the in vivo setting using a dosimetric model to account for dose inhomogeneity within the lung tissue of rats exposed to radon progeny in air. The ability of the model to predict cancer incidence in the rats is assessed and is shown to be problematic at higher doses. This calls into question whether a full claim may be made about the ability of first-principle models to fully constrain models applied to in vivo data at present. Possible explanations for the discrepancy, and implications for extrapolation, are provided.
© 2002 Elsevier Science (USA).

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Year:  2002        PMID: 11846637     DOI: 10.1006/rtph.2001.1516

Source DB:  PubMed          Journal:  Regul Toxicol Pharmacol        ISSN: 0273-2300            Impact factor:   3.271


  7 in total

1.  Protective bystander effects simulated with the state-vector model.

Authors:  Helmut Schöllnberger; Peter M Eckl
Journal:  Dose Response       Date:  2007-06-26       Impact factor: 2.658

2.  Modeling Dose-response at Low Dose: A Systems Biology Approach for Ionization Radiation.

Authors:  Yuchao Zhao; Paolo F Ricci
Journal:  Dose Response       Date:  2010-03-18       Impact factor: 2.658

Review 3.  IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making.

Authors:  Xiaoqing Chang; Yu-Mei Tan; David G Allen; Shannon Bell; Paul C Brown; Lauren Browning; Patricia Ceger; Jeffery Gearhart; Pertti J Hakkinen; Shruti V Kabadi; Nicole C Kleinstreuer; Annie Lumen; Joanna Matheson; Alicia Paini; Heather A Pangburn; Elijah J Petersen; Emily N Reinke; Alexandre J S Ribeiro; Nisha Sipes; Lisa M Sweeney; John F Wambaugh; Ronald Wange; Barbara A Wetmore; Moiz Mumtaz
Journal:  Toxics       Date:  2022-05-01

4.  A new view of radiation-induced cancer: integrating short- and long-term processes. Part I: approach.

Authors:  Igor Shuryak; Philip Hahnfeldt; Lynn Hlatky; Rainer K Sachs; David J Brenner
Journal:  Radiat Environ Biophys       Date:  2009-06-18       Impact factor: 1.925

5.  Low-dose radiation and genotoxic chemicals can protect against stochastic biological effects.

Authors:  Bobby R Scott; Dale M Walker; Vernon E Walker
Journal:  Nonlinearity Biol Toxicol Med       Date:  2004-07

6.  A model for the induction of chromosome aberrations through direct and bystander mechanisms.

Authors:  H Schöllnberger; R E J Mitchel; D J Crawford-Brown; W Hofmann
Journal:  Radiat Prot Dosimetry       Date:  2006-12-13       Impact factor: 0.972

Review 7.  Minimizing second cancer risk following radiotherapy: current perspectives.

Authors:  John Ng; Igor Shuryak
Journal:  Cancer Manag Res       Date:  2014-12-17       Impact factor: 3.989

  7 in total

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