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New stochastic carcinogenesis model with covariates: an approach involving intracellular barrier mechanisms.

Publication ,  Journal Article
Akushevich, I; Veremeyeva, G; Kravchenko, J; Ukraintseva, S; Arbeev, K; Akleyev, AV; Yashin, AI
Published in: Math Biosci
March 2012

In this paper we present a new multiple-pathway stochastic model of carcinogenesis with potential of predicting individual incidence risks on the basis of biomedical measurements. The model incorporates the concept of intracellular barrier mechanisms in which cell malignization occurs due to an inefficient operation of barrier cell mechanisms, such as antioxidant defense, repair systems, and apoptosis. Mathematical formalism combines methodological innovations of mechanistic carcinogenesis models and stochastic process models widely used in studying biodemography of aging and longevity. An advantage of the modeling approach is in the natural combining of two types of measures expressed in terms of model parameters: age-specific hazard rate and means of barrier states. Results of simulation studies allow us to conclude that the model parameters can be estimated in joint analyses of epidemiological data and newly collected data on individual biomolecular measurements of barrier states. Respective experimental designs for such measurements are suggested and discussed. An analytical solution is obtained for the simplest design when only age-specific incidence rates are observed. Detailed comparison with TSCE model reveals advantages of the approach such as the possibility to describe decline in risk at advanced ages, possibilities to describe heterogeneous system of intermediate cells, and perspectives for individual prognoses of cancer risks. Application of the results to fit the SEER data on cancer risks demonstrates a strong predictive power of the model. Further generalizations of the model, opportunities to measure barrier systems, biomedical and mathematical aspects of the new model are discussed.

Duke Scholars

Published In

Math Biosci

DOI

EISSN

1879-3134

Publication Date

March 2012

Volume

236

Issue

1

Start / End Page

16 / 30

Location

United States

Related Subject Headings

  • Stochastic Processes
  • SEER Program
  • Models, Statistical
  • Models, Biological
  • Humans
  • Computer Simulation
  • Cell Transformation, Neoplastic
  • Bioinformatics
  • 49 Mathematical sciences
  • 31 Biological sciences
 

Citation

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Akushevich, I., Veremeyeva, G., Kravchenko, J., Ukraintseva, S., Arbeev, K., Akleyev, A. V., & Yashin, A. I. (2012). New stochastic carcinogenesis model with covariates: an approach involving intracellular barrier mechanisms. Math Biosci, 236(1), 16–30. https://doi.org/10.1016/j.mbs.2011.12.002
Akushevich, Igor, Galina Veremeyeva, Julia Kravchenko, Svetlana Ukraintseva, Konstantin Arbeev, Alexander V. Akleyev, and Anatoly I. Yashin. “New stochastic carcinogenesis model with covariates: an approach involving intracellular barrier mechanisms.Math Biosci 236, no. 1 (March 2012): 16–30. https://doi.org/10.1016/j.mbs.2011.12.002.
Akushevich I, Veremeyeva G, Kravchenko J, Ukraintseva S, Arbeev K, Akleyev AV, et al. New stochastic carcinogenesis model with covariates: an approach involving intracellular barrier mechanisms. Math Biosci. 2012 Mar;236(1):16–30.
Akushevich, Igor, et al. “New stochastic carcinogenesis model with covariates: an approach involving intracellular barrier mechanisms.Math Biosci, vol. 236, no. 1, Mar. 2012, pp. 16–30. Pubmed, doi:10.1016/j.mbs.2011.12.002.
Akushevich I, Veremeyeva G, Kravchenko J, Ukraintseva S, Arbeev K, Akleyev AV, Yashin AI. New stochastic carcinogenesis model with covariates: an approach involving intracellular barrier mechanisms. Math Biosci. 2012 Mar;236(1):16–30.
Journal cover image

Published In

Math Biosci

DOI

EISSN

1879-3134

Publication Date

March 2012

Volume

236

Issue

1

Start / End Page

16 / 30

Location

United States

Related Subject Headings

  • Stochastic Processes
  • SEER Program
  • Models, Statistical
  • Models, Biological
  • Humans
  • Computer Simulation
  • Cell Transformation, Neoplastic
  • Bioinformatics
  • 49 Mathematical sciences
  • 31 Biological sciences