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Hiller J, Vallejo C, Betthauser L, et al. Characteristic patterns of cancer incidence: Epidemiological data, biological theories, and multistage models. Prog Biophys Mol Biol. 2016;124:41-48doi: 10.1016/j.pbiomolbio.2016.11.002.
Hiller, J., Vallejo, C., Betthauser, L., & Keesling, J. (2017). Characteristic patterns of cancer incidence: Epidemiological data, biological theories, and multistage models. Progress in biophysics and molecular biology, 12441-48. https://doi.org/10.1016/j.pbiomolbio.2016.11.002
Hiller, Josh, et al. "Characteristic patterns of cancer incidence: Epidemiological data, biological theories, and multistage models." Progress in biophysics and molecular biology vol. 124 (2017): 41-48. doi: https://doi.org/10.1016/j.pbiomolbio.2016.11.002
Hiller J, Vallejo C, Betthauser L, Keesling J. Characteristic patterns of cancer incidence: Epidemiological data, biological theories, and multistage models. Prog Biophys Mol Biol. 2017 Mar;124:41-48. doi: 10.1016/j.pbiomolbio.2016.11.002. Epub 2016 Nov 10. PMID: 27836510.
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Prog Biophys Mol Biol. 2017 Mar;124:41-48. doi: 10.1016/j.pbiomolbio.2016.11.002. Epub 2016 Nov 10.

Characteristic patterns of cancer incidence: Epidemiological data, biological theories, and multistage models.

Progress in biophysics and molecular biology

Josh Hiller, Celeste Vallejo, Leo Betthauser, James Keesling

Affiliations

  1. Department of Mathematics, University of Florida, USA. Electronic address: [email protected].
  2. Department of Mathematics, University of Florida, USA.

PMID: 27836510 DOI: 10.1016/j.pbiomolbio.2016.11.002

Abstract

We investigate and classify several patterns in cancer incidence and relative risk data which persist across different countries and multiple published studies. We then explore biological hypotheses as well as many mathematical models in the literature that attempt to explain these patterns. A general modeling framework is presented which is general enough to model most of observed behaviors. It is our belief that this model has sufficient flexibility to be adapted to new information as it is discovered. As one application of this framework, we give a model for the effect of aging on the process of carcinogenesis.

Copyright © 2016 Elsevier Ltd. All rights reserved.

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