Evidence map›Paper›PMID 22200574›Full record

ArticleMathematical biosciences2012

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

Igor Akushevich, Galina Veremeyeva, Julia Kravchenko, Svetlana Ukraintseva, Konstantin Arbeev, Alexander V Akleyev, Anatoly I Yashin

Open access · greenAbstract readComparative Study
In one paragraph

Article in Mathematical biosciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Igor AkushevichCenter for Population Health and Aging, Duke University, Durham, NC 27708, USA. igor.akushevich@duke.edu
Galina Veremeyeva
Julia Kravchenko
Svetlana Ukraintseva
Konstantin Arbeev
Alexander V Akleyev
Anatoly I Yashin
Duke University · USUrals Research Center for Radiation Medicine · RU

Funding

Healthy Life at Risk: The Role of SenescenceR01AG028259 · NIA · DUKE UNIVERSITY · PI YASHIN, ANATOLIY I · 2005 to 2009
$1.2M
The future of major geriatric disorders in the US elderlyR01AG032319 · NIA · DUKE UNIVERSITY · PI YASHIN, ANATOLIY I · 2008 to 2012
$1.1M
New Methods of Studying Aging, Health and Longevity: Combining Longitudinal DataR01AG030198 · NIA · DUKE UNIVERSITY · PI YASHIN, ANATOLIY I · 2009 to 2010
$779k
NIA NIH HHS R01 AG028259NIA NIH HHS R01AG028259NIA NIH HHS R01 AG030198NIA NIH HHS R01AG030198NIA NIH HHS R01 AG032319NIA NIH HHS R01AG032319
6 · The paper itself

Abstract

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.

Indexed as

Models, BiologicalCell Transformation, NeoplasticComputer SimulationHumansModels, StatisticalSEER ProgramStochastic Processes

Identifiers

PMID22200574
PMCPMC3806491
OpenAlexW2044043681

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.