Center for Population Health and Aging, Duke University, Durham, NC 27708, USA.
Math Biosci. 2012 Mar;236(1):16-30. doi: 10.1016/j.mbs.2011.12.002. Epub 2011 Dec 17.
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.
本文提出了一种新的多途径随机致癌模型,该模型具有预测个体发病风险的潜力,其预测依据是基于生物医学测量的个体发病风险。该模型将细胞内的屏障机制概念纳入其中,即由于屏障细胞机制(如抗氧化防御、修复系统和细胞凋亡)的运作效率低下,导致细胞恶性转化。数学形式主义将机制致癌模型和在研究衰老和长寿的生物人口统计学中广泛使用的随机过程模型的方法创新结合在一起。该建模方法的一个优点是可以自然地将两种类型的测量值结合在一起,这两种类型的测量值都用模型参数表示:特定年龄的危险率和屏障状态的平均值。模拟研究的结果使我们能够得出结论,即可以通过对流行病学数据和新收集的个体生物分子屏障状态测量值的联合分析来估计模型参数。针对这些测量值,提出了相应的实验设计,并进行了讨论。当仅观察到特定年龄的发病率时,获得了最简单设计的解析解。与 TSCE 模型的详细比较揭示了该方法的优势,例如在高龄时描述风险下降的可能性、描述异质中间细胞系统的可能性以及进行癌症风险个体预后的可能性。将研究结果应用于拟合 SEER 癌症风险数据表明,该模型具有很强的预测能力。进一步推广模型、测量屏障系统的机会、该新模型的生物医学和数学方面都进行了讨论。