Mathematical Models for Carcinogenesis Based on the Evidence of Molecular Biology and Its Application to Data Analysis

考虑到基因组不稳定性的影响，我们开发了癌症发生和细胞死亡的多阶段模型。对于Armitage-Doll型多阶段癌变模型，对阶段数与突变率之间的关系进行了蒙特卡罗模拟。利用原子弹幸存者及其后代的后续数据，我们检验了这些模型的性质。经典的多靶点模型也被用于分析剂量-反应关系的数据。我们试着做一些扩展模型。我们所关注的目标尺寸是异质的，可以用几何级数简化。我们采用两种模型来建立多目标模型：假设响应变量服从泊松分布而建立的泊松回归模型，以及通过加入具有gamma分布的随机共同风险而得到的作为泊松混合模型的γ -脆弱性模型。基于我们研究的理论结果，我们开发了几个计算机程序来分析剂量反应数据，并将它们应用于与动物实验、临床研究和流行病学研究相关的许多实际数据集，包括原子弹幸存者的队列数据。

We developed multistage models of carcinogenesis and cell death with taking account the effect of genomic instability. As for Armitage-Doll type of multistage models for carcinogenesis, some Monte Carlo simulations on the relationship between the number of stages and mutation rate were done. Using the follow-up data among atomic-bomb survivors and offspring, we examined the property of the models.The classical multi-target models have been also considered for use in analyzing data of the dose-response relationship. We tried to make some extended models. The target sizes we are concerned with are heterogeneous as simplified using geometric progression. We apply two models for establishing the multi-target models: a Poisson regression model constructed by assuming that the response variable follows Poisson distribution, and a gamma-frailty model as a Poisson mixture model derived by adding random common risks having a gamma distribution.Based on the theoretical results of our study, we developed several computer programs for analyzing dose-response data, and applied them to many sort of real data sets related to animal experiments, clinical researches and epidemiological studies including atomic bomb survivor's cohort data.