人群接触致癌物的计算机模拟:以法国石棉和间皮瘤死亡率为例

Alireza Banaei , Bertran Auvert , Marcel Goldberg
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引用次数: 6

摘要

癌变的多阶段理论允许建立模型,将个体在特定年龄诊断出肿瘤的概率作为个体过去暴露于致癌物剂(暴露水平与年龄)、暴露后的时间和年龄的函数。当对某种致癌物的接触及其在发病率和死亡率方面的影响以一般人群的规模为模型时,通常必须对个体接触进行估计。如果没有适当的数据,这项艰巨的任务就需要进行昂贵和困难的调查。我们在这里提出了一种方法,该方法允许在不知道单个暴露的情况下对全局暴露进行建模。该方法用于对法国男性人口的石棉暴露进行建模并计算间皮瘤死亡率(间皮瘤是一种癌症,石棉是其唯一致癌物,存在基于多阶段致癌理论的风险函数)。这种方法假设所有个体的暴露函数(暴露水平如何随年龄变化)都是相同的,只有一个参数例外。也就是说,它利用了一个假设,我们称之为标准暴露窗口假设(SEW)。我们使用了两种方法来计算间皮瘤死亡的概率,在法国男性人群的代表性样本中,他们的个人石棉暴露史是已知的:我们将风险函数应用于所有个体,我们应用了SEW假设。两种方法得到的死亡人数非常接近,与观察到的死亡数据吻合得很好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer Modeling of Population Exposure to a Carcinogen: The Example of Asbestos and Mesothelioma Mortality in France

The multistage theory of carcinogenesis allows models to be constructed that provide the individual probability of a diagnosed tumor at a given age as a function of the person's past exposure to carcinogenic agents (exposure level versus age), the time since exposure, and age. When exposure to a carcinogenic agent and its impact in terms of morbidity and mortality are modeled on the scale of the general population, individual exposures must often be estimated. If appropriate data do not already exist, this difficult task necessitates expensive and difficult investigations. We propose here a method that allows this global exposure to be modeled without needing to know the individual exposures. The method is used and illustrated in the context of modeling the asbestos exposure of the French male population and calculating its mortality rate from mesothelioma (a type of cancer for which asbestos is the only carcinogen and for which a risk function based on the multistage theory of carcinogenesis exists). This method assumes that the exposure functions (how exposure levels vary with age) for all individuals are the same, with the exception of one parameter. That is, it utilizes a hypothesis that we called the hypothesis of the Standard Exposure Window (SEW). We used two methods to calculate the probability of death from mesothelioma in a representative sample of the French male population for whom individual histories of asbestos exposure are known: we applied the risk function to all the individuals, and we applied the SEW hypothesis. The number of deaths obtained by the two methods are very close and fit the observed mortality data satisfactorily.

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