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首页> 外文期刊>Risk analysis >Uncertainties in the CIIT Model for Formaldehyde-Induced Carcinogenicity in the Rat: A Limited Sensitivity Analysis-I
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Uncertainties in the CIIT Model for Formaldehyde-Induced Carcinogenicity in the Rat: A Limited Sensitivity Analysis-I

机译:CIIT模型中大鼠甲醛致癌性的不确定性:有限的敏感性分析-I

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摘要

Scientists at the CUT Centers for Health Research (Conolly et al, 2000, 2003; Kimbell et al, 2001a, 2001b) developed a two-stage clonal expansion model of formaldehyde-induced nasal cancers in the F344 rat that made extensive use of mechanistic information. An inference of their modeling approach was that formaldehyde-induced tumorigenicity could be optimally explained without the role of formaldehyde's mutagenic action. In this article, we examine the strength of this result and modify select features to examine the sensitivity of the predicted dose response to select assumptions. We implement solutions to the two-stage cancer model that are valid for nonhomogeneous models (i.e., models with time-dependent parameters), thus accounting for time dependence in variables. In this reimplementation, we examine the sensitivity of model predictions to pooling historical and concurrent control data, and to lumping sacrificed animals in which tumors were discovered incidentally with those in which death was caused by the tumors. We found the CUT model results were not significantly altered with the nonhomogeneous solutions. Dose-response predictions below the range of exposures where tumors occurred in the bioassays were highly sensitive to the choice of control data. In the range of exposures where tumors were observed, the model attributed up to 74% of the added tumor probability to formaldehyde's mutagenic action when our reanalysis restricted the use of the National Toxicology Program (NTP) historical control data to only those obtained from inhalation exposures. Model results were insensitive to hourly or daily temporal variations in DNA protein cross-link (DPX) concentration, a surrogate for the dose-metric linked to formaldehyde-induced mutations, prompting us to utilize weekly averages for this quantity. Various other biological and mathematical uncertainties in the model have been retained unmodified in this analysis. These include model specification of initiated cell division and death rates, and uncertainty and variability in the dose response for cell replication rates, issues that will be considered in a future paper.
机译:CUT健康研究中心的科学家(Conolly等,2000,2003; Kimbell等,2001a,2001b)在F344大鼠中开发了甲醛诱导的鼻癌的两阶段克隆扩增模型,该模型广泛使用了机械信息。他们建模方法的一个推论是,甲醛诱导的致瘤性可以在没有甲醛诱变作用的情况下得到最佳解释。在本文中,我们检查了此结果的强度,并修改了选择功能以检查预测的剂量响应对选择假设的敏感性。我们对两阶段癌症模型实施对非均质模型有效的解决方案(即具有随时间变化的参数的模型),从而解决了变量中随时间变化的问题。在此重新实现中,我们检查了模型预测对合并历史数据和并行控制数据,以及将那些偶然发现肿瘤的死动物与那些由于肿瘤导致死亡的动物混在一起的敏感性。我们发现,非均匀解的CUT模型结果没有显着改变。在生物测定中发生肿瘤的暴露范围以下的剂量反应预测对对照数据的选择高度敏感。在观察到肿瘤的暴露范围内,当我们的重新分析将国家毒理学计划(NTP)历史控制数据的使用仅限于通过吸入暴露获得的数据时,该模型将高达74%的增加的肿瘤可能性归因于甲醛的诱变作用。 。模型结果对DNA蛋白质交联(DPX)浓度的每小时或每日时间变化不敏感,这是与甲醛诱导的突变相关的剂量度量的替代,促使我们利用每周平均值作为该量。在此分析中,模型中的各种其他生物学和数学不确定性均保持不变。这些包括启动细胞分裂和死亡率的模型规范,以及细胞复制速率的剂量反应的不确定性和可变性,这些问题将在以后的论文中进行讨论。

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