Subramaniam Ravi P, Crump Kenny S, Van Landingham Cynthia, White Paul, Chen Chao, Schlosser Paul M
NCEA, ORD, U.S. Environmental Protection Agency, Washington, DC 20460, USA.
Risk Anal. 2007 Oct;27(5):1237-54. doi: 10.1111/j.1539-6924.2007.00968.x.
Scientists at the CIIT 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 CIIT 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.
CIIT健康研究中心的科学家(康诺利等人,2000年、2003年;金贝尔等人,2001年a、2001年b)开发了一种两阶段克隆扩增模型,用于研究F344大鼠中甲醛诱发的鼻腔癌,该模型大量运用了机理信息。他们建模方法的一个推断是,甲醛诱发的致癌性在无需甲醛诱变作用的情况下就能得到最佳解释。在本文中,我们检验了这一结果的可信度,并修改了部分特征以检验预测的剂量反应对特定假设的敏感性。我们对两阶段癌症模型实施了适用于非齐次模型(即参数随时间变化的模型)的解决方案,从而考虑了变量中的时间依赖性。在这次重新实施过程中,我们检验了模型预测对合并历史对照数据和同期对照数据的敏感性,以及对将偶然发现肿瘤的牺牲动物与因肿瘤死亡的动物归为一类的敏感性。我们发现,非齐次解决方案并未显著改变CIIT模型的结果。生物测定中肿瘤出现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)历史对照数据的使用限制为仅从吸入暴露获得的数据时,该模型将高达74%的额外肿瘤发生概率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,DPX浓度是与甲醛诱发突变相关的剂量指标的替代物,这促使我们使用该量的每周平均值。该模型中的各种其他生物学和数学不确定性在本次分析中未作修改予以保留。这些包括起始细胞分裂和死亡率的模型设定,以及细胞复制率剂量反应中的不确定性和变异性,这些问题将在未来的论文中探讨。