Reassessing benzene risks using internal doses and Monte-Carlo uncertainty analysis
Reassessing benzene risks using internal doses and Monte-Carlo uncertainty analysis
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DOI：
10.2307/3433198
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发表时间：
1996-12-01
影响因子：
10.4
通讯作者：
Cox, LA
中科院分区：
文献类型：
--
作者：
Cox, LA
苯对人类癌症的风险是根据流行病学数据估计的，并有来自动物生物测定数据的支持证据。本文利用动物和人类苯代谢的生理药代动力学（PBPK）模型重新研究了基于动物的风险评估。PBPK模型可以很好地预测小鼠灌胃实验中苯的内剂量（总苯代谢物）。数据和PBPK模型输出也可以用一个简单的非线性（Michaelis-Menten）回归模型很好地描述，正如先前Bailer和Heel[苯风险评估中基于代谢物的内剂量]所使用的那样。环境与卫生，82:177-184(1989)]。将多阶段模型族重新调整为内剂量，使小鼠的最大似然估计（MLE）剂量-反应曲线从线性二次曲线变为纯三次曲线，从而使低剂量风险估计比以前的风险评估更小。与Bailer和Heel使用种间剂量转换的研究结果相反，使用PBPK模型对人类进行内部剂量估计可以降低低剂量下的人类风险估计。敏感性分析表明，在低剂量下发现的非线性MLE剂量-反应曲线对内剂量定义的变化具有稳稳性，并且比早期的风险模型更符合流行病学数据。采用基于最大熵概率和贝叶斯条件的蒙特卡罗不确定性分析，给出了真实但未知的剂量响应函数的全概率分布。这样就可以量化低剂量斜率为正的概率：约为10%。过量风险低剂量斜率的95%置信上限也直接由后验分布得出，与之前的q(1)*值相似。这种方法表明，在足够低的剂量下，苯暴露造成的过量风险可能不存在（甚至为负）。关于苯效应的两种生物信息——药代动力学和血液毒性——被检验以检验这一发现的合理性。引入了一个将因果相关的生物学信息纳入苯风险评估的框架，结果表明，药代动力学和血液毒性模型似乎都与吸入足够低浓度的苯不会产生过量风险的假设相一致。
Human cancer risks from benzene have been estimated from epidemiological data, with supporting evidence from animal bioassay data. This article reexamines the animal-based risk assessments using physiologically based pharmacokinetic (PBPK) models of benzene metabolism in animals and humans. Internal doses (total benzene metabolites) from oral gavage experiments in mice are well predicted by the PBPK model. Both the data and the PBPK model outputs are also well described by a simple nonlinear (Michaelis-Menten) regression model, as previously used by Bailer and Heel [Metabolite-based internal doses used in risk assessment of benzene. Environ Health Perspect 82:177-184 (1989)]. Refitting the multistage model family to internal doses changes the maximum-likelihood estimate (MLE) dose-response curve for mice from linear-quadratic to purely cubic, so that low-dose risk estimates are smaller than in previous risk assessments. In contrast to Bailer and Heel's findings using interspecies dose conversion, the use of internal dose estimates for humans from a PBPK model reduces estimated human risks at low doses. Sensitivity analyses suggest that the finding of a nonlinear MLE dose-response curve at low doses is robust to changes in internal dose definitions and more consistent with epidemiological data than earlier risk models. A Monte-Carlo uncertainty analysis based on maximum-entropy probabilities and Bayesian conditioning is used to develop an entire probability distribution for the true but unknown dose-response function. This allows the probability of a positive low-dose slope to be quantified: it is about 10%. An upper 95% confidence limit on the low-dose slope of excess risk is also obtained directly from the posterior distribution and is similar to previous q(1)* values. This approach suggests that the excess risk due to benzene exposure may be nonexistent (or even negative) at sufficiently low doses. Two types of biological information about benzene effects-pharmacokinetic and hematotoxic-are examined to test the plausibility of this finding. A framework for incorporating causally relevant biological information into benzene risk assessment is introduced, and it is shown that both pharmacokinetic and hematotoxic models appear to be consistent with the hypothesis that sufficiently low concentrations of inhaled benzene do not create an excess risk.