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Reassessing benzene risks using internal doses and Monte-Carlo uncertainty analysis.

机译:使用内部剂量和蒙特卡洛不确定性分析重新评估苯风险。

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摘要

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 Hoel [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 Hoel'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 q1* 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 and excess risk.
机译:苯的人类癌症风险已根据流行病学数据进行了估算,并获得了动物生物测定数据的佐证。本文使用动物和人体内苯代谢的基于生理的药代动力学(PBPK)模型,重新审查了基于动物的风险评估。 PBPK模型可以很好地预测小鼠经口管饲实验的内部剂量(总苯代谢物)。数据和PBPK模型的输出结果也可以通过简单的非线性(Michaelis-Menten)回归模型很好地描述,该模型以前曾由Bailer和Hoel [基于代谢物的内部剂量用于苯风险评估]。 Environ Health Perspect 82:177-184(1989)]。将多阶段模型族调整为内部剂量后,小鼠的最大似然估计(MLE)剂量反应曲线将从线性二次方变为纯立方,因此低剂量风险估计值比以前的风险评估小。与Bailer和Hoel使用种间剂量转换的发现相反,使用PBPK模型对人的内部剂量估计值可降低低剂量时估计的人为风险。敏感性分析表明,在低剂量下发现非线性MLE剂量反应曲线对于内部剂量定义的变化是可靠的,并且比流行病学数据与早期风险模型更一致。基于最大熵概率和贝叶斯条件的蒙特卡洛不确定性分析用于为真实但未知的剂量反应函数建立完整的概率分布。这样就可以量化出低剂量正斜率的可能性:大约为10%。还可以直接从后验分布中获得过量风险的低剂量斜率的95%置信上限,该可信度上限与先前的q1 *值相似。这种方法表明,在足够低的剂量下,苯暴露引起的额外风险可能不存在(甚至是负面的)。研究了关于苯影响的两种生物学信息-药代动力学和血液毒性-以检验这一发现的合理性。引入了将因果相关生物学信息纳入苯风险评估的框架,结果表明,药代动力学模型和血液毒性模型均与以下假设相符:吸入苯的浓度足够低不会产生过量风险。

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