Louisiana Tech University, Ruston, Louisiana 71272-0046, USA.
Environ Health Perspect. 2010 Mar;118(3):387-93. doi: 10.1289/ehp.0901250. Epub 2009 Oct 23.
The National Research Council (NRC) Committee on Improving Risk Analysis Approaches Used by the U.S. EPA (Environmental Protection Agency) recommended that low-dose risks be estimated in some situations using human variability distributions (HVDs). HVD modeling estimates log-normal distributions from data on pharmacokinetic and pharmacodynamic variables that affect individual sensitivities to the toxic response. These distributions are combined into an overall log-normal distribution for the threshold dose (dose below which there is no contribution to a toxic response) by assuming the variables act independently and multiplicatively. This distribution is centered at a point-of-departure dose that is usually estimated from animal data. The resulting log-normal distribution is used to quantify low-dose risk.
We examined the implications of various assumptions in HVD modeling for estimating low-dose risk.
The assumptions and data used in HVD modeling were subjected to rigorous scrutiny.
We found that the assumption that the variables affecting human sensitivity vary log normally is not scientifically defensible. Other distributions that are equally consistent with the data provide very different estimates of low-dose risk. HVD modeling can also involve an assumption that a threshold dose defined by dichotomizing a continuous apical response has a log-normal distribution. This assumption is shown to be incompatible (except under highly specialized conditions) with assuming that the continuous apical response itself is log normal. However, the two assumptions can lead to very different estimates of low-dose risk. The assumption in HVD modeling that the threshold dose can be expressed as a function of a product of independent variables lacks phenomenological support. We provide an example that shows that this assumption is generally invalid.
In view of these problems, we recommend caution in the use of HVD modeling as a general approach to estimating low-dose risks from human exposures to toxic chemicals.
美国国家研究委员会(NRC)环境环保局(EPA)提高风险分析方法使用能力委员会建议,在某些情况下,使用人体变异分布(HVD)来估计低剂量风险。HVD 建模从影响个体对毒性反应敏感性的药代动力学和药效学变量的数据中估计对数正态分布。这些分布通过假设变量独立且呈乘法作用而组合成一个总体对数正态分布,用于阈值剂量(低于该剂量不会对毒性反应产生贡献)。该分布以通常从动物数据中估计的起始剂量点为中心。由此产生的对数正态分布用于量化低剂量风险。
我们研究了 HVD 建模中各种假设对估计低剂量风险的影响。
严格审查了 HVD 建模中使用的假设和数据。
我们发现,影响人类敏感性的变量呈对数正态分布的假设在科学上是站不住脚的。与数据同样一致的其他分布提供了非常不同的低剂量风险估计。HVD 建模还可能涉及一个假设,即通过将连续的顶端反应二分法定义的阈值剂量具有对数正态分布。该假设与假设连续顶端反应本身呈对数正态分布不兼容(除非在高度专门的条件下)。然而,这两个假设可以导致非常不同的低剂量风险估计。HVD 建模中假设阈值剂量可以表示为独立变量乘积的函数缺乏现象学支持。我们提供了一个示例,表明该假设通常是无效的。
鉴于这些问题,我们建议谨慎使用 HVD 建模作为从人类接触有毒化学物质估计低剂量风险的一般方法。