Crump K S
ICF-Kaiser, Ruston, Louisiana 71270, USA.
Hum Exp Toxicol. 1996 Oct;15(10):787-98. doi: 10.1177/096032719601501001.
The linearized multistage (LMS) model has for over 15 years been the default dose-response model used by the U.S. Environmental Protection Agency (USEPA) and other federal and state regulatory agencies in the United States for calculating quantitative estimates of low-dose carcinogenic risks from animal data. The LMS model is in essence a flexible statistical model that can describe both linear and non-linear dose-response patterns, and that produces an upper confidence bound on the linear low-dose slope of the dose-response curve. Unlike its namesake, the Armitage-Doll multistage model, the parameters of the LMS do not correspond to actual physiological phenomena. Thus the LMS is 'biological' only to the extent that the true biological dose response is linear at low dose and that low-dose slope is reflected in the experimental data. If the true dose response is non-linear the LMS upper bound may overestimate the true risk by many orders of magnitude. However, competing low-dose extrapolation models, including those derived from 'biologically-based models' that are capable of incorporating additional biological information, have not shown evidence to date of being able to produce quantitative estimates of low-dose risks that are any more accurate than those obtained from the LMS model. Further, even if these attempts were successful, the extent to which more accurate estimates of low-dose risks in a test animal species would translate into improved estimates of human risk is questionable. Thus, it does not appear possible at present to develop a quantitative approach that would be generally applicable and that would offer significant improvements upon the crude bounding estimates of the type provided by the LMS model. Draft USEPA guidelines for cancer risk assessment incorporate an approach similar to the LMS for carcinogens having a linear mode of action. However, under these guidelines quantitative estimates of low-dose risks would not be developed for carcinogens having a non-linear mode of action; instead dose-response modelling would be used in the experimental range to calculate an LED10* (a statistical lower bound on the dose corresponding to a 10% increase in risk), and safety factors would be applied to the LED10* to determine acceptable exposure levels for humans. This approach is very similar to the one presently used by USEPA for non-carcinogens. Rather than using one approach for carcinogens believed to have a linear mode of action and a different approach for all other health effects, it is suggested herein that it would be more appropriate to use an approach conceptually similar to the 'LED10*-safety factor' approach for all health effects, and not to routinely develop quantitative risk estimates from animal data.
线性化多阶段（LMS）模型15年来一直是美国环境保护局（USEPA）以及美国其他联邦和州监管机构用于根据动物数据计算低剂量致癌风险定量估计值的默认剂量反应模型。LMS模型本质上是一个灵活的统计模型，它可以描述线性和非线性剂量反应模式，并能给出剂量反应曲线线性低剂量斜率的上置信界。与它的同名模型——阿米蒂奇 - 多尔多阶段模型不同，LMS模型的参数并不对应于实际的生理现象。因此，LMS模型只是在低剂量下真实的生物学剂量反应是线性的且低剂量斜率反映在实验数据中的程度上才具有“生物学意义”。如果真实的剂量反应是非线性的，那么LMS模型的上界可能会高估真实风险许多个数量级。然而，包括那些源自能够纳入更多生物学信息的“基于生物学的模型”的竞争性低剂量外推模型，到目前为止尚未有证据表明它们能够得出比从LMS模型获得的低剂量风险定量估计更准确的结果。此外，即使这些尝试成功了，在实验动物物种中更准确的低剂量风险估计能在多大程度上转化为对人类风险的更好估计也值得怀疑。因此，目前似乎不可能开发出一种普遍适用且能在LMS模型提供的粗略边界估计基础上有显著改进的定量方法。USEPA癌症风险评估指南草案针对具有线性作用模式的致癌物采用了一种类似于LMS模型的方法。然而，根据这些指南，对于具有非线性作用模式的致癌物不会进行低剂量风险的定量估计；取而代之的是，剂量反应模型将用于实验范围内以计算LED10*（对应风险增加10%的剂量的统计下限），并且安全系数将应用于LED10以确定人类可接受的暴露水平。这种方法与USEPA目前用于非致癌物的方法非常相似。本文建议，对于所有健康影响，使用一种在概念上类似于“LED10 - 安全系数”方法的途径，而不是常规地从动物数据中得出定量风险估计，而不是针对被认为具有线性作用模式的致癌物采用一种方法，而对所有其他健康影响采用不同的方法。
