Edler L, Poirier K, Dourson M, Kleiner J, Mileson B, Nordmann H, Renwick A, Slob W, Walton K, Würtzen G
Deutsches Krebsforschungszentrum, German Cancer Research Center, Abteilung Biostatistik R 0700, Postfach 10 19 49, D-69009, Heidelberg, Germany.
Food Chem Toxicol. 2002 Feb-Mar;40(2-3):283-326. doi: 10.1016/s0278-6915(01)00116-8.
The present review reports on the mathematical methods and statistical techniques presently available for hazard characterisation. The state of the art of mathematical modelling and quantitative methods used currently for regulatory decision-making in Europe and additional potential methods for risk assessment of chemicals in food and diet are described. Existing practices of JECFA, FDA, EPA, etc., are examined for their similarities and differences. A framework is established for the development of new and improved quantitative methodologies. Areas for refinement, improvement and increase of efficiency of each method are identified in a gap analysis. Based on this critical evaluation, needs for future research are defined. It is concluded from our work that mathematical modelling of the dose-response relationship would improve the risk assessment process. An adequate characterisation of the dose-response relationship by mathematical modelling clearly requires the use of a sufficient number of dose groups to achieve a range of different response levels. This need not necessarily lead to an increase in the total number of animals in the study if an appropriate design is used. Chemical-specific data relating to the mode or mechanism of action and/or the toxicokinetics of the chemical should be used for dose-response characterisation whenever possible. It is concluded that a single method of hazard characterisation would not be suitable for all kinds of risk assessments, and that a range of different approaches is necessary so that the method used is the most appropriate for the data available and for the risk characterisation issue. Future refinements to dose-response characterisation should incorporate more clearly the extent of uncertainty and variability in the resulting output.
本综述报告了目前可用于危害特征描述的数学方法和统计技术。描述了欧洲目前用于监管决策的数学建模和定量方法的现状,以及食品和饮食中化学品风险评估的其他潜在方法。研究了食品添加剂联合专家委员会(JECFA)、美国食品药品监督管理局(FDA)、美国环境保护局(EPA)等的现有做法,以找出它们的异同。建立了一个用于开发新的和改进的定量方法的框架。在差距分析中确定了每种方法需要改进、完善和提高效率的领域。基于这一批判性评估,确定了未来研究的需求。我们的工作得出结论,剂量-反应关系的数学建模将改善风险评估过程。通过数学建模充分表征剂量-反应关系显然需要使用足够数量的剂量组,以实现一系列不同的反应水平。如果采用适当的设计,这不一定会导致研究中动物总数的增加。只要有可能,应使用与化学品作用方式或机制和/或毒代动力学相关的特定化学品数据进行剂量-反应表征。得出的结论是,单一的危害特征描述方法不适用于所有类型的风险评估,需要一系列不同的方法,以便所使用的方法最适合可用数据和风险特征描述问题。未来对剂量-反应表征的改进应更明确地纳入结果输出中的不确定性和变异性程度。