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Benchmark dose calculation from epidemiological data.

机译:根据流行病学数据计算基准剂量。

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摘要

A threshold for dose-dependent toxicity is crucial for standards setting but may not be possible to specify from empirical studies. Crump (1984) instead proposed calculating the lower statistical confidence bound of the benchmark dose, which he defined as the dose that causes a small excess risk. This concept has several advantages and has been adopted by regulatory agencies for establishing safe exposure limits for toxic substances such as mercury. We have examined the validity of this method as applied to an epidemiological study of continuous response data associated with mercury exposure. For models that are linear in the parameters, we derived an approximative expression for the lower confidence bound of the benchmark dose. We find that the benchmark calculations are highly dependent on the choice of the dose-effect function and the definition of the benchmark dose. We therefore recommend that several sets of biologically relevant default settings be used to illustrate the effect on the benchmark results and to stimulate research that will guide an a priori choice of proper default settings.
机译:剂量依赖性毒性的阈值对于标准制定至关重要,但根据经验研究可能无法确定。相反,Crump(1984)提议计算基准剂量的统计下限,他将基准剂量定义为引起较小过量风险的剂量。该概念具有多个优点,并已被监管机构采用,以建立有毒物质(例如汞)的安全暴露极限。我们已经检验了该方法用于与汞接触有关的连续反应数据的流行病学研究的有效性。对于参数线性的模型,我们导出了基准剂量下置信界的近似表达式。我们发现基准计算高度依赖于剂量效应函数的选择和基准剂量的定义。因此,我们建议使用几组生物学上相关的默认设置来说明对基准结果的影响,并刺激研究工作,以指导先验选择合适的默认设置。

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