有毒物质低剂量风险评估的线性插值算法。

D W Gaylor, R L Kodell
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引用次数: 0

摘要

为了检测物质的潜在毒性作用,通常对数量相对较少的实验动物施用相对高的剂量。即使使用大量实验动物,也不可能在低环境剂量水平下精确估计低水平的疾病发病率。然而,通过最低实验剂量水平与零之间的线性插值,可以得到凸剂量响应曲线的风险上限。提供了一种简单的数学算法,用于根据剂量反应数据进行低剂量风险评估,并对各种毒理学数据(包括但不限于致癌性)评估了该程序的性能。线性插值得到的低剂量置信限与阿米蒂奇-多尔多阶段模型得到的相似。
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Linear interpolation algorithm for low dose risk assessment of toxic substances.

In order to detect potential toxic effects of substances, relatively high doses generally are administered to relatively small numbers of laboratory animals. It is impossible to estimate low levels of disease incidence with precision at low environmental dose levels even with large numbers of laboratory animals. However, upper limits on risk can be obtained for convex dose response curves by linear interpolation between the lowest experimental dose level and zero. A simple mathematical algorithm is provided for low dose risk assessment from dose response data and the performance of this procedure is evaluated for a variety of toxicological data, including but not limited to carcinogenesis. The low dose confidence limits resulting from linear interpolation are similar to those obtained from the Armitage-Doll multistage model.

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