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毒性测试精度不确定性的核算:界定边界范围的方法及对化学品危害评估的影响。

Accounting for Precision Uncertainty of Toxicity Testing: Methods to Define Borderline Ranges and Implications for Hazard Assessment of Chemicals.

机构信息

Department of Social Sciences, Wageningen University & Research, Hollandseweg 1, Wageningen, 6700 EW, The Netherlands.

BASF SE, Ludwigshafen am Rhein, Germany.

出版信息

Risk Anal. 2022 Feb;42(2):224-238. doi: 10.1111/risa.13648. Epub 2020 Dec 9.

DOI:10.1111/risa.13648
PMID:33300210
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9292900/
Abstract

For hazard classifications of chemicals, continuous data from animal- or nonanimal testing methods are often dichotomized into binary positive/negative outcomes by defining classification thresholds (CT). Experimental data are, however, subject to biological and technical variability. Each test method's precision is limited resulting in uncertainty of the positive/negative outcome if the experimental result is close to the CT. Borderline ranges (BR) around the CT were suggested, which represent ranges in which the study result is ambiguous, that is, positive or negative results are equally likely. The BR reflects a method's precision uncertainty. This article explores and compares different approaches to quantify the BR. Besides using the pooled standard deviation, we determine the BR by means of the median absolute deviation (MAD), with a sequential combination of both methods, and by using nonparametric bootstrapping. Furthermore, we quantify the BR for different hazardous effects, including nonanimal tests for skin corrosion, eye irritation, skin irritation, and skin sensitization as well as for an animal test on skin sensitization (the local lymph node assay, LLNA). Additionally, for one method (direct peptide reactivity assay) the BR was determined experimentally and compared to calculated BRs. Our results demonstrate that (i) the precision of the methods is determining the size of their BRs, (ii) there is no "perfect" method to derive a BR, alas, (iii) a consensus on BR is needed to account for the limited precision of testing methods.

摘要

对于化学品的危害分类,动物或非动物测试方法的连续数据通常通过定义分类阈值 (CT) 分为二进制阳性/阴性结果。然而,实验数据受到生物和技术变异性的影响。由于每种测试方法的精度都有限,如果实验结果接近 CT,则阳性/阴性结果的不确定性就会增加。因此,人们建议在 CT 周围设置边界范围 (BR),这代表研究结果存在模糊性的范围,即阳性和阴性结果的可能性相同。BR 反映了方法的精度不确定性。本文探讨并比较了量化 BR 的不同方法。除了使用汇总标准差外,我们还通过中位数绝对偏差 (MAD)、两种方法的顺序组合以及非参数引导来确定 BR。此外,我们还针对不同的危害效应量化了 BR,包括非动物测试的皮肤腐蚀、眼睛刺激、皮肤刺激和皮肤致敏,以及皮肤致敏的动物测试(局部淋巴结测定法,LLNA)。此外,对于一种方法(直接肽反应性测定法),我们还通过实验确定了 BR,并将其与计算出的 BR 进行了比较。我们的研究结果表明:(i)方法的精度决定了其 BR 的大小;(ii)目前没有“完美”的方法来确定 BR;(iii)为了考虑测试方法的有限精度,需要对 BR 达成共识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c32f/9292900/f115cbd5b41b/RISA-42-224-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c32f/9292900/fdca87784075/RISA-42-224-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c32f/9292900/14b1be7e7448/RISA-42-224-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c32f/9292900/f115cbd5b41b/RISA-42-224-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c32f/9292900/fdca87784075/RISA-42-224-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c32f/9292900/14b1be7e7448/RISA-42-224-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c32f/9292900/f115cbd5b41b/RISA-42-224-g002.jpg

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The impact of precision uncertainty on predictive accuracy metrics of non-animal testing methods.精准不确定性对非动物测试方法预测准确性指标的影响。
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Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility.
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