Department of Environmental Science, Radboud University, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands.
Ecotoxicol Environ Saf. 2012 Jun;80:238-43. doi: 10.1016/j.ecoenv.2012.03.005. Epub 2012 Apr 6.
For warm-blooded species, the hazardous dose of a chemical (HD50) is an upcoming and important characteristic in the assessment of toxic chemicals. Generally, experimental information is available for a limited number of warm-blooded species only, which causes statistical uncertainty. Furthermore, when small datasets contain an unrepresentative sample of species, they can cause systematic uncertainty in chemicals' hazardous doses. The number of species can be enlarged with interspecies correlation estimation (ICE) models, but these are uncertain themselves. The goal of this study is to quantify the possible gain in reliability of the HD50 values for warm-blooded wildlife species after enlargement of the sample size with ICE predictions. For 1137 chemicals, we compared systematic uncertainty and statistical uncertainty between HD50 values based on experimental data (HD50(Ex)) and on datasets combining experimental data and ICE predictions (HD50(Co)). HD50(Ex) values ranged between 1.0×10(-1) and 9.5×10(3)mgkg(wwt)(-1), and HD50(Co) values between 1.1×10(0) and 6.1×10(3)mgkg(wwt)(-1). For over 97 percent of the chemicals, HD50(Ex) values exceeded HD50(Co) values, with a systematic uncertainty (i.e. the ratio of HD50(Ex)/HD50(Co)) of typically 3.5. The limited availability of experimental toxicity data, predominantly for mammals, resulted in a systematic underestimation of the wildlife toxicity of a chemical. Statistical uncertainty factors (i.e. the ratio of the 95th/5th percentile) quantified the statistical uncertainty in the HD50 values. The statistical uncertainty factors ranged between 1.0×10(0) and 2.5×10(22) for the experimental dataset, and between 4.8×10(0) and 1.1×10(2) for the combined dataset. For all sample sizes, median statistical uncertainty factors were the largest for combined datasets. However, combining experimental toxicity data with ICE predictions makes it possible to reduce the upper limit of the range for statistical uncertainty factors. We conclude that, by combining experimental data with ICE model predictions, the validity of the HD50 value can be improved and high statistical uncertainty can be reduced, particularly in cases of limited toxicity data, i.e. data for mammals only or a sample size of n≤4.
对于温血动物物种,化学物质的危险剂量(HD50)是评估有毒化学物质的一个即将到来的重要特征。通常,仅可获得有限数量的温血动物物种的实验信息,这会导致统计不确定性。此外,当小数据集包含代表性不足的物种样本时,它们会导致化学物质危险剂量的系统不确定性。可以使用种间相关估计(ICE)模型来扩大物种数量,但这些模型本身也存在不确定性。本研究的目的是量化通过 ICE 预测扩大样本大小后,对野生动物物种 HD50 值的可靠性的可能增益。对于 1137 种化学物质,我们比较了基于实验数据的 HD50 值(HD50(Ex))和结合实验数据和 ICE 预测的数据集的 HD50 值(HD50(Co))之间的系统不确定性和统计不确定性。HD50(Ex) 值范围在 1.0×10(-1) 到 9.5×10(3)mgkg(wwt)(-1)之间,HD50(Co) 值范围在 1.1×10(0) 到 6.1×10(3)mgkg(wwt)(-1)之间。对于超过 97%的化学物质,HD50(Ex) 值超过 HD50(Co) 值,系统不确定性(即 HD50(Ex)/HD50(Co) 的比值)通常为 3.5。实验毒性数据的有限可用性,主要是哺乳动物,导致对化学物质的野生动物毒性的系统低估。统计不确定性因子(即 95%/5%分位数的比值)量化了 HD50 值的统计不确定性。统计不确定性因子范围在实验数据集为 1.0×10(0) 到 2.5×10(22) 之间,在组合数据集为 4.8×10(0) 到 1.1×10(2) 之间。对于所有样本大小,中位数统计不确定性因子对于组合数据集最大。然而,通过将实验毒性数据与 ICE 预测相结合,可以降低统计不确定性因子范围的上限。我们得出的结论是,通过将实验数据与 ICE 模型预测相结合,可以提高 HD50 值的有效性,并降低高统计不确定性,特别是在毒性数据有限的情况下,即仅针对哺乳动物的数据或 n≤4 的样本量。