Bokkers Bas G H, Slob Wout
Institute for Risk Assessment Sciences (IRAS), P.O. Box 80176, 3508 TD Utrecht, The Netherlands.
Toxicol Sci. 2005 Jun;85(2):1033-40. doi: 10.1093/toxsci/kfi144. Epub 2005 Mar 16.
One approach to derive a data-based assessment factor (AF) for subchronic-to-chronic extrapolation is to determine ratios between the NOAEL(subchronic) and NOAEL(chronic) for the same compounds. Instead of using ratios of NOAELs, the distribution can also be estimated by ratios of subchronic and chronic Benchmark Doses (or Critical Effect Doses, CEDs, for continuous data). In this study 314 dose-response datasets on body weights and liver weights of mice and rats were selected providing dose-response information after both subchronic and chronic exposure. NOAEL ratios could be derived in only 68 of these datasets, while CED ratios could be derived in 189 datasets. When only the (53) datasets suitable for both approaches were evaluated the variation of the CED ratio distribution (GSD [geometric standard deviation]: 2.9) was smaller than the one of the NOAEL ratio distribution (GSD: 3.3). After correcting for the estimation error of the individual CED ratios the GSD of the CED distribution decreased to 2.3. The geometric means (GMs) of the NOAEL and CED distributions were similar (1.2 and 1.6, respectively). Comparing the NOAEL distribution based on all 68 datasets suitable for deriving NOAEL ratios with the CED distribution based on the 189 ratios suitable for deriving CED ratios resulted in similar GMs (1.5 and 1.7, respectively), but the GSDs differed considerably (5.3 and 2.3 respectively). It is concluded that usage of the CED approach results in less wide distributions. Furthermore, a larger fraction of available datasets is useful to inform the ratio distribution. This results in more accurate, and less conservative distributions of AFs in general compared to the distributions based on NOAEL ratios that have been proposed so far.
一种用于推导基于数据的亚慢性到慢性外推评估因子(AF)的方法是确定同一化合物的无观察到有害作用水平(NOAEL,亚慢性)与无观察到有害作用水平(NOAEL,慢性)之间的比值。除了使用NOAEL的比值外,分布也可以通过亚慢性和慢性基准剂量(或连续数据的临界效应剂量,CED)的比值来估计。在本研究中,选择了314个关于小鼠和大鼠体重及肝脏重量的剂量反应数据集,这些数据集提供了亚慢性和慢性暴露后的剂量反应信息。在这些数据集中,只有68个可以得出NOAEL比值,而189个数据集可以得出CED比值。当仅评估适用于两种方法的(53)个数据集时,CED比值分布的变异(几何标准差[GSD]:2.9)小于NOAEL比值分布的变异(GSD:3.3)。在纠正了各个CED比值的估计误差后,CED分布的GSD降至2.3。NOAEL和CED分布的几何均值(GMs)相似(分别为1.2和1.6)。将基于所有68个适用于推导NOAEL比值的数据集的NOAEL分布与基于189个适用于推导CED比值的比值的CED分布进行比较,得到了相似的GMs(分别为1.5和1.7),但GSDs差异很大(分别为5.3和2.3)。结论是,使用CED方法会使分布范围更窄。此外,更大比例的可用数据集可用于为比值分布提供信息。与目前提出的基于NOAEL比值的分布相比,这通常会导致AF的分布更准确且不那么保守。