A comparison of three methods for calculating confidence intervals for the benchmark dose
A comparison of three methods for calculating confidence intervals for the benchmark dose
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DOI：
10.1111/j.0272-4332.2004.00409.x
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发表时间：
2004-02-01
期刊：
影响因子：
3.8
通讯作者：
Slob, W
中科院分区：
文献类型：
--
作者：
Moerbeek, M;Piersma, AH;Slob, W
在危险分析中，有各种计算基准剂量置信区间的方法。本文比较了三种拟合非线性剂量-响应模型的方法：δ法、似然比法和自举法的性能。一组来自发育毒性试验的数据集，具有连续、有序和定量的剂量-反应数据，用于这些方法的比较。对这些数据进行了各种形状的非线性剂量响应模型拟合。结果表明，在使用自举法时，通常需要几千次运行才能获得稳定的置信限。此外，发现自举法和似然比法给出了相当相似的结果。然而，delta方法在某些情况下导致不同（通常较窄）的区间，并且对于非线性剂量-响应模型似乎不可靠。由于自举法比似然比法耗时更长，后者更适合于常规剂量-反应分析。在概率风险评估的背景下，自举法的优点是它直接与蒙特卡罗分析相联系。
Various methods exist to calculate confidence intervals for the benchmark dose in risk analysis. This study compares the performance of three such methods in fitting nonlinear dose-response models: the delta method, the likelihood-ratio method, and the bootstrap method. A data set from a developmental toxicity test with continuous, ordinal, and quantal dose-response data is used for the comparison of these methods. Nonlinear dose-response models, with various shapes, were fitted to these data. The results indicate that a few thousand runs are generally needed to get stable confidence limits when using the bootstrap method. Further, the bootstrap and the likelihood-ratio method were found to give fairly similar results. The delta method, however, resulted in some cases in different (usually narrower) intervals, and appears unreliable for nonlinear dose-response models. Since the bootstrap method is more time consuming than the likelihood-ratio method, the latter is more attractive for routine dose-response analysis. In the context of a probabilistic risk assessment the bootstrap method has the advantage that it directly links to Monte Carlo analysis.