Dunson D B
Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA.
Biometrics. 1998 Jun;54(2):558-69.
This paper proposes a method for assessing risk in developmental toxicity studies with exposure prior to implantation. The method proposed in this paper was developed to account for a dose-dependent trend in the number of implantation sites per dam, which is a common problem in studies with exposure prior to implantation. Toxins may have the effect of interfering with the early reproductive process, which can prevent implantation in the uterine wall. An imputation procedure is presented for estimating the number of potential fetuses by sampling from the empirical distribution of the number of implants per litter in the control group. The marginal death outcomes and the joint malformation and survival outcomes for each potential fetus can be estimated using multiple imputation or the chained data augmentation algorithm. Logit models can then be fit and used to estimate the effect of dose on reducing the probability of a normal birth. These models accommodate multiple covariate effects and can be applied to low-dose extrapolation. A simulation study is done to evaluate the properties of model-based estimators of the mean response and the virtually safe dose level (VSD). It was found that both estimates were good approximations of the underlying dose effect. A dominant lethal assay data set (Luning et al., 1966, Mutation Research 3, 444-451) is analyzed, and the results are compared with those of Rai and Van Ryzin.
本文提出了一种在植入前暴露的发育毒性研究中评估风险的方法。本文提出的方法是为了解决每只母鼠植入部位数量的剂量依赖性趋势这一问题而开发的，这在植入前暴露的研究中是一个常见问题。毒素可能会干扰早期生殖过程，从而阻止在子宫壁着床。本文提出了一种插补程序，通过从对照组每窝植入数量的经验分布中抽样来估计潜在胎儿的数量。每个潜在胎儿的边缘死亡结局以及联合畸形和生存结局可以使用多重插补或链式数据扩充算法进行估计。然后可以拟合Logit模型并用于估计剂量对降低正常出生概率的影响。这些模型考虑了多个协变量效应，可应用于低剂量外推。进行了一项模拟研究，以评估基于模型的平均反应估计值和虚拟安全剂量水平（VSD）的性质。结果发现，这两个估计值都是潜在剂量效应的良好近似值。分析了一个显性致死试验数据集（Luning等人，1966年，《突变研究》3，444 - 451），并将结果与Rai和Van Ryzin的结果进行了比较。
