Proportional hazards regression of survival-sacrifice data with cause-of-death information in animal carcinogenicity studies
Proportional hazards regression of survival-sacrifice data with cause-of-death information in animal carcinogenicity studies
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DOI：
10.1002/sim.8201
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发表时间：
2019-08-30
影响因子：
2
通讯作者：
Mao, Lu
中科院分区：
文献类型：
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作者：
Mao, Lu
常规进行啮齿动物存活-处死实验，以评估某种暴露或药物的肿瘤诱导潜力。由于大多数研究中的肿瘤是不可触及的，动物在死亡时检查肿瘤形成的证据。在一些研究中，死亡原因由病理学家确定，以解释肿瘤发展和死亡之间可能的相关性。现有的死亡原因信息的生存-处死数据的方法仅限于肿瘤发病分布的多组检验或单样本估计，因此不能提供一种自然的方法来量化治疗效果或剂量-反应关系。在本文中，我们提出了半参数回归方法下流行的比例风险模型的肿瘤发病和肿瘤引起的死亡。对于推理，我们开发了一个最大的伪似然估计过程，使用修改的迭代凸次优算法，这是保证收敛到唯一的最大化目标函数。不同肿瘤发生率下的仿真研究表明，新方法提供了有效的推断的协变量的结果关系，并优于替代方法。本文以联苯胺盐酸盐对小鼠肝癌的影响为例进行了真实的研究。
Rodent survival-sacrifice experiments are routinely conducted to assess the tumor-inducing potential of a certain exposure or drug. Because most tumors under study are impalpable, animals are examined at death for evidence of tumor formation. In some studies, the cause of death is ascertained by a pathologist to account for possible correlation between tumor development and death. Existing methods for survival-sacrifice data with cause-of-death information have been restricted to multi-group testing or one-sample estimation of tumor onset distribution and thus do not provide a natural way to quantify treatment effect or dose-response relationship. In this paper, we propose semiparametric regression methods under the popular proportional hazards model for both tumor onset and tumor-caused death. For inference, we develop a maximum pseudo-likelihood estimation procedure using a modified iterative convex minorant algorithm, which is guaranteed to converge to the unique maximizer of the objective function. Simulation studies under different tumor rates show that the new methods provide valid inference on the covariate-outcome relationship and outperform alternative approaches. A real study investigating the effects of benzidine dihydrochloride on liver tumor in mice is analyzed as an illustration.