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动物致癌性实验中疾病关联的检测。

Detection of associations between diseases in animal carcinogenicity experiments.

作者信息

Mitchell T J, Turnbull B W

机构信息

Oak Ridge National Laboratory, Tennessee 37831-8083.

出版信息

Biometrics. 1990 Jun;46(2):359-74.

PMID:2364126
Abstract

We present a statistical test for the hypothesis of independence of two disease processes in animal carcinogenicity experiments. It is assumed that the diseases are occult (detectable only at death via necropsy), and progressive, in that each passes (potentially) through three states in each animal: absent, nonlethally present, and lethally present. The test is based on the combination of statistics from a series of age-stratified 3 x 3 tables in which the animals that die in each age interval are cross-classified into one of these three states for each disease. This test utilizes all the data, whether obtained by sacrifice or by "natural death." It avoids the biases due to lethality noted by Breslow et al. (1974, Journal of the National Cancer Institute 52, 233-239) for the test based on age-stratified 2 x 2 tables, where the nonlethal and lethal occurrences are pooled. In a simulation experiment, we show that such biases (which usually conceal true positive associations and produce spurious negative associations) can be very severe indeed, whereas our test preserves the nominal significance level quite well. The power of the test appears to vary widely, depending on the incidence, time to onset, and rate of progression of each disease. As an example of the application of our method, we assess the association between liver tumors and reticulum cell sarcoma in a radiocarcinogenesis experiment involving approximately 1,000 C3H female mice.

摘要

我们提出了一种用于检验动物致癌性实验中两种疾病进程独立性假设的统计检验方法。假设这些疾病是隐匿性的(仅在尸检时死亡时才可检测到)且呈进行性发展,即每种疾病在每只动物体内(可能)会经历三个阶段:不存在、非致死性存在和致死性存在。该检验基于一系列按年龄分层的3×3表格中的统计数据组合,在这些表格中,将每个年龄区间内死亡的动物按照每种疾病的这三种状态之一进行交叉分类。此检验利用了所有数据,无论是通过处死还是“自然死亡”获得的数据。它避免了Breslow等人(1974年,《国家癌症研究所杂志》52卷,233 - 239页)基于按年龄分层的2×2表格进行检验时所指出的因致死性导致的偏差,在该检验中,非致死性和致死性发生情况被合并在一起。在一个模拟实验中,我们表明这种偏差(通常会掩盖真正的正相关并产生虚假的负相关)可能确实非常严重,而我们的检验能很好地保持名义显著性水平。该检验的功效似乎差异很大,这取决于每种疾病的发病率、发病时间和进展速度。作为我们方法应用的一个例子,我们评估了在一项涉及约1000只C3H雌性小鼠的放射致癌实验中肝肿瘤与网状细胞肉瘤之间的关联。

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Detection of associations between diseases in animal carcinogenicity experiments.动物致癌性实验中疾病关联的检测。
Biometrics. 1990 Jun;46(2):359-74.
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