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动物致癌性研究的设计、分析与解读中的统计学问题。

Statistical issues in the design, analysis and interpretation of animal carcinogenicity studies.

作者信息

Haseman J K

出版信息

Environ Health Perspect. 1984 Dec;58:385-92. doi: 10.1289/ehp.8458385.

Abstract

Statistical issues in the design, analysis and interpretation of animal carcinogenicity studies are discussed. In the area of experimental design, issues that must be considered include randomization of animals, sample size considerations, dose selection and allocation of animals to experimental groups, and control of potentially confounding factors. In the analysis of tumor incidence data, survival differences among groups should be taken into account. It is important to try to distinguish between tumors that contribute to the death of the animal and "incidental" tumors discovered at autopsy in an animal dying of an unrelated cause. Life table analyses (appropriate for lethal tumors) and incidental tumor tests (appropriate for nonfatal tumors) are described, and the utilization of these procedures by the National Toxicology Program is discussed. Despite the fact that past interpretations of carcinogenicity data have tended to focus on pairwise comparisons in general and high-dose effects in particular, the importance of trend tests should not be overlooked, since these procedures are more sensitive than pairwise comparisons to the detection of carcinogenic effects. No rigid statistical "decision rule" should be employed in the interpretation of carcinogenicity data. Although the statistical significance of an observed tumor increase is perhaps the single most important piece of evidence used in the evaluation process, a number of biological factors must also be taken into account. The use of historical control data, the false-positive issue and the interpretation of negative trends are also discussed.

摘要

本文讨论了动物致癌性研究的设计、分析和解释中的统计学问题。在实验设计方面,必须考虑的问题包括动物的随机分组、样本量的考量、剂量选择以及将动物分配到实验组,还有对潜在混杂因素的控制。在肿瘤发生率数据分析中,应考虑组间的生存差异。区分导致动物死亡的肿瘤和在死于无关原因的动物尸检时发现的“偶然”肿瘤很重要。文中描述了生命表分析(适用于致死性肿瘤)和偶然肿瘤检验(适用于非致死性肿瘤),并讨论了国家毒理学计划对这些方法的应用。尽管过去对致癌性数据的解释往往普遍侧重于两两比较,尤其是高剂量效应,但趋势检验的重要性不应被忽视,因为这些方法在检测致癌效应方面比两两比较更敏感。在解释致癌性数据时不应采用严格的统计“决策规则”。虽然观察到的肿瘤增加的统计学显著性可能是评估过程中使用的最重要的单一证据,但还必须考虑许多生物学因素。还讨论了历史对照数据的使用、假阳性问题以及阴性趋势的解释。

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