装配短期测试电池以预测致癌性的规则是什么?

Molecular toxicology Pub Date : 1987-04-01
R Benigni, A Giuliani
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引用次数: 0

摘要

本文的主要主题是描述用于致癌性预测短期试验的可靠电池组装的基本要求。为此目的,通过不同的数据分析方法研究了国际短期致癌物试验评估计划(IPESTTC)生成的数据库的一个子集。在选择数据和统计技术两方面,对问题的方法方面给予了很大的关注。考虑了21种最广泛使用的短期测定法。首先通过因子分析对数据库进行了探索性研究,显示了测试性能之间的异同,并证实了我们之前通过聚类分析得到的结果。通过这种方法,实验对象根据对化学物质的反应分为三组。沙门氏菌检测处于中心组,其特点是在致癌物的敏感性和特异性方面具有平衡的性能。此外,还确定了与沙门氏菌检测相补充的敏感性和特异性检测方法。本文还介绍了IPESTTC结果与Gene-Tox数据库的初步比较。然后用判别分析评价了试验在致癌性预测方面的性能。当将数据子集作为一个整体考虑时,该过程产生了一个线性判别函数,能够正确识别84.2%的致癌物和83.3%的非致癌物。当使用足够的测试电池时,正确识别的致癌物总数约为90%。这一分析得出了一些观察结果。(1)与选择性指标(如灵敏度和特异性)一起,必须确定和考虑测试性能之间的操作互补性。(2)预测致癌活性最有效的电池由三个测试组成,每组一个。这一发现与以下事实相一致:三类检测在敏感性和特异性上有明确的区分,在这个意义上是相互补充的。(3)增加试验次数并不能提高电池的性能,在某些情况下反而会产生相反的效果。(4)从定性的遗传毒性数据出发,估计化学物质致癌的概率是可能的。
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Which rules for assembling short-term test batteries to predict carcinogenicity?

The main theme of this paper is to describe the basic requirements for assembling reliable batteries of short-term tests for carcinogenicity prediction. For this purpose, a subset of the data base generated by the International Program for Evaluation of Short-Term Tests for Carcinogens (IPESTTC) has been studied by different data-analysis methods. Much attention has been focused on the methodological dimensions of the problem, at the level of selection of both data and statistical techniques. Twenty-one of the most widely used short-term assays were considered. An exploratory study of the data base was first performed by factor analysis, showing similarities and dissimilarities between test performances and confirming our previous results obtained by cluster analysis. In this way the assays were divided into three groups on the basis of their responses to the chemicals. The Salmonella assay was in the central group, characterized by equilibrated performances in respect to sensitivity and specificity for carcinogens. Tests complementary to the Salmonella assay for sensitivity and specificity, respectively, were identified as well. A preliminary comparison of the IPESTTC results with the Gene-Tox data base is also presented. The test performances in respect to carcinogenicity prediction were then evaluated by discriminant analysis. When the subset of data was considered as a whole, the procedure resulted in a linear discriminant function able to correctly identify 84.2% of carcinogens and 83.3% of noncarcinogens. The correctly identified carcinogens summed to about 90% when adequate batteries of tests were used. This analysis yielded a number of observations. (1) Together with the selectivity indices (such as sensitivity and specificity), the operational complementarity between test performances must be ascertained and taken into account. (2) The batteries most effective at predicting carcinogenic activity were composed of three tests, one for each group. This finding converged with the fact that the three classes of assays were clearly differentiated for sensitivity and specificity, and in this sense were complementary to each other. (3) The performances of the batteries were not improved by adding more tests, but in several cases the opposite effect occurred. (4) Estimation of the probability of the chemicals of being carcinogenic, starting from qualitative genotoxicity data, is possible.

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