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Development of a database on tumors and tumor sites in humans and in experimental animals for 'Group 1 agents identified through volume 109 of the IARC Monographs.
Journal of Toxicology and Environmental Health, Part B: Critical Reviews ( IF 6.4 ) Pub Date : 2019-10-15 , DOI: 10.1080/10937404.2019.1642601
Yann Grosse 1 , Pascale Lajoie 2, 3 , Mélissa Billard 2 , Daniel Krewski 2, 4, 5 , Jerry Rice 6 , Robert A Baan 7 , Vincent Cogliano 8 , Michael Bird 2 , Jan M Zielinski 2
Affiliation  

Volume 100 in the series of IARC Monographs on the Evaluation of Carcinogenic Risks to Humans comprises an update and review of relevant information on all agents determined to induce cancer in humans. These Group 1 agents are categorized in 6 Monographs (Volumes 100A-F) published in 2012. This paper describes the methodology and stringent criteria used in the creation of a comprehensive database on tumors noted in animals and humans for the carcinogens reviewed in Volume 100, and for additional Group 1 agents that were identified in subsequent Monographs through Volume 109. The development of this database involved the systematic collection of relevant data on tumors detected in humans and experimental animals identified by the Working Groups that conducted evaluations reported in the IARC Monographs. The database includes all human tumor sites identified by the Working Groups, along with all tumor sites for which there was sufficient evidence in experimental animals. This database provides a basis for assessing the degree of concordance between tumor sites observed in humans and experimental animals for Group 1 agents identified through Volume 109.

中文翻译:


开发关于人类和实验动物肿瘤和肿瘤部位的数据库,用于通过 IARC 专着第 109 卷确定的“第 1 类药物”。



IARC 人类致癌风险评估专着系列第 100 卷包含对所有确定诱发人类癌症的物质的相关信息的更新和审查。这些第 1 组药物被分类在 2012 年出版的 6 部专着(第 100A-F 卷)中。本文描述了创建关于动物和人类肿瘤的综合数据库所使用的方法和严格标准,其中涉及第 100 卷中审查的致癌物,以及在后续专着至第 109 卷中确定的其他第 1 组药物。该数据库的开发涉及系统收集在 IARC 专着中报告的评估工作组确定的人类和实验动物中检测到的肿瘤的相关数据。该数据库包括工作组确定的所有人类肿瘤位点,以及在实验动物中有足够证据的所有肿瘤位点。该数据库为评估第 109 卷中确定的第 1 组药物在人类和实验动物中观察到的肿瘤部位之间的一致性程度提供了基础。
更新日期:2019-10-25
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