Comparison of the lower limit of benchmark dose confidence interval with no-observed-adverse-effect level by applying four different software for tumorigenicity testing of pesticides in Japan

Yukuto Yasuhiko, Miwa Ishigami, Satoshi Machino, Tatsuya Fujii, Masanori Aoki, Fumi Irie, Yasunari Kanda, Midori Yoshida

Research output: Contribution to journalArticlepeer-review

Abstract

The benchmark dose (BMD) approach is updated to create an international harmonizing process following rapid theoretical sophistication. We calculated the lower limit of BMD confidence interval (BMDL) for carcinogenicity based on 193 tumorigenicity bioassay data published in 50 pesticide risk assessment reports by the Food Safety Commission of Japan (FSCJ) to validate the appropriateness and necessity for the refinement of the FSCJ-established BMD guidance. Three well-known BMD software, PROAST, BMDS, and BBMD were used to compare their BMDLs with no-observed-adverse-effect levels (NOAELs) for carcinogenicity. Recently implemented methodologies such as model averaging or Bayesian inference were also used. Our results indicate that the BMD approach provides a point of departure similar to the NOAEL approach if the data used exhibit a clear dose-response relationship. In some cases, particularly in software with a frequentist approach, the calculation failed to provide BMDL or provided considerably lower BMDLs than NOAELs. However, most of the datasets that resulted in failed calculations or extremely low BMDLs exhibited unclear dose-response relationships, i.e., non-monotonous and sporadic responses. The expert review on the shape of the dose-response plot would help better apply the BMD approach. Furthermore, we observed that Bayesian approaches provided fewer failed or extreme BMD calculations than the frequentist approaches.

Original languageEnglish
Article number105201
JournalRegulatory Toxicology and Pharmacology
Volume133
DOIs
Publication statusPublished - Aug 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Toxicology

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