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Relative robustness of NOEC and ECx against large uncertainties in data

The relative ability of the NOEC (no-observed-effect concentration) and EC(x) (the effect concentration corresponding to x-percent response) to determine benchmark toxicant concentrations, which are expected to ensure environmental safety, when there are large uncertainties in data was investigated...

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Autores principales: Tanaka, Yoshinari, Nakamura, Kensei, Yokomizo, Hiroyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261558/
https://www.ncbi.nlm.nih.gov/pubmed/30485303
http://dx.doi.org/10.1371/journal.pone.0206901
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author Tanaka, Yoshinari
Nakamura, Kensei
Yokomizo, Hiroyuki
author_facet Tanaka, Yoshinari
Nakamura, Kensei
Yokomizo, Hiroyuki
author_sort Tanaka, Yoshinari
collection PubMed
description The relative ability of the NOEC (no-observed-effect concentration) and EC(x) (the effect concentration corresponding to x-percent response) to determine benchmark toxicant concentrations, which are expected to ensure environmental safety, when there are large uncertainties in data was investigated with Monte Carlo simulations. We assumed a hypothetical true concentration-response function, and examined how random fluctuations of responses around the true responses affected the NOEC and EC(x) values. For assessment of the relative performances of these endpoints, we adopted two criteria: how large uncertainties were allowed for the minimum requirement for safety to be met, and the probability with which the estimated endpoints exceeded the minimum requirement for safety. The results of simulations indicated that, when there were small uncertainties in the data, performance of the NOEC was comparable with or slightly better than the EC(x) (EC(5) and EC(10)) in providing benchmark concentrations that satisfied the minimum requirement for safety. With larger random variation of data (the coefficient of variation in responses between replicates within treatments or in the control was noticeably larger than 10 percent), the NOEC performed considerably worse than the EC(x) in terms of the frequency of simulated runs in which the endpoints exceeded the minimum requirement of safety. We conclude that the NOEC is as relevant as the EC(x) for risk assessment of chemicals under limited situations.
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spelling pubmed-62615582018-12-19 Relative robustness of NOEC and ECx against large uncertainties in data Tanaka, Yoshinari Nakamura, Kensei Yokomizo, Hiroyuki PLoS One Research Article The relative ability of the NOEC (no-observed-effect concentration) and EC(x) (the effect concentration corresponding to x-percent response) to determine benchmark toxicant concentrations, which are expected to ensure environmental safety, when there are large uncertainties in data was investigated with Monte Carlo simulations. We assumed a hypothetical true concentration-response function, and examined how random fluctuations of responses around the true responses affected the NOEC and EC(x) values. For assessment of the relative performances of these endpoints, we adopted two criteria: how large uncertainties were allowed for the minimum requirement for safety to be met, and the probability with which the estimated endpoints exceeded the minimum requirement for safety. The results of simulations indicated that, when there were small uncertainties in the data, performance of the NOEC was comparable with or slightly better than the EC(x) (EC(5) and EC(10)) in providing benchmark concentrations that satisfied the minimum requirement for safety. With larger random variation of data (the coefficient of variation in responses between replicates within treatments or in the control was noticeably larger than 10 percent), the NOEC performed considerably worse than the EC(x) in terms of the frequency of simulated runs in which the endpoints exceeded the minimum requirement of safety. We conclude that the NOEC is as relevant as the EC(x) for risk assessment of chemicals under limited situations. Public Library of Science 2018-11-28 /pmc/articles/PMC6261558/ /pubmed/30485303 http://dx.doi.org/10.1371/journal.pone.0206901 Text en © 2018 Tanaka et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tanaka, Yoshinari
Nakamura, Kensei
Yokomizo, Hiroyuki
Relative robustness of NOEC and ECx against large uncertainties in data
title Relative robustness of NOEC and ECx against large uncertainties in data
title_full Relative robustness of NOEC and ECx against large uncertainties in data
title_fullStr Relative robustness of NOEC and ECx against large uncertainties in data
title_full_unstemmed Relative robustness of NOEC and ECx against large uncertainties in data
title_short Relative robustness of NOEC and ECx against large uncertainties in data
title_sort relative robustness of noec and ecx against large uncertainties in data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261558/
https://www.ncbi.nlm.nih.gov/pubmed/30485303
http://dx.doi.org/10.1371/journal.pone.0206901
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