Literature DB >> 15483190

A statistical evaluation of toxicity study designs for the estimation of the benchmark dose in continuous endpoints.

Wout Slob1, Mirjam Moerbeek, Eija Rauniomaa, Aldert H Piersma.   

Abstract

The benchmark approach is gaining attention as an alternative to the No-Observed-Adverse-Effect-Level (NOAEL) approach. However, current guidelines for the design of toxicity tests are based on assessing a NOAEL. It has been suggested that the current study design may not be optimal for assessing a Benchmark Dose (BMD). To further investigate this we performed three simulation studies in which a large number of designs were compared, focusing on continuous endpoints. Four fictitious endpoints were considered, their underlying dose-response curves having a linear, sublinear, supralinear, or sigmoidal shape. In each simulation run the BMD was derived from a model fitted to the generated data, where the selection of the model was based on that particular data set (according to a formal likelihood ratio test procedure). Thus, the model used for deriving the BMD in a single generated data set may not be the same as the one used for generating the data. In this way, model uncertainty is taken into account as well. The results show that the performance of a design is, first of all, determined by the total number of animals used. Distributing them over more dose groups does not result in a poorer performance of the study, despite the smaller number of animals per dose group. Dose placement is another crucial factor, and to minimize the risk of inadequate dose placement, the use of multiple dose studies is favorable. As a concomitant advantage, the use of multiple doses mitigates the disturbing effect of potential systematic errors in single dose groups. However, for endpoints with large residual variation (CV > or = 18%) there is a substantial probability of not detecting the overall dose-response, and this probability increases in designs with increasing number of dose groups. In such situations, six dose groups may be used as a compromise. Designs with high dose levels (i.e., associated with relatively high effects) are helpful in estimating doses with smaller effects (such as the benchmark dose), and it appears bad practice to omit higher dose groups to improve the fit at lower doses. The typical 28-day study design of four dose groups with five animals (per sex) may not be adequate to assess endpoints with large residual variation (CV > or = 18%), both in assessing a benchmark dose and in assessing a NOAEL.

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Year:  2004        PMID: 15483190     DOI: 10.1093/toxsci/kfi004

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  8 in total

1.  Variation in benchmark dose (BMD) and the 95% lower confidence limit of benchmark dose (BMDL) among general Japanese populations with no anthropogenic exposure to cadmium.

Authors:  Sonoko Sakuragi; Ken Takahashi; Tsutomu Hoshuyama; Jiro Moriguchi; Fumiko Ohashi; Yoshinari Fukui; Masayuki Ikeda
Journal:  Int Arch Occup Environ Health       Date:  2012-01-24       Impact factor: 3.015

2.  A Rat Liver Transcriptomic Point of Departure Predicts a Prospective Liver or Non-liver Apical Point of Departure.

Authors:  Kamin J Johnson; Scott S Auerbach; Eduardo Costa
Journal:  Toxicol Sci       Date:  2020-07-01       Impact factor: 4.849

3.  The Impact of Model Uncertainty on Benchmark Dose Estimation.

Authors:  R Webster West; Walter W Piegorsch; Edsel A Peña; Lingling An; Wensong Wu; Alissa A Wickens; Hui Xiong; Wenhai Chen
Journal:  Environmetrics       Date:  2012-12       Impact factor: 1.900

Review 4.  A review of species differences in the control of, and response to, chemical-induced thyroid hormone perturbations leading to thyroid cancer.

Authors:  John R Foster; Helen Tinwell; Stephanie Melching-Kollmuss
Journal:  Arch Toxicol       Date:  2021-01-05       Impact factor: 5.153

5.  Effects of seasons and parts on volatile N-nitrosamines and their exposure and risk assessment in raw chicken and duck meats.

Authors:  Kexin Li; Rui Wang; Xiaoxu Wang; Changxia Sun; Qiang Li
Journal:  J Food Sci Technol       Date:  2021-07-03       Impact factor: 3.117

6.  Standardizing benchmark dose calculations to improve science-based decisions in human health assessments.

Authors:  Jessica A Wignall; Andrew J Shapiro; Fred A Wright; Tracey J Woodruff; Weihsueh A Chiu; Kathryn Z Guyton; Ivan Rusyn
Journal:  Environ Health Perspect       Date:  2014-02-25       Impact factor: 9.031

7.  Optimal experimental designs for dose-response studies with continuous endpoints.

Authors:  Tim Holland-Letz; Annette Kopp-Schneider
Journal:  Arch Toxicol       Date:  2014-08-26       Impact factor: 5.153

8.  Quantitative assessment of sensitizing potency using a dose-response adaptation of GARDskin.

Authors:  Robin Gradin; Andy Forreryd; Ulrika Mattson; Anders Jerre; Henrik Johansson
Journal:  Sci Rep       Date:  2021-09-23       Impact factor: 4.379

  8 in total

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