National Institute for Occupational Safety and Health, Risk Evaluation Branch, Cincinnati, OH, USA.
Benchmark Dose Estimation Incorporating Multiple Data Sources
Article first published online: 24 OCT 2008
© 2008 Society for Risk Analysis
Volume 29, Issue 2, pages 249–256, February 2009
How to Cite
Wheeler, M. W. and Bailer, A. J. (2009), Benchmark Dose Estimation Incorporating Multiple Data Sources. Risk Analysis, 29: 249–256. doi: 10.1111/j.1539-6924.2008.01144.x
- Issue published online: 23 JAN 2009
- Article first published online: 24 OCT 2008
- Aquatic toxicology;
- Bayesian methods;
- generalized linear mixed models;
- hierarchical models;
- lab-to-lab variability;
- Poisson responses
With the increased availability of toxicological hazard information arising from multiple experimental sources, risk assessors are often confronted with the challenge of synthesizing all available scientific information into an analysis. This analysis is further complicated because significant between-source heterogeneity/lab-to-lab variability is often evident. We estimate benchmark doses using hierarchical models to account for the observed heterogeneity. These models are used to construct source-specific and population-average estimates of the benchmark dose (BMD). This is illustrated with an analysis of the U.S. EPA Region IX's reference toxicity database on the effects of sodium chloride on reproduction in Ceriodaphnia dubia. Results show that such models may effectively account for the lab-source heterogeneity while producing BMD estimates that more truly reflect the variability of the system under study. Failing to account for such heterogeneity may result in estimates having confidence intervals that are overly narrow.