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On determining the BMD from multiple outcomes in developmental toxicity studies when one outcome is intentionally
Julie S Najita1, Paul J Catalano
1Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. jnajita@jimmy.harvard.edu
Risk Analysis : an Official Publication of the Society for Risk Analysis
|December 13, 2012
Summary
This study explores developmental toxicity risk assessment, showing that strategically sampling pups with malformations can improve benchmark dose (BMD) precision and reduce costs compared to simple random sampling.
Area of Science:
- Environmental toxicology
- Developmental biology
- Biostatistics
Background:
- Public health concerns regarding prenatal exposure to environmental factors necessitate robust developmental toxicity studies.
- The benchmark dose (BMD) is crucial for risk assessment, with joint modeling approaches analyzing multiple outcomes.
- Resource limitations can restrict evaluating all subjects for continuous outcomes, leading to subset selection.
Purpose of the Study:
- To develop and evaluate a subset selection model for developmental toxicity studies.
- To understand how prespecified sampling rates influence the precision of the benchmark dose (BMD).
- To assess potential cost savings associated with optimized sampling strategies.
Main Methods:
- Described a subset selection model allowing differential sampling of pups with and without malformations.
- Utilized simulations based on a joint mixed effects model to assess BMD precision.
- Employed case weights to obtain valid dose-response estimates accounting for subset selection.
Main Results:
- Oversampling malformations can yield improvements in BMD precision compared to simple random sampling (SRS).
- Certain sampling rates can result in substantially worse precision than SRS.
- Oversampling strategies demonstrate potential for significant cost savings in studies.
Conclusions:
- The developed subset selection model offers a flexible approach to developmental toxicity study design.
- Strategic sampling, particularly oversampling malformations, can enhance risk assessment efficiency and cost-effectiveness.
- Careful consideration of sampling rates is essential to avoid compromising BMD precision.
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