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The Impact of Model Uncertainty on Benchmark Dose Estimation
R Webster West1, Walter W Piegorsch, Edsel A Peña
1Department of Statistics, Texas A&M University, College Station, TX, USA.
Environmetrics
|June 25, 2013
Summary
Model misspecification in toxicological risk assessment can lead to inaccurate benchmark dose (BMD) and benchmark dose lower confidence limit (BMDL) calculations. This may result in unsafe low-dose inferences, potentially exceeding target risk levels.
Area of Science:
- Toxicological Risk Assessment
- Biostatistics
- Environmental Health
Background:
- The benchmark dose (BMD) approach is crucial for estimating low exposure levels in toxicological risk assessment.
- Traditional methods rely on parametric dose-response models, but model specification and selection introduce uncertainty.
- Model misspecification can lead to inaccurate low-dose inferences and potentially unsafe risk assessments.
Purpose of the Study:
- To investigate the impact of model selection and misspecification on BMD and BMDL estimations.
- To evaluate the associated extra risks at BMDL values under different model scenarios.
- To highlight potential dangers in traditional model selection strategies for BMD calculations.
Main Methods:
- Large-scale Monte Carlo simulations were employed to study dose-response experiments with quantal data.
- The study focused on the effects of parametric model misspecification on BMD and BMDL.
- Analysis included the extra risks achieved at BMDL under correctly and incorrectly selected models.
Main Results:
- A significant percentage of simulations showed that the true extra risk at the BMDL exceeded the benchmark risk (BMR) when models were misspecified.
- Incorrect model selection can lead to unreliable BMDL values and underestimation of actual risks.
- The study identified potential safety concerns arising from standard model selection practices.
Conclusions:
- Traditional model selection strategies in BMD analysis can be hazardous.
- Model misspecification poses a substantial risk to the accuracy and safety of low-dose risk assessments.
- Careful consideration and robust methods for model selection are essential for reliable toxicological risk assessment.
Keywords:
AICBMDLBenchmark analysisExcess RiskExtraModel adequacyModel selectionQuantitative risk assessmentRiskMore Related Videos
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