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Thursday, September 09, 2010
ADVERSE IMPACTS OF THE VARIABILITY IN THE MAGNITUDE OF THE BIAS IN THE LINEARIZED MULTISTAGE MODELS OVERSTATEMENT OF RISKS

 

In the regulatory arena, the q1* value is often said to be conservative, in the sense that, by overstating the potency and added risks, it is thought to be protective of public health by inducing extreme measures to reduce exposure and dose due to the substance at hand.  Of course, if such a conservative potency measure leads to a misallocation of public health resources, then this conservatism could very well be injurious to public health. 

 

The exaggeration (bias) in the linearized multistage models upper bounds on potency is not the same for all dose-response relationships (more exaggeration when the underlying dose-response relationship is sublinear and less exaggeration when it is linear).  Hence, the exaggeration in the linearized multistage models upper bounds on potency is not the same for all substances.  This unequal bias could easily lead to the allocation of limited health protection resources to a substance with little or no practical health risks instead of a substance of more serious practical concern.

3. Human Health Risk Assessment
3.1     
Quantitative Risk Assessment and Statistical Analysis
3.2      Importance of Dose and Dose-Response Relationships
3.3      Misuse of Regulatory Upper-Bound Risk Characterizations
3.4      Risk Characterization Choices and Risk Exaggeration
3.5      A Better Approach to Cancer Risk Characterization
3.6      Overview of Background, Motivation, and Statistical Methods for Margin-of-Exposure Characterizations of Cancer Risks
           3.6.1    Importance of Dose
           3.6.2    Dose-Response Modeling
           3.6.3    Dose-Response Models
           3.6.4    Maximum Likelihood Estimation
           3.6.5    
Multistage Model
           3.6.6    Example of Fitted Multistage Model
           3.6.7    Potency
           3.6.8    Linearized Multistage Model
           3.6.9    Overstatement of Risks by the Linearized Multistage Model
           3.6.10  Adverse Impacts of the Variability in the Magnitude of the Bias in the Linearized Multistage Model's Overstatement of Risks
           3.6.11  Non-Responsiveness of the Linearized Multistage Model to Data
           3.6.12  Ranking Relative Risks
           3.6.13  Added Risk versus Extra Risk
           3.6.14  Need for a Better Dose-Response Characterization
           3.6.15  Better Dose-Response Characterization
           3.6.16  Benchmark Doses
           3.6.17  Responsiveness of Benchmark Doses Data Versus the Relative Non-Responsiveness of the Regulatory Upper-Bound Potency Q1* based on the Linearized Multistage Model
           3.6.18  Recommended Dose-Response Characterization
           3.6.19  Margin-of-Exposure Characterizations
           3.6.20  Conclusion
           3.6.21  Figures 1 to 16
3.7      Innovative Risk Assessment
3.8      Components of High-to-Low-Dose Extrapolation and Dose-Response Modeling
3.9      Probabilistic Exposure Assessment
3.10    Aggregate Risk Assessment
3.11    Cumulative Risk Assessment
3.12    Example Activities