Login
Monday, September 06, 2010
Overview of Background, Motivation, and Statistical Methods for Margin-Of-Exposure Characterizations of Cancer Risks

 

 
IMPORTANCE OF DOSE

 

Dose-response modeling is almost always a key component of quantitative human health risk assessment and reflects a central premise of toxicology; namely, that "the dose makes the poison."  This phrase ("the dose makes the poison") was used by Paracelsus in the 16th century when he wanted to use mercury to treat syphilis.  The dose is the amount of chemical or other substance entering the body.  The risk is the probability of a particular chemical agent causing a disease or other response of concern and is a function of the dose received.  The function is called the dose-response relationship or dose-response model.

 

            Dose-response models are a critical component of quantitative human health risk assessment.  Almost all chemical substances have the potential to be poisonous (toxic) if the dose is sufficiently high.  However, at lower doses many chemicals are harmless and indeed, like drugs and vitamins, may be beneficial to health.  Dose-response models reflect the importance of the size of the dose in determining the probability of a response of concern such as a disease or death.

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