Another flaw in the linearized multistage model upper bounds on human cancer potency

Area of Science:

• Environmental toxicology
• Risk assessment methodology
• Carcinogenesis

Background:

• Federal agencies, including the EPA, use statistical methods based on animal experiments to estimate human cancer potencies.
• Current methodologies simplify assumptions, failing to account for quantitative differences in background transition rates in the multistage carcinogenic process between humans and experimental animals.
• Tumorigenic responses in rodents often occur in organs with high background tumor incidence, leading to overestimation of human risk.

Purpose of the Study:

• To identify flaws in the current statistical methodology used for characterizing human cancer potencies.
• To highlight the overestimation of human cancer risks due to simplified assumptions in risk assessment.
• To advocate for a transition to a more comprehensive, biologically based risk assessment methodology.

Main Methods:

• Analysis of the statistical methodology employed by the EPA and other federal agencies for cancer potency characterization.
• Evaluation of the impact of quantitative differences in background transition rates on risk estimation.
• Comparison of tumorigenic responses in experimental animals (rats and mice) and humans.

Main Results:

• The current methodology significantly exaggerates human cancer risk estimates and bounds in certain instances.
• Simplified assumptions fail to properly assess species-specific background transition rates in carcinogenesis.
• High background tumor incidence in animal organs leads to a substantial overstatement of human risk.

Conclusions:

• A newly recognized flaw, alongside previously identified issues, strongly indicates the inadequacy of the current default screening methodology.
• There is a compelling need to move away from solely default screening towards a more comprehensive, biologically based risk assessment.
• Implementing biologically informed models will provide more accurate human cancer risk characterizations.