Challenges to default assumptions stimulate comprehensive realism as a new tier in quantitative cancer risk assessment.

The current practice in carcinogen risk assessment of using a linearized multistage model and assuming low-dose linearity is based on several false premises. In many cases linearity at low doses would not be expected based on the interaction between the multiple components in the carcinogenic process. The two-stage growth models, involving multiple mutations and cell birth and death rates, provide one means of exploring these interactions. In addition, if carcinogenesis is considered to be the imbalance between invading substances and defense mechanisms, then the cancer probability depends on how much the substance increases or decrease the number of defenders or their efficiency as well as increasing or decreasing the number of invaders. Challenges to low-dose linearity and other default assumptions have stimulated the development of new risk assessment methodologies as have the need for more realistic estimates of risk, better uncertainty characterization, and greater utilization of cost-benefit analyses, and other tools for risk management decision making. "Comprehensive realism" is an emerging quantitative weight-of-evidence risk assessment methodology which is designed to reflect all of the relevant and available information and the current state of knowledge about the health risks associated with a substance.