Uncertainty in High-to-Low Dose Extrapolation

One complicating factor in this extrapolation process is that the target of interest is different for those chemicals that may cause cancer and those that don t. For 

So far, we have only discussed dose extrapolation for non-Ccmcer chemicals. The same uncertainties discussed for dose extrapolation of non-cancer effects cu e also relevant for cancer effects. Mathematical models are typically used to extrapolate relationships from dose and cancer incidence established using high laboratory doses to those at low doses. These models can range from relatively simple linear equations (e.g., a straight line is assumed to represent the relationship) to complex mathematical solutions that involve exponential terms and knowledge of calculus. These models differ in their complexity based on the amount of information known about how a chemical causes cancer. Since the process of cancer development is complex, it is not surprising that some of the models used to describe the relationships between dose and response are also complex. 

Probably the most common of these models is the Linearized Multistage Model (LMS), which is one of the simplest models developed for dose extrapolation for 

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