Approaches to Human Health Risk Assessment Based on the Signal-to-Noise Crossover Dose
Chiu, Weihsueh A., Guyton, Kathryn Z., Hogan, Karen, Jiont, Jennifer, Environmental Health Perspectives
We acknowledge the effort of Sand et al. (2011) in striving to develop a transparent, objective procedure for point of departure (POD) estimation, as encouraged by scientific review groups (National Research Council 2009). Although additional characterization of the statistical properties of the signal-to-noise crossover dose (SNCD) may be warranted, the goal of Sand et al. (2011) appears consistent with the intent of the POD to characterize "the beginning of extrapolation to lower doses" [U.S. Environmental Protection Agency (EPA) 2005]. In this letter we respond to the authors' illustration of their approach using cancer bioassay data to develop reference doses (RfDs) that target a 1/1,000 risk through linear extrapolation from the POD by highlighting opportunities to augment their statistically based approach with biological considerations.
For most carcinogens, the U.S. EPA develops cancer potency estimates as follows (U.S. EPA 2005). A POD associated with a benchmark response level (BMR) is derived and converted to human-equivalent units (incorporating information about cross-species dose scaling). The BMR is then divided by the human-equivalent POD to obtain a potency estimate, under the assumption that risks extrapolate linearly with doses below the BMR. For Sand et al. (2011), the upper-bound extra risk estimate (UERSNCD) is the BMR associated with the SNCD, but we recommend expressing SNCDs in human equivalents before deriving potency estimates.
For nonlinear extrapolation resulting in a RfD (which the U.S. EPA uses for noncancer effects and carcinogens with a threshold mode of action), Sand et al. (2011) chose to linearly extrapolate to a 1/1,000 risk in the test animal, which they considered analogous to applying a 100-fold uncertainty factor to a BMDLio (lower bound on the benchmark dose corresponding to 10% extra risk). Several aspects of this proposal merit further consideration. First, margins of exposure much larger than 100-fold would be typical for cancer. Furthermore, whereas linear extrapolation involves extrapolation in the same population to a smaller level of effect, the standard uncertainty factor approach involves extrapolation across populations at a fixed level of effect. The alternative we propose separately accounts for these biologically unrelated processes.
Motivating our proposal is the need highlighted by Sand et al. (2011) to clearly separate statistical factors supporting the level of effect associated with the POD while also fully incorporating biological considerations. We propose specifying "target" effect levels (TELs) associated with different end points based on biological considerations, independent of data set. The TELS could then be compared with the lowest practical BMR for a given data set--the UERSNICO used by Sand et al. The UERSNCD/TEL ratio is a diagnostic of the extent of extrapolation to the TEL. If UERSNCI [less than or equal to] TEL, then the BMD at the TEL does not involve extrapolation and can serve as the POD. …