Benchmark Dose Calculation for Ordered Categorical Responses

Abstract

The use of benchmark dose (BMD) calculations for dichotomous or continuous responses is well established in the risk assessment of cancer and noncancer endpoints. In some cases, responses to exposure are categorized in terms of ordinal severity effects such as none, mild, adverse, and severe. Such responses can be assessed using categorical regression (CATREG) analysis. However, while CATREG has been employed to compare the benchmark approach and the no-adverse-effect-level (NOAEL) approach in determining a reference dose, the utility of CATREG for risk assessment remains unclear. This study proposes a CATREG model to extend the BMD approach to ordered categorical responses by modeling severity levels as censored interval limits of a standard normal distribution. The BMD is calculated as a weighted average of the BMDs obtained at dichotomous cutoffs for each adverse severity level above the critical effect, with the weights being proportional to the reciprocal of the expected loss at the cutoff under the normal probability model. This approach provides a link between the current BMD procedures for dichotomous and continuous data. We estimate the CATREG parameters using a Markov chain Monte Carlo simulation procedure. The proposed method is demonstrated using examples of aldicarb and urethane, each with several categories of severity levels. Simulation studies comparing the BMD and BMDL (lower confidence bound on the BMD) using the proposed method to the correspondent estimates using the existing methods for dichotomous and continuous data are quite compatible; the difference is mainly dependent on the choice of cutoffs for the severity levels.

Impact of copper oxide nanomaterials on differentiated and undifferentiated Caco-2 intestinal epithelial cells; assessment of cytotoxicity, barrier integrity, cytokine production and nanomaterial penetration

“…BMD is useful in estimating the concentration of a toxicant required to elicit a low, but measurable (sub lethal), toxic response. BMD eliminates the problems associated with determination of the of no-observed-effect-level (NOEL) as it uses full dose-response data in the statistical analysis thereby enhancing quantification of uncertainty in the data [ 68 ]. Although differentiated Caco-2 cells are considered to be more representative of cells in vivo, undifferentiated cells were used initially to screen cytotoxicity, as it is technically easier, quicker and cheaper to perform these studies and so a wider range of concentrations can be tested.…”

A Review of Recent Advances in Benchmark Dose Methodology

“…End points of other types than quantal or continuous are not common in the BMD literature. A few exceptions include the work by Chen and Chen () who calculated BMD for ordered categorical data by defining BMD as a weighted average of the estimated BMD values using cutoffs at different severity levels, and Wheeler and Bailer () who considered BMD for count data. Parallel developments for effective dose estimation based on count data may also be useful for BMD estimation (Delignette‐Muller, Lopes, Veber, & Charles, ; Zhang et al., ; Zhang, Bailer, & Oris, ).…”

Dose-Response Modelling of Paralytic Shellfish Poisoning (PSP) in Humans

“…BMD is the dose corresponding to a specified increase in the extra response of an exposed group in comparison with a control group. Even if already studied [39], there is no official approach to establish BMD from ordinal data.…”