A randomization test-based method for risk assessment in neurotoxicology.

Abstract

A current trend in risk assessment for systemic toxicity (noncancer) endpoints is to utilize the observable range of the dose-effect curve in order to estimate the likelihood of obtaining effects at lower concentrations. Methods to accomplish this endeavor are typically based on variability in either the effects of fixed doses (benchmark approaches), or on variability in the doses producing a fixed effect (probabilistic or tolerance-distribution approaches). The latter method may be particularly desirable because it can be used to determine variability in the effect of an agent in a population, which is an important goal of risk assessment. This method of analysis, however, has typically been accomplished using dose-effect data from individual subjects, which can be impractical in toxicology. A new method is therefore presented that can use traditional groups-design data to generate a set of dose-effect functions. Population tolerances for a specific effect can then be estimated from these model dose-effect functions. It is based on the randomization test, which assesses the generality of a data set by comparing it to a data set constructed from randomized combinations of single point estimates. The present article describes an iterative line-fitting program that generates such a data set and then uses it to provide risk assessments for two pesticides, triadimefon and carbaryl. The effects of these pesticides were studied on the locomotor activity of laboratory rats, a common neurobehavioral end point. Triadimefon produced dose-dependent increases in activity, while carbaryl produced dose-dependent decreases in activity. Risk figures derived from the empirical distribution of individual dose-effect functions were compared to those from the iterative line-fitting program. The results indicate that the method generates comparable risk figures, although potential limitations are also described.