QUANTALIZATION OF CONTINUOUS DATA FOR BENCHMARK DOSE ESTIMATION

Benchmark doses corresponding to low levels of noncancer disease risk have been proposed to replace the no-observed-adverse effect level for establishing allowable daily intakes or reference doses. For quantal data each animal is classified with or without a disease. The proporti on of animals with an adverse effect (risk) is observed as a function of dose of a toxic substance. The calculation of a benchmark dose is r elatively straightforward. For continuous data a somewhat more complic ated designation of risk is required. Because of the more direct proce dures with quantal data, consideration could be given to converting co ntinuous data to quantal data before estimating benchmark doses. The p urpose of this paper is to compare the precision of the two approaches (use of continuous or quantalized data) for a number of sublinear dos e-response curves ranging from low to high probabilities of risk at th e highest dose. In these studies, five animals per dose were generally satisfactory to estimate the benchmark dose for continuous data, wher eas the corresponding quantalized data generally do not perform as wel l even with 10 to 20 animals per dose. For quantalized data, the lower 95% confidence limits on the estimates of the benchmark dose were gen erally a factor of 3 to 4 below the true benchmark dose, whereas the c onfidence limits using the continuous data were generally within a fac tor of 2 of the true benchmark dose. Although the use of quantalized d ata for the estimation of risk is more direct, estimates of benchmark doses using the continuous data were more precise. Based on this study , converting continuous data to quantal data is not recommended. (C) 1 996 Academic Press, Inc.