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Publication Detail

Title: A simulation study of quantitative risk assessment for bivariate continuous outcomes.

Authors: Yu, Zi-Fan; Catalano, Paul J; Catzlano, Paul J

Published In Risk Anal, (2008 Oct)

Abstract: The neurotoxic effects of chemical agents are often investigated in controlled studies on rodents, with binary and continuous multiple endpoints routinely collected. One goal is to conduct quantitative risk assessment to determine safe dose levels. Yu and Catalano (2005) describe a method for quantitative risk assessment for bivariate continuous outcomes by extending a univariate method of percentile regression. The model is likelihood based and allows for separate dose-response models for each outcome while accounting for the bivariate correlation. The approach to benchmark dose (BMD) estimation is analogous to that for quantal data without having to specify arbitrary cutoff values. In this article, we evaluate the behavior of the BMD relative to background rates, sample size, level of bivariate correlation, dose-response trend, and distributional assumptions. Using simulations, we explore the effects of these factors on the resulting BMD and BMDL distributions. In addition, we illustrate our method with data from a neurotoxicity study of parathion exposure in rats.

PubMed ID: 18631306 Exiting the NIEHS site

MeSH Terms: Animals; Benchmarking; Central Nervous System Diseases/chemically induced; Dose-Response Relationship, Drug*; Insecticides/toxicity; Models, Animal; Monte Carlo Method; Parathion/toxicity; Rats; Regression Analysis; Risk Assessment/methods*

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