학술논문

Using categorical regression instead of a NOAEL to characterize a toxicologist's judgment in noncancer risk assessment
Document Type
Conference
Source
1993 (2nd) International Symposium on Uncertainty Modeling and Analysis Uncertainty modelling and analysis Uncertainty Modeling and Analysis, 1993. Proceedings., Second International Symposium on. :254-261 1993
Subject
Computing and Processing
Toxicology
Uncertainty
Risk management
Humans
Protection
Extrapolation
Life estimation
Lifetime estimation
Iris
Feeds
Language
Abstract
Noncancer health risk assessment involves the evaluation of multiple types of toxic effects. For regulatory recommendations, such as the Reference Dose (RfD), the US Environmental Protection Agency (EPA) relies heavily on expert judgment. This toxicologic judgment mixes toxic impact with likelihood: what effects are adverse, which of these is critical, and which dose is the highest reliable NOAEL (No-Observed-Adverse-Effect Level). Uncertainty is indicated by qualitative statements of confidence. Statistical regression using ordered categories of overall toxicity is proposed as a superior alternative. Uncertainty and variability are represented by statistical models, all relevant data are used, not just the NOAEL for the critical effect, and health risk can be estimated at exposure levels above the RfD.ETX