Benchmark Dose Risk Analysis with Mixed-Factor Quantal Data in Environmental Risk Assessment

• Activity Number: 168 - Risk analysis and related topics
• Type: Contributed
• Date/Time: Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
• Sponsor: Section on Risk Analysis
• Author(s): Maria Assumpció Sans-Fuentes* and Walter W. Piegorsch
• Companies: University of Arizona and University of Arizona
• Keywords: Benchmark analysis; BMDL; lower confidence limits; quantal response data; quantitative risk assessment; simultaneous inferences

Abstract

Benchmark analysis is a general risk estimation strategy for identifying the benchmark dose (BMD) past which the risk of exhibiting an adverse environmental response exceeds a fixed, target value of benchmark response (BMR). Estimation of BMD and of its lower confidence limit (BMDL) is well understood for the case of an adverse response to a single stimulus. In many environmental settings, however, one or more additional, secondary, qualitative factor(s) may collude to affect the adverse outcome, such that the risk changes with differential levels of the secondary factor.

This research extends the single-dose BMD paradigm to a mixed-factor setting with a secondary qualitative factor possessing two levels. With focus on quantal-response data and using a generalized linear model with a complementary-log link function, we derive expressions for BMD and BMDL. We study the operating characteristics of six different approaches to calculate the BMDL, using Monte Carlo evaluations. We illustrate the calculations via an example data from environmental carcinogenicity testing.