JSM 2005 - Toronto

Abstract #303854

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Activity Number: 189
Type: Contributed
Date/Time: Monday, August 8, 2005 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #303854
Title: Multiplicity-adjusted Inferences in Risk Assessment: Benchmark Analysis with Quantal Response Data
Author(s): Daniela Nitcheva*+ and Walter W. Piegorsch and Webster West and Ralph Kodell
Companies: South Carolina Cancer Center and University of South Carolina and University of South Carolina and National Center for Toxicological Research
Address: 7 Richalnd Medical Park, Columbia, SC, 29203, United States
Keywords: multistage model ; simultaneous inferences ; benchmark dose
Abstract:

A primary objective in quantitative risk or safety assessment is characterization of the severity and likelihood of an adverse effect caused by a chemical toxin or pharmaceutical agent. In many cases, data are not available at low doses or exposures to the agent, and inferences at those doses must be based on the high-dose data. A modern method for making low-dose inferences is known as benchmark analysis, where attention centers on the dose at which a fixed benchmark level of risk is achieved. Both upper confidence limits on the risk and lower confidence limits on the "benchmark dose" are of interest. In practice, a number of possible benchmark risks may be under study. In such cases, corrections must be applied to adjust the limits for multiplicity. Several approaches for doing so were studied with quantal response data. To compare their properties, Monte Carlo simulation techniques were used. Although all methods exhibit conservative simultaneous coverage, we recommend use of LR approach as least conservative.

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Revised March 2005