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Procedures for calculating benchmark doses for health risk assessment
1National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Regulatory Toxicology and Pharmacology : RTP
|February 3, 1999
Summary
The benchmark dose (BD) method offers a more robust approach to noncancer health risk assessment than traditional methods like the no observed adverse effect level (NOAEL). This paper details statistical procedures for calculating BDs across various data types, enhancing safety evaluations.
Area of Science:
- Toxicology
- Risk Assessment
- Biostatistics
Background:
- Traditional safety assessments for noncancer health effects rely on the no observed adverse effect level (NOAEL) divided by safety factors to derive acceptable daily intakes (ADIs) or reference doses (RfDs).
- The NOAEL approach has limitations, including underutilization of dose-response data, potential for higher ADIs from less robust experiments, and an unknown level of residual risk.
- The benchmark dose (BD) has emerged as a valuable adjunct or alternative, providing a dose associated with a specified, controlled low level of risk.
Purpose of the Study:
- To summarize and present statistical procedures for calculating benchmark doses (BDs) and their confidence limits for noncancer endpoints.
- To illustrate these procedures for quantal, quasicontinuous, and continuous data types encountered in toxicological studies.
Main Methods:
- Statistical procedures for calculating BDs and confidence limits are presented for different data types: quantal (binary), quasicontinuous (proportion), and continuous.
- Special considerations for quasicontinuous data in developmental studies (e.g., proportion of abnormal fetuses per litter) are addressed, including handling litter effects.
- Methods for continuous data, including defining adverse effects based on percentiles and estimating risk as a function of dose, are illustrated with neurotoxicity data.
- Multivariate procedures for estimating BDs when multiple adverse endpoints are present are demonstrated using developmental and reproductive toxicity data.
Main Results:
- The paper provides a comprehensive overview of statistical methodologies for BD estimation across diverse toxicological data structures.
- Illustrative examples demonstrate the application of these methods to real-world toxicity data, including developmental, reproductive, and neurotoxicity studies.
- The presented procedures allow for the estimation of BDs and associated confidence intervals, facilitating more precise risk characterization.
Conclusions:
- The benchmark dose (BD) methodology offers a statistically sound and data-driven approach to noncancer health risk assessment.
- The statistical procedures outlined are applicable to various data types, enhancing the utility of BDs in regulatory toxicology.
- Utilizing BDs improves upon traditional NOAEL-based assessments by better incorporating dose-response information and controlling for specific risk levels.
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