Main Title |
State-of-the-Science Workshop Report: Issues and Approaches in Low Dose-Response Extrapolationfor Environmental Health Risk Assessment. |
Author |
R. H. WHITE ;
I. Cote ;
L. Zeise ;
M. FOX ;
F. Dominici
|
Other Authors |
|
CORP Author |
Johns Hopkins Univ., Baltimore, MD. School of Public Health.; Environmental Protection Agency, Research Triangle Park, NC.; California Environmental Protection Agency, Sacramento. Office of Environmental Health Hazard Assessment.; Environmental Protection Agency, Washington, DC.; Clark Univ., Worcester, MA. |
Year Published |
2007 |
Stock Number |
PB2009-101838 |
Additional Subjects |
Dose-response relationships ;
Low dose irradiation ;
Environmental exposure ;
Health effects ;
Meetings ;
Risk assessments ;
Extrapolation ;
Neoplasms ;
Radiation doses ;
Cancer ;
Environmental pollutants ;
Uncertainty ;
Variability ;
Evaluation ;
Statistical data
|
Holdings |
Library |
Call Number |
Additional Info |
Location |
Last Modified |
Checkout Status |
NTIS |
PB2009-101838 |
Some EPA libraries have a fiche copy filed under the call number shown. |
|
07/26/2022 |
|
Collation |
31p |
Abstract |
Low-dose extrapolation model selection for evaluating the health effects of environmental pollutants is a key component of the risk assessment process. At a workshop held in Baltimore, MD, on April 23-24, 2007, and sponsored by U.S. Environmental Protection Agency and Johns Hopkins Risk Sciences and Public Policy Institute, a multidisciplinary group of experts reviewed the state of the science regarding low-dose extrapolation modeling and its application in environmental health risk assessments. Discussion topics were identified based on a literature review, which included examples for which human responses to ambient exposures have been extensively characterized for cancer and/or noncancer outcomes. Topics included: the need for formalized approaches and criteria to assess the evidence for mode of action; the use of human vs. animal data; the use of mode of action information in biologically-based models; and the implications of interindividual variability, background disease processes and background exposures in threshold vs. nonthreshold model choice. |