Publication related to RSI or an RSI staff member
A model-free approach to low-dose extrapolation.
Estimates of risk associated with exposure to low levels of carcinogenic substances present in the environment are generally obtained by linear extrapolation from higher exposure levels at which risks can be estimated directly. In this paper, we examine the scientific basis for the assumption of low-dose linearity in carcinogenic risk assessment and the different statistical methods that have been proposed for linear extrapolation. A model-free approach to linear extrapolation is described and illustrated using epidemiological data on radiation carcinogenesis. The statistical properties of this method are empirically assessed using 572 selected sets of bioassay data.
Authors
- Krewski, D, Krewski D, Health Protection Branch, Health and Welfare Canada, Ottawa, Ontario.
- Gaylor, D, Gaylor D,
- Szyszkowicz, M, Szyszkowicz M,
YEAR OF PUBLICATION: 1991
SOURCE: Environ Health Perspect. 1991 Jan;90:279-85. doi: 10.1289/ehp.90-1519485.
JOURNAL TITLE ABBREVIATION: Environ Health Perspect
JOURNAL TITLE: Environmental health perspectives
ISSN: 0091-6765 (Print) 0091-6765 (Linking)
VOLUME: 90
PAGES: 279-85
PLACE OF PUBLICATION: United States
ABSTRACT:
Estimates of risk associated with exposure to low levels of carcinogenic substances present in the environment are generally obtained by linear extrapolation from higher exposure levels at which risks can be estimated directly. In this paper, we examine the scientific basis for the assumption of low-dose linearity in carcinogenic risk assessment and the different statistical methods that have been proposed for linear extrapolation. A model-free approach to linear extrapolation is described and illustrated using epidemiological data on radiation carcinogenesis. The statistical properties of this method are empirically assessed using 572 selected sets of bioassay data.
Estimates of risk associated with exposure to low levels of carcinogenic substances present in the environment are generally obtained by linear extrapolation from higher exposure levels at which risks can be estimated directly. In this paper, we examine the scientific basis for the assumption of low-dose linearity in carcinogenic risk assessment and the different statistical methods that have been proposed for linear extrapolation. A model-free approach to linear extrapolation is described and illustrated using epidemiological data on radiation carcinogenesis. The statistical properties of this method are empirically assessed using 572 selected sets of bioassay data.
LANGUAGE: eng
DATE OF PUBLICATION: 1991 Jan
DATE COMPLETED: 19910725
DATE REVISED: 20181113
MESH DATE: 1991/01/01 00:01
EDAT: 1991/01/01 00:00
STATUS: MEDLINE
PUBLICATION STATUS: ppublish
OWNER: NLM
Related RSI Experts
Chief Risk Scientist
Dr. Daniel Krewski is Chief Risk Scientist and co-founder of Risk Sciences International (RSI), a firm established in 2006 to bring evidence-based, multidisciplinary expertise to the challenge of understanding, managing, and communicating risk. As RSI’s inaugural CEO and long-time scientific...