Document Detail


Radiation hormesis: historical perspective and implications for low-dose cancer risk assessment.
MedLine Citation:
PMID:  20585444     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
Current guidelines for limiting exposure of humans to ionizing radiation are based on the linear-no-threshold (LNT) hypothesis for radiation carcinogenesis under which cancer risk increases linearly as the radiation dose increases. With the LNT model even a very small dose could cause cancer and the model is used in establishing guidelines for limiting radiation exposure of humans. A slope change at low doses and dose rates is implemented using an empirical dose and dose rate effectiveness factor (DDREF). This imposes usually unacknowledged nonlinearity but not a threshold in the dose-response curve for cancer induction. In contrast, with the hormetic model, low doses of radiation reduce the cancer incidence while it is elevated after high doses. Based on a review of epidemiological and other data for exposure to low radiation doses and dose rates, it was found that the LNT model fails badly. Cancer risk after ordinarily encountered radiation exposure (medical X-rays, natural background radiation, etc.) is much lower than projections based on the LNT model and is often less than the risk for spontaneous cancer (a hormetic response). Understanding the mechanistic basis for hormetic responses will provide new insights about both risks and benefits from low-dose radiation exposure.
Authors:
Alexander M Vaiserman
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Publication Detail:
Type:  Journal Article     Date:  2010-01-18
Journal Detail:
Title:  Dose-response : a publication of International Hormesis Society     Volume:  8     ISSN:  1559-3258     ISO Abbreviation:  Dose Response     Publication Date:  2010  
Date Detail:
Created Date:  2010-06-29     Completed Date:  2011-07-14     Revised Date:  2013-05-29    
Medline Journal Info:
Nlm Unique ID:  101308899     Medline TA:  Dose Response     Country:  United States    
Other Details:
Languages:  eng     Pagination:  172-91     Citation Subset:  -    
Affiliation:
Laboratory of Mathematical Modeling of Aging Processes, Institute of Gerontology, Kiev, Ukraine.
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