| Title |
Estimating radiation-induced cancer risks at very low doses: rationale for using a linear no-threshold approach
|
|---|---|
| Published in |
Radiation and Environmental Biophysics, February 2006
|
| DOI | 10.1007/s00411-006-0029-4 |
| Pubmed ID | |
| Authors |
David J. Brenner, Rainer K. Sachs |
| Abstract |
The possible cancer risks caused by ionizing radiation doses of ~1 mSv or less are too small to be estimated directly from epidemiological data. The linear no-threshold (LNT) approach to estimating such risks involves using epidemiological data at higher (but still low) doses to establish an "anchor point", and then extrapolating the excess cancer risk linearly down from this point to the low dose of interest. The study in this issue by Professor Tubiana and colleagues, summarizing a French Academy of Sciences report, argues that such LNT extrapolations systematically give substantial overestimates of the excess cancer risk at very low doses. We suggest that, to the contrary, even if there are significant deviations from linearity in the relevant dose range, potentially caused by the effects of inter-cellular interactions or immune surveillance, we know almost nothing quantitatively about these effects. Consequently, we do not know the magnitude, nor even the direction of any such deviations from linearity-the risks could indeed be lower than those predicted by a linear extrapolation, but they could well be higher. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 1% |
| Brazil | 1 | 1% |
| India | 1 | 1% |
| Belarus | 1 | 1% |
| Nigeria | 1 | 1% |
| Unknown | 73 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 23% |
| Student > Ph. D. Student | 15 | 19% |
| Other | 8 | 10% |
| Student > Master | 6 | 8% |
| Professor | 5 | 6% |
| Other | 13 | 17% |
| Unknown | 13 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 23% |
| Physics and Astronomy | 14 | 18% |
| Agricultural and Biological Sciences | 12 | 15% |
| Biochemistry, Genetics and Molecular Biology | 5 | 6% |
| Environmental Science | 3 | 4% |
| Other | 6 | 8% |
| Unknown | 20 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 January 2012.
All research outputs
#16,049,105
of 23,815,455 outputs
Outputs from Radiation and Environmental Biophysics
#331
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#136,033
of 158,907 outputs
Outputs of similar age from Radiation and Environmental Biophysics
#3
of 4 outputs
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