Extrapolating radiation-induced cancer risks from low doses to very low doses

Center for Radiological Research, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA.
Health physics (Impact Factor: 0.77). 11/2009; 97(5):505-9. DOI: 10.1097/HP.0b013e3181ad7f04
Source: PubMed

ABSTRACT There is strong evidence that ionizing radiation increases cancer risks at high doses (e.g., >or=1 Gy), and persuasive, if controversial, epidemiological evidence that cancer risks are increased at low doses ( approximately 10 mGy). Discussed here are the issues related to extrapolating radiation risks from low radiation doses to very low doses (<or=1 mGy) - for which purpose we are forced to rely on radiobiological evidence and biophysical arguments. At high doses, cells are typically hit by many tracks of radiation, while at low doses most cells are typically hit by a single track of radiation; at very low doses proportionately fewer cells are hit, again only by a single track of radiation. Thus, in comparing low doses to very low doses, the damage to hit cells remains essentially the same (a single radiation track passing through a cell), but what changes is the number of cells that are subjected to this same damage, which decreases linearly as the dose decreases. This is the argument for a linear no-threshold (LNT) model. It is important to emphasize that this LNT argument only applies to the extrapolation from low doses to very low doses, not from high to low doses. Of course there are caveats to this argument, such as the potential effects of phenomena such as inter-cellular communication and immunosurveillance, and the possibility of different radiobiological processes at very low doses, compared to low doses. However, there is little conclusive experimental evidence about the significance of these phenomena at very low doses, and comparative mechanistic studies at high doses vs. low doses will not be informative in this context. At present, we do not know whether such radiobiological phenomena would produce small or large perturbations, or even whether they would increase or decrease cancer risks at very low doses, compared with the prediction of a linear extrapolation from low doses.

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    • "The errors in the cancer risk model as presented in the BEIR VII report are estimated at a factor of 2 or 3 for the purpose of estimating risks from low-dose x-ray exposure (National Research Council 2006). In addition, carcinogenic risks induced by low doses and also the age-dependency of dose risk have been the subject of dispute; it has been suggested that the risk after exposure in middle age may be up to twice as high as currently estimated by the standard models (Dendy and Brugmans 2003; Tubiana 2005; Brenner 2009; Shuryak et al. 2010). Therefore, the authors expect that the errors in the cancer risk model are dominant over the limitations aforementioned. "
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    ABSTRACT: The aim of this study was to compare the summing method (A) with the complement method (B) for calculating the cumulative lifetime-attributable-risk (LARtot) of tumor incidence and mortality of multiple CT exposures. Method A defines LARtot as the summation of the risk of each separate exposure. Method B was defined as the complement of the probability of inducing no cancer in N separate exposures. The risk of each separate exposure was estimated using dose, gender, and age at exposure (BEIR VII phase 2). Both methods were compared in a simulation and applied to a database of 11,884 patients exposed to multiple CTs. The relative difference between the methods was defined as ΔP%. Simulation confirmed that Method A always overestimates LARtot. ΔP% was proportional to the dose per exposure and the number of exposures. The differences between Methods A and B were small. Average LARtot of tumor incidence was 0.140% (Method A) and 0.139% (Method B) with maxima of 5.70% and 5.56%, respectively. Average LARtot of mortality was 0.085% for both methods, with maxima of 2.20% and 2.18%, respectively. ΔP% was highest (2.43%) for a female patient (3-y old) exposed to eight recurrent scans and a cumulative dose of 144 mSv. Although Method B is more accurate, both methods can be used to estimate the cumulative risk of multiple CT exposures. These results have to be interpreted, however, in the perspective of the uncertainties in the cancer risk model, which have been estimated at a factor of 2 or 3.
    Health physics 04/2014; 106(4):475-83. DOI:10.1097/HP.0000000000000083 · 0.77 Impact Factor
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    • "Effects of Ionizing Radiation (BEIR) defines a low dose as being in the range from near zero up to about 100 millisieverts (National Research Council, 2006). Others argue that only doses below about 10 millisieverts (mSv) are low (Brenner, 2009). "
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    ABSTRACT: There is scientific consensus on a prevailing hypothesis that, down to near-zero levels, the occurrence of future cancer is proportional to the dose of radiation received. Some experts and professional bodies in the field, however, subscribe to this linear no-threshold (LNT) model in scientific discussions but object to the use of the model for policy-related purposes. Given the large economic interests that are affected by policy decisions, this article recommends that experts and professional bodies avoid the intermingling of scientific and policy debates and acknowledge a logical implication of the LNT hypothesis: Low-dose radiation will sicken and kill a number of people over time.
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