Uncertainties in estimating health risks associated with exposure to ionising radiation

Abstract

The information for the present discussion on the uncertainties associated with estimation of radiation risks and probability of disease causation was assembled for the recently published NCRP Report No. 171 on this topic. This memorandum provides a timely overview of the topic, given that quantitative uncertainty analysis is the state of the art in health risk assessment and given its potential importance to developments in radiation protection. Over the past decade the increasing volume of epidemiology data and the supporting radiobiology findings have aided in the reduction of uncertainty in the risk estimates derived. However, it is equally apparent that there remain significant uncertainties related to dose assessment, low dose and low dose-rate extrapolation approaches (e.g. the selection of an appropriate dose and dose-rate effectiveness factor), the biological effectiveness where considerations of the health effects of high-LET and lower-energy low-LET radiations are required and the transfer of risks from a population for which health effects data are available to one for which such data are not available. The impact of radiation on human health has focused in recent years on cancer, although there has been a decided increase in the data for noncancer effects together with more reliable estimates of the risk following radiation exposure, even at relatively low doses (notably for cataracts and cardiovascular disease). New approaches for the estimation of hereditary risk have been developed with the use of human data whenever feasible, although the current estimates of heritable radiation effects still are based on mouse data because of an absence of effects in human studies. Uncertainties associated with estimation of these different types of health effects are discussed in a qualitative and semi-quantitative manner as appropriate. The way forward would seem to require additional epidemiological studies, especially studies of low dose and low dose-rate occupational and perhaps environmental exposures and for exposures to x rays and high-LET radiations used in medicine. The development of models for more reliably combining the epidemiology data with experimental laboratory animal and cellular data can enhance the overall risk assessment approach by providing biologically refined data to strengthen the estimation of effects at low doses as opposed to the sole use of mathematical models of epidemiological data that are primarily driven by medium/high doses. NASA's approach to radiation protection for astronauts, although a unique occupational group, indicates the possible applicability of estimates of risk and their uncertainty in a broader context for developing recommendations on: (1) dose limits for occupational exposure and exposure of members of the public; (2) criteria to limit exposures of workers and members of the public to radon and its short-lived decay products; and (3) the dosimetric quantity (effective dose) used in radiation protection.

Cardiovascular diseases related to ionizing radiation: The risk of low-dose exposure (Review)

“…Once we have a comprehensive understanding of the underlying biological mechanisms, biologically-based dose-response models can be included in the dose risk assessment. This may prove to be beneficial for an accurate risk estimation in the low-dose region (49). …”

Donor-Specific Cell-Based Assays in Studying Sensitivity to Low-Dose Radiation: A Population-Based Perspective

“…Its major mechanism of carcinogenicity is DNA damage ( 1 , 2 ). In contrast, risk estimates from epidemiological studies examining low radiation doses (<0.2 Gy) suffer from a significant uncertainty ( 3 , 4 ). The biological effects of low-dose radiation differ from those observed at high doses and are mostly unrelated to DNA damage per se ( 5 – 13 ).…”

Are the studies on cancer risk from CT scans biased by indication? Elements of answer from a large-scale cohort study in France

“…One initial approach to such an assessment is to use robust epidemiological results obtained at higher doses to predict the cancer risks related to these low-dose exposures. Although this approach makes it possible to estimate an expected magnitude of potential risks ( Brenner and Hall, 2007 ; Ivanov et al , 2012 ; Krille et al , 2012 ; Calandrino et al , 2013 ; Miglioretti et al , 2013 ; Journy et al , 2014 ), its validity has been widely debated in view of hypotheses underlying those extrapolations, in particular of a no-threshold relation between cancer risk and radiation exposure ( Brenner and Sachs, 2006 ; Mothersill and Seymour, 2013 ; Preston et al , 2013 ).…”