Risk projection methods allow for timely assessment of the potential magnitude of radiation-related cancer risks following low-dose radiation exposures. To estimate such risks directly through observational studies would generally require infeasibly large studies and long-term follow-up to achieve reasonable statistical power. We developed an online radiation risk assessment tool (RadRAT) which can be used to estimate the lifetime risk of radiation-related cancer with uncertainty intervals following a user-specified exposure history (https://irep.nci.nih.gov/radrat). The uncertainty intervals are a key component of the program because of the various assumptions that are involved in such calculations. The risk models used in RadRAT are broadly based on those developed by the BEIR VII committee for estimating lifetime risk following low-dose radiation exposure to the U.S. population for eleven site-specific cancers. We developed new risk models for seven additional cancer sites: oral, esophagus, gallbladder, pancreas, rectum, kidney and brain/central nervous system (CNS) cancers using data from the Japanese atomic bomb survivors. The lifetime risk estimates are slightly higher for RadRAT than for BEIR VII across all exposure ages mostly because the weighting of the excess relative risk and excess absolute risk models was conducted on an arithmetic rather than a logarithmic scale. The calculator can be used to estimate lifetime cancer risk from both uniform and non-uniform doses that are acute or chronic. It is most appropriate for low-LET radiation doses <1Gy, and for individuals with life-expectancy and cancer rates similar to the general population in the U.S.

The Interactive RadioEpidemiological Program (IREP) is a Web-based, interactive computer code that is used to estimate the probability that a given cancer in an individual was induced by given exposures to ionizing radiation. IREP was developed by a Working Group of the National Cancer Institute and Centers for Disease Control and Prevention, and was adopted and modified by the National Institute for Occupational Safety and Health (NIOSH) for use in adjudicating claims for compensation for cancer under the Energy Employees Occupational Illness Compensation Program Act of 2000. In this paper, the quantity calculated in IREP is referred to as “probability of causation/assigned share” (PC/AS). PC/AS for a given cancer in an individual is calculated on the basis of an estimate of the excess relative risk (ERR) associated with given radiation exposures and the relationship PC/AS = ERR/ERR+1. IREP accounts for uncertainties in calculating probability distributions of ERR and PC/AS. An accounting of uncertainty is necessary when decisions about granting claims for compensation for cancer are made on the basis of an estimate of the upper 99% credibility limit of PC/AS to give claimants the “benefit of the doubt.” This paper discusses models and methods incorporated in IREP to estimate ERR and PC/AS. Approaches to accounting for uncertainty are emphasized, and limitations of IREP are discussed. Although IREP is intended to provide unbiased estimates of ERR and PC/AS and their uncertainties to represent the current state of knowledge, there are situations described in this paper in which NIOSH, as a matter of policy, makes assumptions that give a higher estimate of the upper 99% credibility limit of PC/AS than other plausible alternatives and, thus, are more favorable to claimants.

This paper presents so-called radiation effectiveness factors that are intended to represent the biological effectiveness of different radiation types, relative to high-energy Co gamma rays, for the purpose of estimating cancer risks and probability of causation of radiogenic cancers in identified individuals. Radiation effectiveness factors are expressed as subjective probability distributions to represent uncertainty that arises from uncertainties in estimates of relative biological effectiveness obtained from radiobiological studies of stochastic endpoints, limited data on biological effectiveness obtained from human epidemiological studies, and other judgments involved in evaluating the applicability of available information to induction of cancers in humans. Primarily on the basis of reviews and evaluations of available data by experts, probability distributions of radiation effectiveness factors are developed for the following radiation types: neutrons of energy less than 10 keV, 10-100 keV, 0.1-2 MeV (including fission neutrons), 2-20 MeV, and greater than 20 MeV; alpha particles of any energy emitted by radionuclides; photons of energy 30-250 keV and less than 30 keV; and electrons of energy less than 15 keV. Photons of energy greater than 250 keV and electrons of energy greater than 15 keV are assumed to have the same biological effectiveness as reference Co gamma rays and are assigned a radiation effectiveness factor of unity, without uncertainty. For neutrons and alpha particles, separate probability distributions of radiation effectiveness factors are developed for solid tumors and leukemias, and small corrections to represent an inverse dose-rate effect are applied to those distributions in cases of chronic exposure. A radiation effectiveness factor different from unity for 15-60 keV electrons is discussed but is not adopted due to a lack of relevant radiobiological data. Radiation effectiveness factors presented in this paper are incorporated in the Interactive RadioEpidemiological Program and were developed for use by The National Institute for Occupational Safety and Health and U.S. Department of Labor in evaluating claims for compensation for radiogenic cancers by workers at U.S. Department of Energy facilities.

Quantification of uncertainties in doses from intakes of radionuclides is important in risk assessments and epidemiologic studies of individuals exposed to radiation. In this study, the uncertainties in the doses per unit intake (i.e., dose coefficients) for ingestion of 131I, 137Cs, and 90Sr by healthy individuals have been determined. Age-dependent thyroid dose coefficients were derived for 131I. The analysis for 131I uses recent measurements of thyroid volume obtained by ultrasonography, which indicate a thyroid mass lower than that previously obtained using autopsy measurements. The coefficients for 137Cs are determined using the relationship between the biological half-lives and the amount of potassium in the human body. The most recent International Commission on Radiological Protection biokinetic model was employed to determine the uncertainties for 90Sr. For 137Cs and 90Sr, the dose coefficients represent exposure in adulthood and they were determined for all organs of radiological importance. The uncertainty in the estimated dose coefficients represent state of knowledge estimates for a reference individual, and they are described by lognormal distributions with a specified geometric mean (GM) and geometric standard deviation (GSD). The estimated geometric means vary only slightly from the dose coefficients reported by ICRP publications. The largest uncertainty is observed in the dose coefficients for bone surface (GSD = 2.6), and red bone marrow (GSD = 2.4) in the case of ingestion of 90Sr. For most other organs, the uncertainty in the 90Sr dose coefficients is characterized by a GSD of 1.8 (or less for some organs). For 131I, the uncertainty in the thyroid dose coefficients is well represented by a GSD of 1.7 for both sexes and all ages other than infants for whom a GSD of 1.8 is more appropriate. The lowest uncertainties are obtained for the dose coefficients from ingestion of 137Cs (GSD = 1.24 for males; 1.4 for females). A dominant source of uncertainty in the ingestion dose coefficients is the variation of the biokinetic parameters. For 131I, the largest contribution to the uncertainty comes from the variation in the thyroid mass, but the contribution of the biokinetic parameters is comparable. The biokinetic parameters with the largest contribution to the uncertainty are (a) the fractional uptake from blood to thyroid in the case of ingestion of 131I, (b) the absorbed fraction from the gastrointestinal tract (f1) in the case of 90Sr, and (c) the amount of potassium in the body for 137Cs. The contribution to the uncertainty of the absorbed fraction (which accounts for the fraction of energy deposited in the target organ) is the smallest contributor to the uncertainty in the dose coefficients for most organs. To reduce the uncertainty in the dose estimated for a real individual, one should determine the above-mentioned parameters for the specified individual rather than to rely on assumptions for a reference individual.

The radioactive isotopes of strontium have always been a major concern in radiation protection. Currently, radiostrontium is of interest for evaluation of the health effects of the Chernobyl accident and for epidemiological studies in populations exposed to releases from the Mayak nuclear facilities in Russia. Ingestion is one of the most important exposure pathways involving radioactive strontium. The main sources of published data on the fraction of the ingested strontium that is transferred to plasma (f1) are summarized. For some of these studies, the original data had to be reanalyzed and a new iterative method to account for the elimination in feces of strontium of endogenous origin (i.e., that was absorbed to blood and has already been returned into feces) was employed. Data indicate no significant dependence of the absorbed fraction on sex or age at exposure within the adult group, but absorption of strontium is reduced if the intake of stable calcium is very high and is enhanced if the intake of calcium is very low. The probability distribution function of f1 values is well represented by a lognormal curve with a geometric mean of 22.3% and a geometric standard deviation of 1.44 (95% confidence interval 10.9% to 45.6%, or about a factor of 2 around the geometric mean). This distribution can be considered representative for the variability of the f1 values in a population of healthy adults.