Minimum latency effects for cancer associated with exposures to radiation or other carcinogens.

BACKGROUND: In estimating radiation-associated cancer risks a fixed period for the minimum latency is often assumed. Two empirical latency functions have been used to model latency, continuously increasing from 0. A stochastic biologically-based approach yields a still more plausible way of describing latency and can be directly estimated from clinical data. METHODS: We derived the parameters for a stochastic biologically-based model from tumour growth data for various cancers, and least-squares fitted the two types of empirical latency function to the stochastic model-predicted cumulative probability. RESULTS: There is wide variation in growth rates among tumours, particularly slow for prostate and thyroid cancer and particularly fast for leukaemia. The slow growth rate for prostate and thyroid tumours implies that the number of tumour cells required for clinical detection cannot greatly exceed 106. For all tumours, both empirical latency functions closely approximated the predicted biological model cumulative probability. CONCLUSIONS: Our results, illustrating use of a stochastic biologically-based model using clinical data not tied to any particular carcinogen, have implications for estimating latency associated with any mutagen. They apply to tumour growth in general, and may be useful for example, in planning screenings for cancer using imaging techniques.

Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms.

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.

ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence.

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.

Methods to account for uncertainties in exposure assessment in studies of environmental exposures.

BACKGROUND: Accurate exposure estimation in environmental epidemiological studies is crucial for health risk assessment. Failure to account for uncertainties in exposure estimation could lead to biased results in exposure-response analyses. Assessment of the effects of uncertainties in exposure estimation on risk estimates received a lot of attention in radiation epidemiology and in several studies of diet and air pollution. The objective of this narrative review is to examine the commonly used statistical approaches to account for exposure estimation errors in risk analyses and to suggest how each could be applied in environmental epidemiological studies. MAIN TEXT: We review two main error types in estimating exposures in epidemiological studies: shared and unshared errors and their subtypes. We describe the four main statistical approaches to adjust for exposure estimation uncertainties (regression calibration, simulation-extrapolation, Monte Carlo maximum likelihood and Bayesian model averaging) along with examples to give readers better understanding of their advantages and limitations. We also explain the advantages of using a 2-dimensional Monte-Carlo (2DMC) simulation method to quantify the effect of uncertainties in exposure estimates using full-likelihood methods. For exposures that are estimated independently between subjects and are more likely to introduce unshared errors, regression calibration and SIMEX methods are able to adequately account for exposure uncertainties in risk analyses. When an uncalibrated measuring device is used or estimation parameters with uncertain mean values are applied to a group of people, shared errors could potentially be large. In this case, Monte Carlo maximum likelihood and Bayesian model averaging methods based on estimates of exposure from the 2DMC simulations would work well. The majority of reviewed studies show relatively moderate changes (within 100%) in risk estimates after accounting for uncertainties in exposure estimates, except for the two studies which doubled/tripled naïve estimates. CONCLUSIONS: In this paper, we demonstrate various statistical methods to account for uncertain exposure estimates in risk analyses. The differences in the results of various adjustment methods could be due to various error structures in datasets and whether or not a proper statistical method was applied. Epidemiological studies of environmental exposures should include exposure-response analyses accounting for uncertainties in exposure estimates.

Organ-specific dose coefficients derived from Monte Carlo simulations for historical (1930s to 1960s) fluoroscopic and radiographic examinations of tuberculosis patients.

This work provides dose coefficients necessary to reconstruct doses used in epidemiological studies of tuberculosis patients treated from the 1930s through the 1960s, who were exposed to diagnostic imaging while undergoing treatment. We made use of averaged imaging parameters from measurement data, physician interviews, and available literature of the Canadian Fluoroscopy Cohort Study and, on occasion, from a similar study of tuberculosis patients from Massachusetts, United States, treated between 1925 and 1954. We used computational phantoms of the human anatomy and Monte Carlo radiation transport methods to compute dose coefficients that relate dose in air, at a point 20 cm away from the source, to absorbed dose in 58 organs. We selected five male and five female phantoms, based on the mean height and weight of Canadian tuberculosis patients in that era, for the 1-, 5-, 10-, 15-year old and adult ages. Using high-performance computers at the National Institutes of Health, we simulated 2,400 unique fluoroscopic and radiographic exposures by varying x-ray beam quality, field size, field shuttering, imaged anatomy, phantom orientation, and computational phantom. Compared with previous dose coefficients reported for this population, our dosimetry system uses improved anatomical phantoms constructed from computed tomography imaging datasets. The new set of dose coefficients includes tissues that were not previously assessed, in particular, for tissues outside the x-ray field or for pediatric patients. In addition, we provide dose coefficients for radiography and for fluoroscopic procedures not previously assessed in the dosimetry of this cohort (i.e. pneumoperitoneum and chest aspirations). These new dose coefficients would allow a comprehensive assessment of exposures in the cohort. In addition to providing newly derived dose coefficients, we believe the automation and methods developed to complete these dosimetry calculations are generalizable and can be applied to other epidemiological studies interested in an exposure assessment from medical x-ray imaging. These epidemiological studies provide important data for assessing health risks of radiation exposure to help inform the current system of radiological protection and efforts to optimize the use of radiation in medical studies.

Estimation of Heights and Body Masses of Tuberculosis Patients in the Canadian Fluoroscopy Cohort Study for Use in Individual Dosimetry.

ABSTRACT: This paper documents the estimation of mean heights and body masses, by age and sex, used in development of organ-specific dose conversion coefficients for external radiation for a historical cohort of about 64,000 patients from the Canadian Fluoroscopy Cohort Study. Patients were exposed to repeated fluoroscopy and chest radiography examinations in the course of treatment for tuberculosis in residential medical facilities throughout Canada between 1930 and 1969. Using Canadian national survey data and extensive literature review, mean heights and masses were obtained for the White population of Canada during the time period of interest, and the differences in mean body mass between tuberculosis patients and the general population were estimated. Results in terms of mean height and body mass of Canadian tuberculosis patients, with uncertainties, are reported for selected age groups (children of ages 1, 5, 10, and 15 y and adults age 20+) and for both sexes. Use of estimated average heights and body masses by age and sex permits the adjustment of computerized phantoms for body mass for a given age, thereby increasing the relevance of the organ-specific dose conversion coefficients for the cohort and improving the accuracy of the resulting estimated organ doses.

Fluoroscopy X-Ray Organ-Specific Dosimetry System (FLUXOR) for Estimation of Organ Doses and Their Uncertainties in the Canadian Fluoroscopy Cohort Study.

As part of ongoing efforts to assess lifespan disease mortality and incidence in 63,715 patients from the Canadian Fluoroscopy Cohort Study (CFCS) who were treated for tuberculosis between 1930 and 1969, we developed a new FLUoroscopy X-ray ORgan-specific dosimetry system (FLUXOR) to estimate radiation doses to various organs and tissues. Approximately 45% of patients received medical procedures accompanied by fluoroscopy, including artificial pneumothorax (air in pleural cavity to collapse of lungs), pneumoperitoneum (air in peritoneal cavity), aspiration of fluid from pleural cavity and gastrointestinal series. In addition, patients received chest radiographs for purposes of diagnosis and monitoring of disease status. FLUXOR utilizes age-, sex- and body size-dependent dose coefficients for fluoroscopy and radiography exams, estimated using radiation transport simulations in up-to-date computational hybrid anthropomorphic phantoms. The phantoms include an updated heart model, and were adjusted to match the estimated mean height and body mass of tuberculosis patients in Canada during the relevant time period. Patient-specific data (machine settings, exposure duration, patient orientation) used during individual fluoroscopy or radiography exams were not recorded. Doses to patients were based on parameter values inferred from interviews with 91 physicians practicing at the time, historical literature, and estimated number of procedures from patient records. FLUXOR uses probability distributions to represent the uncertainty in the unknown true, average value of each dosimetry parameter. Uncertainties were shared across all patients within specific subgroups of the cohort, defined by age at treatment, sex, type of procedure, time period of exams and region (Nova Scotia or other provinces). Monte Carlo techniques were used to propagate uncertainties, by sampling alternative average values for each parameter. Alternative average doses per exam were estimated for patients in each subgroup, with the total average dose per individual determined by the number of exams received. This process was repeated to produce alternative cohort vectors of average organ doses per patient. This article presents estimates of doses to lungs, female breast, active bone marrow and heart wall. Means and 95% confidence intervals (CI) of average organ doses across all 63,715 patients were 320 (160, 560) mGy to lungs, 250 (120, 450) mGy to female breast, 190 (100, 340) mGy to heart wall and 92 (47, 160) mGy to active bone marrow. Approximately 60% of all patients had average doses to the four studied organs of less than 10 mGy, 10% received between 10 and 100 mGy, 25% between 100 and 1,000 mGy, and 5% above 1,000 mGy. Pneumothorax was the medical procedure that accounted for the largest contribution to cohort average doses. The major contributors to uncertainty in estimated doses per procedure for the four organs of interest are the uncertainties in exposure duration, tube voltage, tube output, and patient orientation relative to the X-ray tube, with the uncertainty in exposure duration being most often the dominant source. Uncertainty in patient orientation was important for doses to female breast, and, to a lesser degree, for doses to heart wall. The uncertainty in number of exams was an important contributor to uncertainty for ∼30% of patients. The estimated organ doses and their uncertainties will be used for analyses of incidence and mortality of cancer and non-cancer diseases. The CFCS cohort is an important addition to existing radio-epidemiological cohorts, given the moderate-to-high doses received fractionated over several years, the type of irradiation (external irradiation only), radiation type (X rays only), a balanced combination of both genders and inclusion of people of all ages.

Organ Doses from Chest Radiographs in Tuberculosis Patients in Canada and Their Uncertainties in Periods from 1930 to 1969.

This paper describes a study to estimate absorbed doses to various organs from film-based chest radiographs and their uncertainties in the periods 1930 to 1948, 1949 to 1955, and 1956 to 1969. Estimated organ doses will be used in new analyses of risks of cancer and other diseases in tuberculosis patients in Canada who had chest fluoroscopic and radiographic examinations in those periods. In this paper, doses to lungs, female breast, active bone marrow, and heart from a single chest radiograph in adults and children of ages 1, 5, 10, and 15 y in the Canadian cohort and their uncertainties are estimated using (1) data on the tube voltage (kV), total filtration (mm Al), tube-current exposure-time product (mA s), and tube output (mR [mA s]) in each period; (2) assumptions about patient orientation, distance from the source to the skin of a patient, and film size; and (3) new calculations of sex- and age-specific organ dose conversion coefficients (organ doses per dose in air at skin entrance). Variations in estimated doses to each organ across the three periods are less than 20% in adults and up to about 30% at younger ages. Uncertainties in estimated organ doses are about a factor of 2 to 3 in adults and up to a factor of 4 at younger ages and are due mainly to uncertainties in the tube voltage and tube-current exposure-time product.

Probability Distribution of Dose and Dose-Rate Effectiveness Factor for use in Estimating Risks of Solid Cancers From Exposure to Low-Let Radiation.

This paper presents an analysis to develop a subjective state-of-knowledge probability distribution of a dose and dose-rate effectiveness factor for use in estimating risks of solid cancers from exposure to low linear energy transfer radiation (photons or electrons) whenever linear dose responses from acute and chronic exposure are assumed. A dose and dose-rate effectiveness factor represents an assumption that the risk of a solid cancer per Gy at low acute doses or low dose rates of low linear energy transfer radiation, RL, differs from the risk per Gy at higher acute doses, RH; RL is estimated as RH divided by a dose and dose-rate effectiveness factor, where RH is estimated from analyses of dose responses in Japanese atomic-bomb survivors. A probability distribution to represent uncertainty in a dose and dose-rate effectiveness factor for solid cancers was developed from analyses of epidemiologic data on risks of incidence or mortality from all solid cancers as a group or all cancers excluding leukemias, including (1) analyses of possible nonlinearities in dose responses in atomic-bomb survivors, which give estimates of a low-dose effectiveness factor, and (2) comparisons of risks in radiation workers or members of the public from chronic exposure to low linear energy transfer radiation at low dose rates with risks in atomic-bomb survivors, which give estimates of a dose-rate effectiveness factor. Probability distributions of uncertain low-dose effectiveness factors and dose-rate effectiveness factors for solid cancer incidence and mortality were combined using assumptions about the relative weight that should be assigned to each estimate to represent its relevance to estimation of a dose and dose-rate effectiveness factor. The probability distribution of a dose and dose-rate effectiveness factor for solid cancers developed in this study has a median (50th percentile) and 90% subjective confidence interval of 1.3 (0.47, 3.6). The harmonic mean is 1.1, which implies that the arithmetic mean of an uncertain estimate of the risk of a solid cancer per Gy at low acute doses or low dose rates of low linear energy transfer radiation is only about 10% less than the mean risk per Gy at higher acute doses. Data were also evaluated to define a low acute dose or low dose rate of low linear energy transfer radiation, i.e., a dose or dose rate below which a dose and dose-rate effectiveness factor should be applied in estimating risks of solid cancers.

The Hanford Thyroid Disease Study: an alternative view of the findings.

The Hanford Thyroid Disease Study (HTDS) is one of the largest and most complex epidemiologic studies of the relation between environmental exposures to I and thyroid disease. The study detected no dose-response relation using a 0.05 level for statistical significance. The results for thyroid cancer appear inconsistent with those from other studies of populations with similar exposures, and either reflect inadequate statistical power, bias, or unique relations between exposure and disease risk. In this paper, we explore these possibilities, and present evidence that the HTDS statistical power was inadequate due to complex uncertainties associated with the mathematical models and assumptions used to reconstruct individual doses. We conclude that, at the very least, the confidence intervals reported by the HTDS for thyroid cancer and other thyroid diseases are too narrow because they fail to reflect key uncertainties in the measurement-error structure. We recommend that the HTDS results be interpreted as inconclusive rather than as evidence for little or no disease risk from Hanford exposures.

Method for analyzing left-censored bioassay data in large cohort studies.

In retrospective epidemiological studies of large cohorts of workers exposed to radioactive materials, it is often necessary to analyze large numbers of bioassay data sets containing censored values, or values recorded as less than a detection limit. Censored bioassay data create problems for all bioassay analysis methods, including analytical techniques based on least-squares regression to estimate intakes. A method is presented here that uses a simple empirically-derived equation for imputing replacement values for urine uranium concentration results reported as zero or less than a detection limit, that produces minimal bias in intakes estimated using least-square regression methods with the assumption of lognormally distributed measurement errors.

Exposure to Recycled Uranium Contaminants in Gaseous Diffusion Plants.

As part of an ongoing study of health effects in a pooled cohort of gaseous diffusion plant workers, organ dose from internal exposure to uranium was evaluated. Due to the introduction of recycled uranium into the plants, there was also potential for exposure to radiologically significant levels of 99Tc, 237Np and 238,239Pu. In the evaluation of dose response, these radionuclide exposures could confound the effect of internal uranium. Using urine bioassay data for study subjects reported in facility records, intakes and absorbed dose to bone surface, red bone marrow and kidneys were estimated as these organs were associated with a priori outcomes of interest. Additionally, 99Tc intakes and doses were calculated using a new systemic model for technetium and compared to intakes and doses calculated using the current model recommended by the International Commission on Radiological Protection. Organ absorbed doses for the transuranics were significant compared to uranium doses; however, 99Tc doses calculated using the new systemic model were significant as well. Use of the new model resulted in an increase in 99Tc-related absorbed organ dose of a factor of 8 (red bone marrow) to 30 (bone surface).

Internal exposure to uranium in a pooled cohort of gaseous diffusion plant workers.

Intakes and absorbed organ doses were estimated for 29 303 workers employed at three former US gaseous diffusion plants as part of a study of cause-specific mortality and cancer incidence in uranium enrichment workers. Uranium urinalysis data (>600 000 urine samples) were available for 58 % of the pooled cohort. Facility records provided uranium gravimetric and radioactivity concentration data and allowed estimation of enrichment levels of uranium to which workers may have been exposed. Urine data were generally recorded with facility department numbers, which were also available in study subjects' work histories. Bioassay data were imputed for study subjects with no recorded sample results (33 % of pooled cohort) by assigning department average urine uranium concentration. Gravimetric data were converted to 24-h uranium activity excretion using department average specific activities. Intakes and organ doses were calculated assuming chronic exposure by inhalation to a 5-µm activity median aerodynamic diameter aerosol of soluble uranium. Median intakes varied between 0.31 and 0.74 Bq d(-1) for the three facilities. Median organ doses for the three facilities varied between 0.019 and 0.051, 0.68 and 1.8, 0.078 and 0.22, 0.28 and 0.74, and 0.094 and 0.25 mGy for lung, bone surface, red bone marrow, kidneys, and liver, respectively. Estimated intakes and organ doses for study subjects with imputed bioassay data were similar in magnitude.

Testing prediction capabilities of an 131I terrestrial transport model by using measurements collected at the Hanford nuclear facility.

A model describing transport of 131I in the environment was developed by SENES Oak Ridge, Inc., for assessment of radiation doses and excess lifetime risk from 131I atmospheric releases from Oak Ridge Reservation in Oak Ridge, Tennessee, and from Idaho National Engineering and Environmental Laboratory in southeast Idaho. This paper describes the results of an exercise designed to test the reliability of this model and to identify the main sources of uncertainty in doses and risks estimated by this model. The testing of the model was based on materials published by the International Atomic Energy Agency BIOMASS program, specifically environmental data collected after the release into atmosphere of 63 curies of 131I during 2-5 September 1963, after an accident at the Hanford PUREX Chemical Separations Plant, in Hanford, Washington. Measurements of activity in air, vegetation, and milk were collected in nine counties around Hanford during the first couple of months after the accident. The activity of 131I in the thyroid glands of two children was measured 47 d after the accident. The model developed by SENES Oak Ridge, Inc., was used to estimate concentrations of 131I in environmental media, thyroid doses for the general population, and the activity of 131I in thyroid glands of the two children. Predicted concentrations of 131I in pasture grass and milk and thyroid doses were compared with similar estimates produced by other modelers. The SENES model was also used to estimate excess lifetime risk of thyroid cancer due to the September 1963 releases of 131I from Hanford. The SENES model was first calibrated and then applied to all locations of interest around Hanford without fitting the model parameters to a given location. Predictions showed that the SENES model reproduces satisfactorily the time-dependent and the time-integrated measured concentrations in vegetation and milk, and provides reliable estimates of 131I activity in thyroids of children. SENES model generated concentrations of 131I closer to observed concentrations, as compared to the predictions produced with other models. The inter-model comparison showed that variation of thyroid doses among all participating models (SENES model included) was a factor of 3 for the general population, but a factor of 10 for the two studied children. As opposed to other models, SENES model allows a complete analysis of uncertainties in every predicted quantity, including estimated thyroid doses and risk of thyroid cancer. The uncertainties in the risk-per-unit-dose and the dose-per-unit-intake coefficients are major contributors to the uncertainty in the estimated lifetime risk and thyroid dose, respectively. The largest contributors to the uncertainty in the estimated concentration in milk are the feed-to-milk transfer factor (F(m)), the dry deposition velocity (V(d)), and the mass interception factor (r/Y)dry for the elemental form of iodine (I2). Exposure to the 1963 PUREX/Hanford accident produced low doses and risks for people living at the studied locations. The upper 97.5th percentile of the excess lifetime risk of thyroid cancer for the most extreme situations is about 10(-4). Measurements in pasture grass and milk at all locations around Hanford indicate a very low transfer of 131I from pasture to cow's milk (e.g., a feed-to-milk transfer coefficient, F(m), for commercial cows of about 0.0022 d L(-1)). These values are towards the low end of F(m) values measured elsewhere and they are low compared to the F(m) values used in other dose reconstruction studies, including the Hanford Environmental Dose Reconstruction.

Absorption of strontium from the gastrointestinal tract into plasma in healthy human adults.

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.

Uncertainties in dose coefficients from ingestion of 131I, 137Cs, and 90Sr.

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.

A perspective on public concerns about exposure to fallout from the production and testing of nuclear weapons.

Exposures of the American public occurred nationwide from the testing of nuclear weapons in the United States, the Pacific, and the former Soviet Union. After decades of diminished public awareness on the subject of health risks resulting from exposure to fallout, the release of the National Cancer Institute's 1997 report on nationwide exposure to 131I from the Nevada Test Site (NTS) has led to renewed interest. Public requests for information are focused on individual and family health problems, the right to credible and full disclosure of information, and the need for medical care and assistance for exposure-related health problems. Public concerns have been raised regarding: (a) the lack of information on the potential health risks from exposure to all biologically significant radionuclides in fallout; (b) the lack of independent oversight that includes public participation; (c) governmental portrayal of exposures averaged over very large segments of the population without identification of much larger values for individuals or population subgroups likely to be at highest risk; and (d) a governmental response to known or suspected human exposures that consumes large periods of time and devotes considerable funding to various research-related activities before serious consideration is given to addressing health care responsibilities to exposed individuals. To some extent, these complaints and concerns are rooted in the legacy of government secrecy surrounding the development and testing of nuclear weapons, public distrust of government sources of information about radiation exposures and health risks, and the imposition of past exposures without informed consent. Members of the public participating in the oversight of dose reconstruction projects and epidemiologic studies are requesting information on the total impact from all relevant sources of exposure at each site that might contribute significantly to an individual's risk, including exposure to local releases and to NTS and global fallout. Information is being requested on individual doses and risks from these cumulative exposures, with estimates of uncertainty, including estimates of the absorbed organ dose (as opposed to the effective dose), the risk of disease incidence as opposed to the risk of a cancer fatality, and the chance that a person's diagnosed disease was caused by past exposure (i.e., the probability of causation). This paper attempts to address some of these concerns. We conclude by noting that many individuals exposed in childhood during the 1950's to 131I in fallout from nuclear weapons production and testing would qualify for compensation and medical care if the present rules for the adjudication of claims for atomic veterans and radiation workers at DOE sites were to be extended to the public.

Estimation of internal exposure to uranium with uncertainty from urinalysis data using the InDEP computer code.

The National Institute for Occupational Safety and Health (NIOSH) is currently studying mortality in a cohort of 6409 workers at a former uranium processing facility. As part of this study, over 220 000 urine samples were used to reconstruct organ doses due to internal exposure to uranium. Most of the available computational programs designed for analysis of bioassay data handle a single case at a time, and thus require a significant outlay of time and resources for the exposure assessment of a large cohort. NIOSH is currently supporting the development of a computer program, InDEP (Internal Dose Evaluation Program), to facilitate internal radiation exposure assessment as part of epidemiological studies of both uranium- and plutonium-exposed cohorts. A novel feature of InDEP is its batch processing capability which allows for the evaluation of multiple study subjects simultaneously. InDEP analyses bioassay data and derives intakes and organ doses with uncertainty estimates using least-squares regression techniques or using the Bayes' Theorem as applied to internal dosimetry (Bayesian method). This paper describes the application of the current version of InDEP to formulate assumptions about the characteristics of exposure at the study facility that were used in a detailed retrospective intake and organ dose assessment of the cohort.

Beyond dose assessment: using risk with full disclosure of uncertainty in public and scientific communication.

Evaluations of radiation exposures of workers and the public traditionally focus on assessments of radiation dose, especially annual dose, without explicitly evaluating the health risk associated with those exposures, principally the risk of radiation-induced cancer. When dose is the endpoint of an assessment, opportunities to communicate the significance of exposures are limited to comparisons with dose criteria in regulations, doses due to natural background or medical x-rays, and doses above which a statistically significant increase of disease has been observed in epidemiologic studies. Risk assessment generally addresses the chance (probability) that specific diseases might be induced by past, present, or future exposure. The risk of cancer per unit dose will vary depending on gender, age, exposure type (acute or chronic), and radiation type. It is not uncommon to find that two individuals with the same effective dose will have substantially different risks. Risk assessment has shown, for example, that: (a) medical exposures to computed tomography scans have become a leading source of future risk to the general population, and that the risk would be increased above recently published estimates if the incidence of skin cancer and the increased risk from exposure to x-rays compared with high-energy photons were taken into account; (b) indoor radon is a significant contributor to the baseline risk of lung cancer, particularly among people who have never smoked; and (c) members of the public who were exposed in childhood to I in fallout from atmospheric nuclear weapons tests and were diagnosed with thyroid cancer later in life would frequently meet criteria established for federal compensation of cancers experienced by energy workers and military participants at atmospheric weapons tests. Risk estimation also enables comparisons of impacts of exposures to radiation and chemical carcinogens and other hazards to life and health. Communication of risk with uncertainty is essential for reaching informed consent, whether communicating to a larger community debating the tradeoffs of risks and benefits of an action that involves radiation exposure or communicating at the level of a physician and patient.