Accounting for shared and unshared dosimetric uncertainties in the dose response for ultrasound-detected thyroid nodules after exposure to radioactive fallout

A Historical Survey of Key Epidemiological Studies of Ionizing Radiation Exposure

In this article we review the history of key epidemiological studies of populations exposed to ionizing radiation. We highlight historical and recent findings regarding radiation-associated risks for incidence and mortality of cancer and non-cancer outcomes with emphasis on study design and methods of exposure assessment and dose estimation along with brief consideration of sources of bias for a few of the more important studies. We examine the findings from the epidemiological studies of the Japanese atomic bomb survivors, persons exposed to radiation for diagnostic or therapeutic purposes, those exposed to environmental sources including Chornobyl and other reactor accidents, and occupationally exposed cohorts. We also summarize results of pooled studies. These summaries are necessarily brief, but we provide references to more detailed information. We discuss possible future directions of study, to include assessment of susceptible populations, and possible new populations, data sources, study designs and methods of analysis.

Recommendations on statistical approaches to account for dose uncertainties in radiation epidemiologic risk models

PURPOSE

Epidemiological studies of stochastic radiation health effects such as cancer, meant to estimate risks of the adverse effects as a function of radiation dose, depend largely on estimates of the radiation doses received by the exposed group under study. Those estimates are based on dosimetry that always has uncertainty, which often can be quite substantial. Studies that do not incorporate statistical methods to correct for dosimetric uncertainty may produce biased estimates of risk and incorrect confidence bounds on those estimates. This paper reviews commonly used statistical methods to correct radiation risk regressions for dosimetric uncertainty, with emphasis on some newer methods. We begin by describing the types of dose uncertainty that may occur, including those in which an uncertain value is shared by part or all of a cohort, and then demonstrate how these sources of uncertainty arise in radiation dosimetry. We briefly describe the effects of different types of dosimetric uncertainty on risk estimates, followed by a description of each method of adjusting for the uncertainty.

CONCLUSIONS

Each of the method has strengths and weaknesses, and some methods have limited applicability. We describe the types of uncertainty to which each method can be applied and its pros and cons. Finally, we provide summary recommendations and touch briefly on suggestions for further research.

A generalisation of the method of regression calibration and comparison with Bayesian and frequentist model averaging methods

For many cancer sites low-dose risks are not known and must be extrapolated from those observed in groups exposed at much higher levels of dose. Measurement error can substantially alter the dose-response shape and hence the extrapolated risk. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, there has been considerable attention paid to methods of dealing with shared errors, which are common in many datasets, and particularly important in occupational and environmental settings. In this paper we test Bayesian model averaging (BMA) and frequentist model averaging (FMA) methods, the first of these similar to the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, and both fairly recently proposed, against a very newly proposed modification of the regression calibration method, the extended regression calibration (ERC) method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. The quasi-2DMC with BMA method performs well when a linear model is assumed, but very poorly when a linear-quadratic model is assumed, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5% when the magnitude of shared Berkson error is large (50%). For the linear model the bias is generally under 10%. However, using a linear-quadratic model it produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. FMA performs as well as quasi-2DMC with BMA when a linear model is assumed, and generally much better with a linear-quadratic model, although the coverage probability for the quadratic coefficient is uniformly too high. However both linear and quadratic coefficients have pronounced upward bias, particularly when Berkson error is large. By comparison ERC yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the quasi-2DMC with BMA or FMA methods, particularly for the linear-quadratic model. The bias of the predicted relative risk at a variety of doses is generally smallest for ERC, and largest for the quasi-2DMC with BMA and FMA methods (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between ERC and the other two methods. In general ERC performs best in the scenarios presented, and should be the method of choice in situations where there may be substantial shared error, or suspected curvature in the dose response.

A generalisation of the method of regression calibration and comparison with Bayesian and frequentist model averaging methods

For many cancer sites low-dose risks are not known and must be extrapolated from those observed in groups exposed at much higher levels of dose. Measurement error can substantially alter the dose-response shape and hence the extrapolated risk. Recently, there has been considerable attention paid to methods of dealing with shared errors, which are particularly important in occupational and environmental settings. In this paper we test Bayesian model averaging (BMA) and frequentist model averaging (FMA) methods, the first of these similar to the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, and both fairly recently proposed, against a very newly proposed modification of the regression calibration method, the extended regression calibration (ERC) method. The quasi-2DMC+BMA method performs well when a linear model is assumed, but poorly when a linear-quadratic model is assumed. FMA performs as well as quasi-2DMC+BMA when a linear model is assumed, and generally much better with a linear-quadratic model, although the coverage probability for the quadratic coefficient is uniformly too high. ERC yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the quasi-2DMC+BMA or FMA methods, particularly for the linear-quadratic model. The bias of predicted relative risk at a variety of doses is generally smallest for ERC, and largest for quasi-2DMC+BMA and FMA, with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between ERC and the other two methods. In general ERC performs best in the scenarios presented, and should be the method of choice in situations where there may be substantial shared error, or suspected curvature in the dose response.

Comorbid Conditions in Persons Exposed to Ionizing Radiation and Veterans of the Soviet-Afghan War: A Cohort Study in Kazakhstan

OBJECTIVES

This study investigated the prevalence and characteristics of comorbid conditions in patients exposed to ionizing radiation and those who were involved in the Soviet-Afghan war.

METHODS

This study analyzed the frequency and spectrum of morbidity and comorbidity in patients over a long-term period (30-35 years) following exposure to ionizing radiation at the Semipalatinsk nuclear test site or the Chornobyl nuclear power plant, and among participants of the Soviet-Afghan war. A cohort study, both prospective and retrospective, was conducted on 675 patients who underwent comprehensive examinations.

RESULTS

Numerical data were analyzed using the Statistica 6 program. The results are presented as the mean±standard deviation, median, and interquartile range (25-75th percentiles). The statistical significance of between-group differences was assessed using the Student t-test and Pearson chi-square test. A p-value of less than 0.05 was considered statistically significant. We found a high prevalence of cardiovascular diseases, including hypertension (55.0%) and cardiac ischemia (32.9%); these rates exceeded the average for this age group in the general population.

CONCLUSIONS

The cumulative impact of causal occupational, environmental, and ultra-high stress factors in the combat zone in participants of the Soviet-Afghan war, along with common conventional factors, contributed to the formation of a specific comorbidity structure. This necessitates a rational approach to identifying early predictors of cardiovascular events and central nervous system disorders, as well as pathognomonic clinical symptoms in this patient cohort. It also underscores the importance of selecting suitable methods and strategies for implementing treatment and prevention measures.

Frequentist model averaging for analysis of dose-response in epidemiologic studies with complex exposure uncertainty

In epidemiologic studies, association estimates of an exposure with disease outcomes are often biased when the uncertainties of exposure are ignored. Consequently, corresponding confidence intervals (CIs) will not have correct coverage. This issue is particularly problematic when exposures must be reconstructed from physical measurements, for example, for environmental or occupational radiation doses that were received by a study population for which radiation doses cannot be measured directly. To incorporate complex uncertainties in reconstructed exposures, the two-dimensional Monte Carlo (2DMC) dose estimation method has been proposed and used in various dose reconstruction efforts. The 2DMC method generates multiple exposure realizations from dosimetry models that incorporate various sources of errors to reflect the uncertainty of the dose distribution as well as the uncertainties in individual doses in the exposed population. Traditional measurement-error model approaches, typically based on using mean doses in the dose-exposure analysis, do not fully account exposure uncertainties. A recently developed statistical approach that overcomes many of these limitations by analyzing multiple exposure realizations in relation to disease risk is Bayesian model averaging (BMA). The analytic advantage of the BMA is its ability to better accommodate complex exposure uncertainty in the risk estimation, but a practical. Drawback is its significant computational complexity. In this present paper, we propose a novel frequentist model averaging (FMA) approach which has all the analytical advantages of the BMA method but is much simpler to implement and computationally faster. We show in simulations that, like BMA, FMA yields 95% confidence intervals for association parameters that close to 95% coverage rate. In simulations, the FMA has shorter length of CIs than those of another frequentist approach, the corrected information matrix (CIM) method. We illustrate the similarities in performance of BMA and FMA from a study of exposures from radioactive fallout in Kazakhstan.

A generalisation of the method of regression calibration and comparison with the Bayesian 2-dimensional Monte Carlo method

For many cancer sites it is necessary to assess risks from low-dose exposures via extrapolation from groups exposed at moderate and high levels of dose. Measurement error can substantially alter the shape of this relationship and hence the derived population risk estimates. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, much attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. In this paper we test a Bayesian model averaging method, the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, that has been fairly recently proposed against a very newly proposed modification of the regression calibration method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. We also compared both methods against standard regression calibration and Monte Carlo maximum likelihood. The Bayesian 2DMC method performs poorly, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5%, particularly when the magnitudes of classical and Berkson error are both moderate to large (20%-50%). The method also produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. By comparison the extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the Bayesian 2DMC and all other methods. The bias of the predicted relative risk at a variety of doses is generally smallest for extended regression calibration, and largest for the Bayesian 2DMC method (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between the other two methods.

A generalisation of the method of regression calibration

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose-response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient [Formula: see text] are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient [Formula: see text] are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for [Formula: see text] that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient [Formula: see text] are substantially upwardly biased.

Dose estimates and their uncertainties for use in epidemiological studies of radiation-exposed populations in the Russian Southern Urals

Many residents of the Russian Southern Urals were exposed to radioactive environmental pollution created by the operations of the Mayak Production Association in the mid- 20th century. There were two major releases: the discharge of about 1x1017 Bq of liquid waste into the Techa River between 1949 and 1959; and the atmospheric release of 7.4 * 1016 Bq as a result an explosion in the radioactive waste-storage facility in 1957. The releases into the Techa River resulted in the exposure of more than 30,000 people who lived in riverside villages between 1950 and 1961. The 1957 accident contaminated a larger area with the highest exposure levels in an area that is called the East Urals Radioactive Trace (EURT). Current epidemiologic studies of the exposed populations are based on dose estimates obtained using a Monte-Carlo dosimetry system (TRDS-2016MC) that provides multiple realizations of the annual doses for each cohort member. These dose realizations provide a central estimate of the individual dose and information on the uncertainty of these dose estimates. In addition, the correlation of individual annual doses over realizations provides important information on shared uncertainties that can be used to assess the impact of shared dose uncertainties on risk estimate uncertainty.This paper considers dose uncertainties in the TRDS-2016MC. Individual doses from external and internal radiation sources were reconstructed for 48,036 people based on environmental contamination patterns, residential histories, individual 90Sr body-burden measurements and dietary intakes. Dietary intake of 90Sr resulted in doses accumulated in active bone marrow (or simply, marrow) that were an order of magnitude greater than those in soft tissues. About 84% of the marrow dose and 50% of the stomach dose was associated with internal exposures. The lognormal distribution is well-fitted to the individual dose realizations, which, therefore, could be expressed and easily operated in terms of geometric mean (GM) and geometric standard deviation (GSD). Cohort average GM for marrow and stomach cumulative doses are 0.21 and 0.03 Gy, respectively. Cohort average dose uncertainties in terms of GSD are as follows: for marrow it is 2.93 (90%CI: 2.02-4.34); for stomach and the other non-calcified tissues it is 2.32 (90% CI: 1.78-2.9).

Exposure to the Thyroid from Intake of Radioiodine Isotopes after the Chornobyl Accident. Report I: Revised Doses and Associated Uncertainties for the Ukrainian-American Cohort

Thyroid doses from intake of radioiodine isotopes (131I, 132Te+132I, and 133I) and associated uncertainties were revised for the 13,204 Ukrainian-American cohort members exposed in childhood and adolescence to fallout from the Chornobyl nuclear power plant accident. The main changes related to the revision of the 131I thyroid activity measured in cohort members, the use of thyroid-mass values specific to the Ukrainian population, and the revision of the 131I ground deposition densities in Ukraine. Uncertainties in doses were assessed considering shared and unshared errors in the parameters of the dosimetry model. Using a Monte-Carlo simulation procedure, 1,000 individual stochastic thyroid doses were calculated for each cohort member. The arithmetic mean of thyroid doses from intake of 131I, 132Te+132I, and 133I for the entire cohort was 0.60 Gy (median = 0.22 Gy). For 9,474 subjects (71.6% of the total), the thyroid doses were less than 0.5 Gy. Thyroid doses for 42 cohort members (0.3% of the total) exceeded 10 Gy while the highest dose was 35 Gy. Intake of 131I contributed around 95% to internal thyroid exposure from radioiodine isotopes. The geometric standard deviation of individual stochastic thyroid doses varied among cohort members from 1.4 to 4.3 with an arithmetic mean of 1.6 and a median of 1.4. It was shown that the contribution of shared errors to the dose uncertainty was small. The revised thyroid doses resulted, in average, in around 40% decrease for cohort members from Zhytomyr Oblast and an increase of around 24% and 35% for the cohort members from Kyiv and Chernihiv Oblast, respectively. Arithmetic mean of TD20 doses for the cohort was around 8% less than that estimated in TD10, 0.60 Gy vs. 0.65 Gy, respectively; however, global median of TD20 doses somewhat increased compared to TD10: 0.22 Gy vs. 0.19 Gy, respectively. The difference between TD10 and TD20 was mainly due to a revision of the individual 131I thyroid activity measured in the cohort members.

Inter-agency perspective: Translating advances in biomarker discovery and medical countermeasures development between terrestrial and space radiation environments

Over the past 20+ years, the U.S. Government has made significant strides in establishing research funding and initiating a portfolio consisting of subject matter experts on radiation-induced biological effects in normal tissues. Research supported by the National Cancer Institute (NCI) provided much of the early findings on identifying cellular pathways involved in radiation injuries, due to the need to push the boundaries to kill tumor cells while minimizing damage to intervening normal tissues. By protecting normal tissue surrounding the tumors, physicians can deliver a higher radiation dose to tumors and reduce adverse effects related to the treatment. Initially relying on this critical NCI research, the National Institute of Allergy and Infectious Diseases (NIAID), first tasked with developing radiation medical countermeasures in 2004, has provided bridge funding to move basic research toward advanced development and translation. The goal of the NIAID program is to fund approaches that can one day be employed to protect civilian populations during a radiological or nuclear incident. In addition, with the reality of long-term space flights and the possibility of radiation exposures to both acute, high-intensity, and chronic lower-dose levels, the National Aeronautics and Space Administration (NASA) has identified requirements to discover and develop radioprotectors and mitigators to protect their astronauts during space missions. In sustained partnership with sister agencies, these three organizations must continue to leverage funding and findings in their overlapping research areas to accelerate biomarker identification and product development to help safeguard these different and yet undeniably similar human populations - cancer patients, public citizens, and astronauts.

Impact of uncertainties in exposure assessment on thyroid cancer risk among cleanup workers in Ukraine exposed due to the Chornobyl accident

A large excess risk of thyroid cancer was observed among Belarusian/Russian/Baltic Chornobyl cleanup workers. A more recent study of Ukraine cleanup workers found more modest excess risks of thyroid cancer. Dose errors in this data are substantial, associated with model uncertainties and questionnaire response. Regression calibration is often used for dose-error adjustment, but may not adequately account for the full error distribution. We aimed to examine the impact of exposure-assessment uncertainties on thyroid cancer among Ukrainian cleanup workers using Monte Carlo maximum likelihood, and compare with results derived using regression calibration. Analyses assessed the sensitivity of results to various components of internal and external dose. Regression calibration yielded an excess odds ratio per Gy (EOR/Gy) of 0.437 (95% CI - 0.042, 1.577, p = 0.100), compared with the EOR/Gy using Monte Carlo maximum likelihood of 0.517 (95% CI - 0.039, 2.035, p = 0.093). Trend risk estimates for follicular morphology tumors exhibited much more extreme effects of full-likelihood adjustment, the EOR/Gy using regression calibration of 3.224 (95% CI - 0.082, 30.615, p = 0.068) becoming ~ 50% larger, 4.708 (95% CI - 0.075, 85.143, p = 0.066) when using Monte Carlo maximum likelihood. Results were sensitive to omission of external components of dose. In summary, use of Monte Carlo maximum likelihood adjustment for dose error led to increases in trend risks, particularly for follicular morphology thyroid cancers, where risks increased by ~ 50%, and were borderline significant. The unexpected finding for follicular tumors needs to be replicated in other exposed groups.

Assessment of internal exposure to 131I and short-lived radioiodine isotopes and associated uncertainties in the Ukrainian cohort of persons exposed in utero

This study revised the thyroid doses for 2582 Ukrainian in utero cohort members exposed to Chornobyl fallout (the Ukrainian in utero cohort) based on revision of: (i) 131I thyroid activity measured in the Ukrainian population, (ii) thyroid dosimetry system for entire Ukraine, and (iii) 131I ground deposition densities in Ukraine. Other major improvements included: (i) assessment of uncertainties in the thyroid doses considering shared and unshared error, and (ii) accounting for intake of short-lived radioisotopes of tellurium and iodine (132Te+132I and 133I). Intake of 131I was the major pathway for thyroid exposure, its median contribution to the thyroid dose was 97.4%. The mean prenatal and postnatal thyroid dose from 131I was 87 mGy (median = 17 mGy), higher than previous deterministic dose of 72 mGy (median = 12 mGy). For 39 individuals (1.5%) the dose exceeded 1.0 Gy, while the highest dose among the cohort members was 2.7 Gy. The geometric standard deviation (GSD) of 1000 individual stochastic doses varied from 1.9 to 5.2 with a mean of 3.1 and a median of 3.2. The lowest uncertainty (mean GSD = 2.3, median GSD = 2.2) was found for the subjects whose mothers were measured for 131I thyroid activity, while for individuals, whose mothers were not measured, the mean and median GSDs were 3.4. Uncertainties in thyroid doses were driven by shared errors associated with the parameters of the ecological model.

A Methodology for Estimating External Doses to Individuals and Populations Exposed to Radioactive Fallout from Nuclear Detonations

ABSTRACT

A methodology of assessment of the doses from external irradiation resulting from the ground deposition of radioactive debris (fallout) from a nuclear detonation is proposed in this paper. The input data used to apply this methodology for a particular location are the outdoor exposure rate at any time after deposition of fallout and the time-of-arrival of fallout, as indicated and discussed in a companion paper titled "A Method for Estimating the Deposition Density of Fallout on the Ground and on Vegetation from a Low-yield Low-altitude Nuclear Detonation." Example doses are estimated for several age categories and for all radiosensitive organs and tissues identified in the most recent ICRP publications. Doses are calculated for the first year after the detonation, when more than 90% of the external dose is delivered for populations close to the detonation site over a time period of 70 y, which is intended to represent the lifetime dose. Modeled doses in their simplest form assume no environmental remediation, though modifications can be introduced. Two types of dose assessment are considered: (1) initial, for a rapid but only approximate dose estimation soon after the nuclear detonation; and (2) improved, for a later, more accurate, dose assessment following the analysis of post-detonation measurements of radiation exposure and fallout deposition and the access of information on the lifestyle of the exposed population.

Dose Estimation for Exposure to Radioactive Fallout from Nuclear Detonations

ABSTRACT

In recent years, the prospects that a nuclear device might be detonated due to a regional or global political conflict, by violation of present nuclear weapons test ban agreements, or due to an act of terrorism, has increased. Thus, the need exists for a well conceptualized, well described, and internally consistent methodology for dose estimation that takes full advantage of the experience gained over the last 70 y in both measurement technology and dose assessment methodology. Here, the models, rationale, and data needed for a detailed state-of-the-art dose assessment for exposure to radioactive fallout from nuclear detonations discussed in five companion papers are summarized. These five papers present methods and data for estimating radionuclide deposition of fallout radionuclides, internal and external dose from the deposited fallout, and discussion of the uncertainties in the assessed doses. In addition, this paper includes a brief discussion of secondary issues related to assessments of radiation dose from fallout. The intention of this work is to provide a usable and consistent methodology for both prospective and retrospective assessments of exposure from radioactive fallout from a nuclear detonation.

A Method for Estimating the Deposition Density of Fallout on the Ground and on Vegetation from a Low-yield, Low-altitude Nuclear Detonation

ABSTRACT

This paper describes a relatively simple model developed from observations of local fallout from US and USSR nuclear tests that allows reasonable estimates to be made of the deposition density (activity per unit area) on both the ground and on vegetation for each radionuclide of interest produced in a nuclear fission detonation as a function of location and time after the explosion. In addition to accounting for decay rate and in-growth of radionuclides, the model accounts for the fractionation (modification of the relative activity of various fission and activation products in fallout relative to that produced in the explosion) that results from differences in the condensation temperatures of the various fission and activation products produced in the explosion. The proposed methodology can be used to estimate the deposition density of all fallout radionuclides produced in a low yield, low altitude fission detonation that contribute significantly to dose. The method requires only data from post-detonation measurements of exposure rate (or beta or a specific nuclide activity) and fallout time-of-arrival. These deposition-density estimates allow retrospective as well as rapid prospective estimates to be made of both external and internal radiation exposure to downwind populations living within a few hundred kilometers of ground zero, as described in the companion papers in this volume.

An examination of dose uncertainty and dose distribution effects on community noise attitudinal survey outcomes

Social survey data sets of large numbers of individual respondents' opinions are generally viewed as supporting reliable inferences of relationships between the prevalence of noise-induced annoyance and noise exposure levels. The current analyses identify conditions under which noise dose distributions and acoustic measurement uncertainty lead to appreciable mis-estimation of the slopes of empirical dose-response relationships with respect to those of true slopes in exposure ranges of interest. These findings were revealed by Monte Carlo methods for creating simulated data sets with varying exposure ranges and degrees of dose uncertainty. These simulated data sets support quantitative comparisons of dose-response relationships between empirical outcomes and known (assumed) relationships. The effect of noise dose uncertainty is appreciable for dose uncertainties with standard deviations greater than about 2 decibels. Limited dose ranges as well as haystack-shaped (non-uniform) dose distributions magnify the biasing effect of dose uncertainty on the slopes of observed relationships. Narrow exposure ranges can also create a false asymptotic behavior in the relationship. These phenomena are well documented in the non-acoustic literature.

Dose Estimation for the European Epidemiological Study on Pediatric Computed Tomography (EPI-CT)

Within the European Epidemiological Study to Quantify Risks for Paediatric Computerized Tomography (EPI-CT study), a cohort was assembled comprising nearly one million children, adolescents and young adults who received over 1.4 million computed tomography (CT) examinations before 22 years of age in nine European countries from the late 1970s to 2014. Here we describe the methods used for, and the results of, organ dose estimations from CT scanning for the EPI-CT cohort members. Data on CT machine settings were obtained from national surveys, questionnaire data, and the Digital Imaging and Communications in Medicine (DICOM) headers of 437,249 individual CT scans. Exposure characteristics were reconstructed for patients within specific age groups who received scans of the same body region, based on categories of machines with common technology used over the time period in each of the 276 participating hospitals. A carefully designed method for assessing uncertainty combined with the National Cancer Institute Dosimetry System for CT (NCICT, a CT organ dose calculator), was employed to estimate absorbed dose to individual organs for each CT scan received. The two-dimensional Monte Carlo sampling method, which maintains a separation of shared and unshared error, allowed us to characterize uncertainty both on individual doses as well as for the entire cohort dose distribution. Provided here are summaries of estimated doses from CT imaging per scan and per examination, as well as the overall distribution of estimated doses in the cohort. Doses are provided for five selected tissues (active bone marrow, brain, eye lens, thyroid and female breasts), by body region (i.e., head, chest, abdomen/pelvis), patient age, and time period (1977-1990, 1991-2000, 2001-2014). Relatively high doses were received by the brain from head CTs in the early 1990s, with individual mean doses (mean of 200 simulated values) of up to 66 mGy per scan. Optimization strategies implemented since the late 1990s have resulted in an overall decrease in doses over time, especially at young ages. In chest CTs, active bone marrow doses dropped from over 15 mGy prior to 1991 to approximately 5 mGy per scan after 2001. Our findings illustrate patterns of age-specific doses and their temporal changes, and provide suitable dose estimates for radiation-induced risk estimation in epidemiological studies.

Lung Cancer in the Mayak Workers Cohort: Risk Estimation and Uncertainty Analysis

The workers at the Mayak nuclear facility near Ozyorsk, Russia are a primary source of information about exposure to radiation at low-dose rates, since they were subject to protracted exposures to external gamma rays and to internal exposures from plutonium inhalation. Here we re-examine lung cancer mortality rates and assess the effects of external gamma and internal plutonium exposures using recently developed Monte Carlo dosimetry systems. Using individual lagged mean annual lung doses computed from the dose realizations, we fit excess relative risk (ERR) models to the lung cancer mortality data for the Mayak Workers Cohort using risk-modeling software. We then used the corrected-information matrix (CIM) approach to widen the confidence intervals of ERR by taking into account the uncertainty in doses represented by multiple realizations from the Monte Carlo dosimetry systems. Findings of this work revealed that there were 930 lung cancer deaths during follow-up. Plutonium lung doses (but not gamma doses) were generally higher in the new dosimetry systems than those used in the previous analysis. This led to a reduction in the risk per unit dose compared to prior estimates. The estimated ERR/Gy for external gamma-ray exposure was 0.19 (95% CI: 0.07 to 0.31) for both sexes combined, while the ERR/Gy for internal exposures based on mean plutonium doses were 3.5 (95% CI: 2.3 to 4.6) and 8.9 (95% CI: 3.4 to 14) for males and females at attained age 60. Accounting for uncertainty in dose had little effect on the confidence intervals for the ERR associated with gamma-ray exposure, but had a marked impact on confidence intervals, particularly the upper bounds, for the effect of plutonium exposure [adjusted 95% CIs: 1.5 to 8.9 for males and 2.7 to 28 for females]. In conclusion, lung cancer rates increased significantly with both external gamma-ray and internal plutonium exposures. Accounting for the effects of dose uncertainty markedly increased the width of the confidence intervals for the plutonium dose response but had little impact on the external gamma dose effect estimate. Adjusting risk estimate confidence intervals using CIM provides a solution to the important problem of dose uncertainty. This work demonstrates, for the first time, that it is possible and practical to use our recently developed CIM method to make such adjustments in a large cohort study.

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.

Thyroid Doses to French Polynesians Resulting from Atmospheric Nuclear Weapons Tests: Estimates Based on Radiation Measurements and Population Lifestyle Data

Thyroid doses were estimated for the subjects of a population-based case-control study of thyroid cancer in a population exposed to fallout after atmospheric nuclear weapons tests conducted in French Polynesia between 1966 and 1974. Thyroid doses due to (1) intake of I and of short-lived radioiodine isotopes (I, I, I) and Te, (2) external irradiation from gamma-emitting radionuclides deposited on the ground, and (3) ingestion of long-lived Cs with foodstuffs were reconstructed for each study subject. The dosimetry model that had been used in 2008 in Phase I of the study was substantially improved with (1) results of radiation monitoring of the environment and foodstuffs, which became available in 2013 for public access, and (2) historical data on population lifestyle related to the period of the tests, which were collected in 2016-2017 using focus-group discussions and key informant interviews. The mean thyroid dose among the study subjects was found to be around 5 mGy while the highest dose was estimated to be around 36 mGy. Doses from I intake ranged up to 27 mGy, while those from intake of short-lived iodine isotopes (I, I, I) and Te ranged up to 14 mGy. Thyroid doses from external exposure ranged up to 6 mGy, and those from internal exposure due to Cs ingestion did not exceed 1 mGy. Intake of I was found to be the main pathway for thyroid exposure accounting for 72% of the total dose. Results of this study are being used to evaluate the risk of thyroid cancer among the subjects of the epidemiologic study of thyroid cancer among French Polynesians.

Accounting for Unfissioned Plutonium from the Trinity Atomic Bomb Test

The Trinity test device contained about 6 kg of plutonium as its fission source, resulting in a fission yield of 21 kT. However, only about 15% of the Pu actually underwent fission. The remaining unfissioned plutonium eventually was vaporized in the fireball and after cooling, was deposited downwind from the test site along with the various fission and activation products produced in the explosion. Using data from radiochemical analyses of soil samples collected postshot (most many years later), supplemented by model estimates of plutonium deposition density estimated from reported exposure rates at 12 h postshot, we have estimated the total activity and geographical distribution of the deposition density of this unfissioned plutonium in New Mexico. A majority (about 80%) of the unfissioned plutonium was deposited within the state of New Mexico, most in a relatively small area about 30-100 km downwind (the Chupadera Mesa area). For most of the state, the deposition density was a small fraction of the subsequent deposition density of Pu from Nevada Test Site tests (1951-1958) and later from global fallout from the large US and Russian thermonuclear tests (1952-1962). The fraction of the total unfissioned Pu that was deposited in New Mexico from Trinity was greater than the fraction of fission products deposited. Due to plutonium being highly refractory, a greater fraction of the Pu was incorporated into large particles that fell out closer to the test site as opposed to more volatile fission products (such as Cs and I) that tend to deposit on the surface of smaller particles that travel farther before depositing. The plutonium deposited as a result of the Trinity test was unlikely to have resulted in significant health risks to the downwind population.

Estimated Radiation Doses Received by New Mexico Residents from the 1945 Trinity Nuclear Test

The National Cancer Institute study of projected health risks to New Mexico residents from the 1945 Trinity nuclear test provides best estimates of organ radiation absorbed doses received by representative persons according to ethnicity, age, and county. Doses to five organs/tissues at significant risk from exposure to radioactive fallout (i.e., active bone marrow, thyroid gland, lungs, stomach, and colon) from the 63 most important radionuclides in fresh fallout from external and internal irradiation were estimated. The organ doses were estimated for four resident ethnic groups in New Mexico (Whites, Hispanics, Native Americans, and African Americans) in seven age groups using: (1) assessment models described in a companion paper, (2) data on the spatial distribution and magnitude of radioactive fallout derived from historical documents, and (3) data collected on diets and lifestyles in 1945 from interviews and focus groups conducted in 2015-2017 (described in a companion paper). The organ doses were found to vary widely across the state with the highest doses directly to the northeast of the detonation site and at locations close to the center of the Trinity fallout plume. Spatial heterogeneity of fallout deposition was the largest cause of variation of doses across the state with lesser differences due to age and ethnicity, the latter because of differences in diets and lifestyles. The exposure pathways considered included both external irradiation from deposited fallout and internal irradiation via inhalation of airborne radionuclides in the debris cloud as well as resuspended ground activity and ingestion of contaminated drinking water (derived both from rivers and rainwater cisterns) and foodstuffs including milk products, beef, mutton, and pork, human-consumed plant products including leafy vegetables, fruit vegetables, fruits, and berries. Tables of best estimates of county population-weighted average organ doses by ethnicity and age are presented. A discussion of our estimates of uncertainty is also provided to illustrate a lower and upper credible range on our best estimates of doses. Our findings indicate that only small geographic areas immediately downwind to the northeast received exposures of any significance as judged by their magnitude relative to natural radiation. The findings presented are the most comprehensive and well-described estimates of doses received by populations of New Mexico from the Trinity nuclear test.

Contemporary Thyroid Nodule Evaluation and Management

CONTEXT

Approximately 60% of adults harbor 1 or more thyroid nodules. The possibility of cancer is the overriding concern, but only about 5% prove to be malignant. The widespread use of diagnostic imaging and improved access to health care favor the discovery of small, subclinical nodules and small papillary cancers. Overdiagnosis and overtreatment is associated with potentially excessive costs and nonnegligible morbidity for patients.

EVIDENCE ACQUISITION

We conducted a PubMed search for the recent English-language articles dealing with thyroid nodule management.

EVIDENCE SYNTHESIS

The initial assessment includes an evaluation of clinical risk factors and sonographic examination of the neck. Sonographic risk-stratification systems (e.g., Thyroid Imaging Reporting and Data Systems) can be used to estimate the risk of malignancy and the need for biopsy based on nodule features and size. When cytology findings are indeterminate, molecular analysis of the aspirate may obviate the need for diagnostic surgery. Many nodules will not require biopsy. These nodules and those that are cytologically benign can be managed with long-term follow-up alone. If malignancy is suspected, options include surgery (increasingly less extensive), active surveillance or, in selected cases, minimally invasive techniques.

CONCLUSION

Thyroid nodule evaluation is no longer a 1-size-fits-all proposition. For most nodules, the likelihood of malignancy can be confidently estimated without resorting to cytology or molecular testing, and low-frequency surveillance is sufficient for most patients. When there are multiple options for diagnosis and/or treatment, they should be discussed with patients as frankly as possible to identify an approach that best meets their needs.

Analysis of Cataract in Relationship to Occupational Radiation Dose Accounting for Dosimetric Uncertainties in a Cohort of U.S. Radiologic Technologists

Cataract is one of the major morbidities in the U.S. population and it has long been appreciated that high and acutely delivered radiation doses of 1 Gy or more can induce cataract. Some more recent studies, in particular those of the U.S. Radiologic Technologists, have suggested that cataract may be induced by much lower, chronically delivered doses of ionizing radiation. It is well recognized that dosimetric measurement error can substantially alter the shape of the radiation dose-response relationship and thus, the derived study risk estimates, and can also inflate the variance of the estimates. In the current study, we evaluate the impact of uncertainties in eye-lens absorbed doses on the estimated risk of cataract in the U.S. Radiologic Technologists' Monte Carlo Dosimetry System, using both absolute and relative risk models. Among 11,345 cases we show that the inflation in the standard error for the excess relative risk (ERR) is generally modest, at most approximately 20% of the unadjusted standard error, depending on the model used for the baseline risk. The largest adjustment results from use of relative risk models, so that the ERR/Gy and its 95% confidence intervals change from 1.085 (0.645, 1.525) to 1.085 (0.558, 1.612) after adjustment. However, the inflation in the standard error of the excess absolute risk (EAR) coefficient is generally minimal, at most approximately 0.04% of the standard error.

Uncertainties in Radiation Doses for a Case-control Study of Thyroid Cancer among Persons Exposed in Childhood to 131 I from Chernobyl Fallout

Uncertainties in thyroid doses due to I intake were evaluated for 2,239 subjects in a case-control study of thyroid cancer following exposure to Chernobyl fallout during childhood and adolescence carried out in contaminated regions of Belarus and Russia. Using new methodological developments that became available recently, a Monte Carlo simulation procedure was applied to calculate 1,000 alternative vectors of thyroid doses due to I intake for the study population of 2,239 subjects accounting for sources of shared and unshared errors. An overall arithmetic mean of the stochastic thyroid doses in the study was estimated to be 0.43 Gy and median dose of 0.16 Gy. The arithmetic mean and median of deterministic doses estimated previously for 1,615 of 2,239 study subjects were 0.48 Gy and 0.20 Gy, respectively. The geometric standard deviation of individual stochastic doses varied from 1.59 to 3.61 with an arithmetic mean of 1.94 and a geometric mean of 1.89 over all subjects of the study. These multiple sets of thyroid doses were used to update radiation-related thyroid cancer risks in the study population exposed to I after the Chernobyl accident.

Issues in Interpreting Epidemiologic Studies of Populations Exposed to Low-Dose, High-Energy Photon Radiation

This article addresses issues relevant to interpreting findings from 26 epidemiologic studies of persons exposed to low-dose radiation. We review the extensive data from both epidemiologic studies of persons exposed at moderate or high doses and from radiobiology that together have firmly established radiation as carcinogenic. We then discuss the use of the linear relative risk model that has been used to describe data from both low- and moderate- or high-dose studies. We consider the effects of dose measurement errors; these can reduce statistical power and lead to underestimation of risks but are very unlikely to bring about a spurious dose response. We estimate statistical power for the low-dose studies under the assumption that true risks of radiation-related cancers are those expected from studies of Japanese atomic bomb survivors. Finally, we discuss the interpretation of confidence intervals and statistical tests and the applicability of the Bradford Hill principles for a causal relationship.

Fallout from Nuclear Weapons Tests: Environmental, Health, Political, and Sociological Considerations

The process of nuclear fission, which was discovered in 1938, opened the door to the production of nuclear weapons, which were used in 1945 by the United States against Japan in World War II, and to the detonation of >500 nuclear weapons tests in the atmosphere by the United States, the former Soviet Union, the United Kingdom, China, and France from 1946-1980. Hundreds of radionuclides, most of them short-lived, were produced in the atmospheric tests. The radioactive clouds produced by the explosions were usually partitioned between the troposphere and the stratosphere: the activity that remained in the troposphere resulted in local and regional fallout, consisting mainly of short-lived radionuclides and in relatively high doses for the populations residing in the vicinity of the test site, whereas the activity that reached the stratosphere returned to the ground with a half-life of ~1 y and was composed of long-lived radionuclides that contaminated all uncovered materials on Earth to a small extent and led to low-level irradiation of the world population for decades or more. The health effects resulting from exposure to radioactive fallout constitute, in most cases, small excesses over baseline rates for thyroid cancer and leukemia. An extra 49,000 cases of thyroid cancer would be expected to occur among the US population from exposure to radioactive fallout from the atmospheric nuclear weapons tests that were conducted at the Nevada Test Site in the 1950s. In addition, there could be as many as 11,000 deaths from non-thyroid cancers related to fallout from all atmospheric tests that were conducted at all sites in the world, with leukemia making up 10% of the total. Public concern arose in part from the secrecy that surrounded the nuclear testing programs and, for a long time, the poor communication regarding the consequences of the tests, both in terms of radiation doses and of health effects. Sociological and political pressures contributed to the establishment of programs of compensation for radiation exposures and evidence of radiation-induced diseases in countries that incurred significant fallout from nuclear weapons testing.

Dose coefficients of percentile-specific computational phantoms for photon external exposures

The use of dose coefficients (DCs) based on the reference phantoms recommended by the International Commission on Radiological Protection (ICRP) with a fixed body size may produce errors to the estimated organ/tissue doses to be used, for example, for epidemiologic studies depending on the body size of cohort members. A set of percentile-specific computational phantoms that represent 10th, 50th, and 90th percentile standing heights and body masses in adult male and female Caucasian populations were recently developed by modifying the mesh-type ICRP reference computational phantoms (MRCPs). In the present study, these percentile-specific phantoms were used to calculate a comprehensive dataset of body-size-dependent DCs for photon external exposures by performing Monte Carlo dose calculations with the Geant4 code. The dataset includes the DCs of absorbed doses for 29 individual organs/tissues from 0.01 to 104 MeV photon energy, in the antero-posterior, postero-anterior, right lateral, left lateral, rotational, and isotropic geometries. The body-size-dependent DCs were compared with the DCs of the MRCPs in the reference body size, showing that the DCs of the MRCPs are generally similar to those of the 50th percentile standing height and body mass phantoms over the entire photon energy region except for low energies (≤ 0.03 MeV); the differences are mostly less than 10%. In contrast, there are significant differences in the DCs between the MRCPs and the 10th and 90th percentile standing height and body mass phantoms (i.e., H10M10 and H90M90). At energies of less than about 10 MeV, the MRCPs tended to under- and over-estimate the organ/tissue doses of the H10M10 and H90M90 phantoms, respectively. This tendency was revised at higher energies. The DCs of the percentile-specific phantoms were also compared with the previously published values of another phantom sets with similar body sizes, showing significant differences particularly at energies below about 0.1 MeV, which is mainly due to the different locations and depths of organs/tissues between the different phantom libraries. The DCs established in the present study should be useful to improve the dosimetric accuracy in the reconstructions of organ/tissue doses for individuals in risk assessment for epidemiologic investigations taking body sizes into account.

Radio-biologically motivated modeling of radiation risks of mortality from ischemic heart diseases in the Canadian fluoroscopy cohort study

Recent analyses of the Canadian fluoroscopy cohort study reported significantly increased radiation risks of mortality from ischemic heart diseases (IHD) with a linear dose-response adjusted for dose fractionation. This cohort includes 63,707 tuberculosis patients from Canada who were exposed to low-to-moderate dose fractionated X-rays in 1930s-1950s and were followed-up for death from non-cancer causes during 1950-1987. In the current analysis, we scrutinized the assumption of linearity by analyzing a series of radio-biologically motivated nonlinear dose-response models to get a better understanding of the impact of radiation damage on IHD. The models were weighted according to their quality of fit and were then mathematically superposed applying the multi-model inference (MMI) technique. Our results indicated an essentially linear dose-response relationship for IHD mortality at low and medium doses and a supra-linear relationship at higher doses (> 1.5 Gy). At 5 Gy, the estimated radiation risks were fivefold higher compared to the linear no-threshold (LNT) model. This is the largest study of patients exposed to fractionated low-to-moderate doses of radiation. Our analyses confirm previously reported significantly increased radiation risks of IHD from doses similar to those from diagnostic radiation procedures.

Thyroid Cancer after Exposure to Radioiodine in Childhood and Adolescence: 131I-Related Risk and the Role of Selected Host and Environmental Factors

In this study, we expanded on a previously published population-based case-control study on subjects exposed to iodine-131 (131I) from Chernobyl fallout at age ≤18 years using improved individual 131I absorbed thyroid doses. We further studied the impact of iodine deficiency and other selected host risk factors on 131I-related thyroid cancer risk after childhood exposure. We included 298 thyroid cancer cases and 1934 matched controls from the most contaminated regions of Belarus and the Russian Federation. We performed statistical analysis using conditional logistic regression models. We found a statistically significant linear quadratic dose-effect association between thyroid cancer and 131I thyroid dose in the range up to 5 grays (Gy). Self-reported personal history of benign nodules, any thyroid disease except thyroid cancer, family history of thyroid cancer, increased body mass index, and deficient stable iodine status at the time of the accident were statistically significant risk factors (p < 0.05 for each factor) for thyroid cancer after adjustment for thyroid 131I dose effect. Subjects who received stable iodine supplementation in the years after the accident had a significantly lower 131I-related risk of thyroid cancer. Our findings are important for thyroid cancer prevention, and for further improvement of medical surveillance in the affected populations.

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.

The State Scientific Automated Medical Registry, Kazakhstan: an important resource for low-dose radiation health research

Direct quantitative assessment of health risks following exposure to ionizing radiation is based on findings from epidemiological studies. Populations affected by nuclear bomb testing are among those that allow such assessment. The population living around the former Soviet Union's Semipalatinsk nuclear test site is one of the largest human cohorts exposed to radiation from nuclear weapons tests. Following research that started in the 1960s, a registry that contains information on more than 300,000 individuals residing in the areas neighboring to the test site was established. Four nuclear weapons tests, conducted from 1949 to 1956, resulted in non-negligible radiation exposures to the public, corresponding up to approximately 300 mGy external dose. The registry contains relevant information about those who lived at the time of the testing as well as about their offspring, including biological material. An international group of scientists worked together within the research project SEMI-NUC funded by the European Union, and concluded that the registry provides a novel, mostly unexplored, and valuable resource for the assessment of the population risks associated with environmental radiation exposure. Suggestions for future studies and pathways on how to use the best dose assessment strategies have also been described in the project. Moreover, the registry could be used for research on other relevant public health topics.

Recent Epidemiologic Studies and the Linear No-Threshold Model For Radiation Protection-Considerations Regarding NCRP Commentary 27

National Council on Radiation Protection and Measurements Commentary 27 examines recent epidemiologic data primarily from low-dose or low dose-rate studies of low linear-energy-transfer radiation and cancer to assess whether they support the linear no-threshold model as used in radiation protection. The commentary provides a critical review of low-dose or low dose-rate studies, most published within the last 10 y, that are applicable to current occupational, environmental, and medical radiation exposures. The strengths and weaknesses of the epidemiologic methods, dosimetry assessments, and statistical modeling of 29 epidemiologic studies of total solid cancer, leukemia, breast cancer, and thyroid cancer, as well as heritable effects and a few nonmalignant conditions, were evaluated. An appraisal of the degree to which the low-dose or low dose-rate studies supported a linear no-threshold model for radiation protection or on the contrary, demonstrated sufficient evidence that the linear no-threshold model is inappropriate for the purposes of radiation protection was also included. The review found that many, though not all, studies of solid cancer supported the continued use of the linear no-threshold model in radiation protection. Evaluations of the principal studies of leukemia and low-dose or low dose-rate radiation exposure also lent support for the linear no-threshold model as used in protection. Ischemic heart disease, a major type of cardiovascular disease, was examined briefly, but the results of recent studies were considered too weak or inconsistent to allow firm conclusions regarding support of the linear no-threshold model. It is acknowledged that the possible risks from very low doses of low linear-energy-transfer radiation are small and uncertain and that it may never be possible to prove or disprove the validity of the linear no-threshold assumption by epidemiologic means. Nonetheless, the preponderance of recent epidemiologic data on solid cancer is supportive of the continued use of the linear no-threshold model for the purposes of radiation protection. This conclusion is in accord with judgments by other national and international scientific committees, based on somewhat older data. Currently, no alternative dose-response relationship appears more pragmatic or prudent for radiation protection purposes than the linear no-threshold model.

Thyroid Cancer and Benign Nodules After Exposure In Utero to Fallout From Chernobyl

Background

Children and adolescents exposed to radioactive iodine-131 (I-131) in fallout from the 1986 Chernobyl nuclear accident appear to be at increased risk of thyroid cancer and benign thyroid nodules. The prenatal period is also considered radiosensitive, and the fetal thyroid can absorb I-131 from the maternal circulation.

Objectives

We aimed to estimate the risk of malignant and benign thyroid nodules in individuals exposed prenatally.

Methods

We studied a cohort of 2582 subjects in Ukraine with estimates of I-131 prenatal thyroid dose (mean = 72.6 mGy), who underwent two standardized thyroid screening examinations. To evaluate the dose-response relationship, we estimated the excess OR (EOR) using logistic regression.

Results

Based on a combined total of eight cases diagnosed at screenings from 2003 to 2006 and 2012 to 2015, we found a markedly elevated, albeit not statistically significant, dose-related risk of thyroid cancer (EOR/Gy = 3.91, 95% CI: -1.49, 65.66). At cycle 2 (n = 1,786), there was a strong and significant association between I-131 thyroid dose and screen-detected large benign nodules (≥10 mm) (EOR/Gy = 4.19, 95% CI: 0.68, 11.62; P = 0.009), but no significant increase in risk for small nodules (<10 mm) (EOR/Gy = 0.34, 95% CI: -0.67, 2.24; P = 0.604).

Conclusions

The dose effect by nodule size, with I-131 risk for large but not small nodules, is similar to that among exposed children and adolescents in Belarus. Based on a small number of cases, there is also a suggestive effect of I-131 dose on thyroid cancer risk.

Increased prevalence of essential hypertension in areas previously exposed to fallout due to nuclear weapons testing at the Semipalatinsk Test Site, Kazakhstan

This study examines the association between environmental radiation exposure and essential hypertension in a series of investigated geographical districts adjacent to the Semipalatinsk nuclear test site in Kazakhstan. The sample consists of 2000 volunteers participants in screening examinations in three administrative districts close to the nuclear test site, which was carried out as part of the Government Programs on Environmental Health Hazard. The cross-sectional study compares prevalence ratios in a population sample with long-term exposure in the low and intermediate dose range. Age-adjusted odds ratios for hypertension were found significantly increased with higher exposure groups. After accounting for main cardiovascular risk factors into the model and stratifying by gender, the prevalence odds ratios for radiation remained significantly increased, with a significant dose-response effect observed for some but not all subgroups. The results support existing evidence of cardiovascular health effects of radiation exposure and of persisting environmental health issues that require attention in both epidemiological surveys and healthcare provision.

Risk of Thyroid Nodules in Residents of Belarus Exposed to Chernobyl Fallout as Children and Adolescents

CONTEXT

Although radiation exposure is an important predictor of thyroid cancer on diagnosis of a thyroid nodule, the relationship between childhood radiation exposure and thyroid nodules has not been comprehensively evaluated.

OBJECTIVE

To examine the association between internal I-131 thyroid dose and thyroid nodules in young adults exposed during childhood.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, we screened residents of Belarus aged ≤18 years at the time of the Chernobyl nuclear accident for thyroid disease (median age, 21 years) with thyroid palpation, ultrasonography, blood/urine analysis, and medical follow-up when appropriate. Eligible participants (N = 11,421) had intact thyroid glands and doses based on direct individual thyroid activity measurements.

MAIN OUTCOME MEASURES

Excess odds ratios per Gray (EOR/Gy, scaled at age 5 years at exposure) for any thyroid nodule and for nodules grouped by cytology/histology, diameter size, and singularity.

RESULTS

Risk of any thyroid nodule increased significantly with I-131 dose and, for a given dose, with younger age at exposure. The EOR/Gy (95% confidence intervals) for neoplastic nodules (3.82; 0.87 to 15.52) was significantly higher than for nonneoplastic nodules (0.32; <0.03 to 0.70) and did not vary by size; whereas the EOR/Gy for nonneoplastic nodules did vary by size (P = 0.02) and was 1.55 (0.36 to 5.46) for nodules ≥10 mm and 0.02 (<-0.02 to 0.70) for nodules <10 mm. EORs/Gy for single and multiple nodules were comparable.

CONCLUSIONS

Childhood exposure to internal I-131 is associated with increased risk of neoplastic thyroid nodules of any size and nonneoplastic nodules ≥10 mm.

Correction of confidence intervals in excess relative risk models using Monte Carlo dosimetry systems with shared errors

In epidemiological studies, exposures of interest are often measured with uncertainties, which may be independent or correlated. Independent errors can often be characterized relatively easily while correlated measurement errors have shared and hierarchical components that complicate the description of their structure. For some important studies, Monte Carlo dosimetry systems that provide multiple realizations of exposure estimates have been used to represent such complex error structures. While the effects of independent measurement errors on parameter estimation and methods to correct these effects have been studied comprehensively in the epidemiological literature, the literature on the effects of correlated errors, and associated correction methods is much more sparse. In this paper, we implement a novel method that calculates corrected confidence intervals based on the approximate asymptotic distribution of parameter estimates in linear excess relative risk (ERR) models. These models are widely used in survival analysis, particularly in radiation epidemiology. Specifically, for the dose effect estimate of interest (increase in relative risk per unit dose), a mixture distribution consisting of a normal and a lognormal component is applied. This choice of asymptotic approximation guarantees that corrected confidence intervals will always be bounded, a result which does not hold under a normal approximation. A simulation study was conducted to evaluate the proposed method in survival analysis using a realistic ERR model. We used both simulated Monte Carlo dosimetry systems (MCDS) and actual dose histories from the Mayak Worker Dosimetry System 2013, a MCDS for plutonium exposures in the Mayak Worker Cohort. Results show our proposed methods provide much improved coverage probabilities for the dose effect parameter, and noticeable improvements for other model parameters.

A geographical study of thyroid cancer incidence in north-west England following the Windscale nuclear reactor fire of 1957

The Windscale nuclear reactor fire at Sellafield, United Kingdom, in October 1957 led to an uncontrolled release of iodine-131 (radioactive half-life, 8 d) into the atmosphere. Contamination from the accident was most pronounced in the counties of Cumbria and Lancashire, north-west England. Radioiodine concentrates in the thyroid gland producing an excess risk of thyroid cancer, notably among those exposed as children, which persists into later life. For an initial investigation of thyroid cancer incidence in north-west England, data were obtained on cases of thyroid cancer among people born during 1929-1973 and diagnosed during 1974-2012 while resident in England, together with corresponding populations. Incidence rate ratios (IRRs), with Poisson 95% confidence intervals (CIs), compared thyroid cancer incidence rates in Cumbria and in Lancashire with those in the rest of England. For those aged  <20 years in 1958, a statistically significantly increased IRR was found for those diagnosed during 1974-2012 while living in Cumbria (IRR  =  1.29; 95% CI 1.09-1.52), but the equivalent IRR for Lancashire was marginally non-significantly decreased (IRR  =  0.91; 95% CI 0.80-1.04). This pattern of IRRs was also apparent for earlier births, and the significantly increased IRR in Cumbria extended to individuals born in 1959-1963, who would not have been exposed to iodine-131 from the Windscale accident. Moreover, significant overdispersion was present in the temporal distributions of the IRRs, so that Poisson CIs substantially underestimate statistical uncertainties. Consequently, although further investigations are required to properly understand the unusual patterns of thyroid cancer IRRs in Cumbria and Lancashire, the results of this preliminary study are not consistent with an effect of exposure to iodine-131 from the Windscale accident.

Doses for post-Chernobyl epidemiological studies: are they reliable?

On 26 April 2016, thirty years will have elapsed since the occurrence of the Chernobyl accident, which has so far been the most severe in the history of the nuclear reactor industry. Numerous epidemiological studies were conducted to evaluate the possible health consequences of the accident. Since the credibility of the association between the radiation exposure and health outcome is highly dependent on the adequacy of the dosimetric quantities used in these studies, this paper makes an effort to overview the methods used to estimate individual doses and the associated uncertainties in the main analytical epidemiological studies (i.e. cohort or case-control) related to the Chernobyl accident. Based on the thorough analysis and comparison with other radiation studies, the authors conclude that individual doses for the Chernobyl analytical epidemiological studies have been calculated with a relatively high degree of reliability and well-characterized uncertainties, and that they compare favorably with many other non-Chernobyl studies. The major strengths of the Chernobyl studies are: (1) they are grounded on a large number of measurements, either performed on humans or made in the environment; and (2) extensive effort has been invested to evaluate the uncertainties associated with the dose estimates. Nevertheless, gaps in the methodology are identified and suggestions for the possible improvement of the current dose estimates are made.

Concerted Uranium Research in Europe (CURE): toward a collaborative project integrating dosimetry, epidemiology and radiobiology to study the effects of occupational uranium exposure

The potential health impacts of chronic exposures to uranium, as they occur in occupational settings, are not well characterized. Most epidemiological studies have been limited by small sample sizes, and a lack of harmonization of methods used to quantify radiation doses resulting from uranium exposure. Experimental studies have shown that uranium has biological effects, but their implications for human health are not clear. New studies that would combine the strengths of large, well-designed epidemiological datasets with those of state-of-the-art biological methods would help improve the characterization of the biological and health effects of occupational uranium exposure. The aim of the European Commission concerted action CURE (Concerted Uranium Research in Europe) was to develop protocols for such a future collaborative research project, in which dosimetry, epidemiology and biology would be integrated to better characterize the effects of occupational uranium exposure. These protocols were developed from existing European cohorts of workers exposed to uranium together with expertise in epidemiology, biology and dosimetry of CURE partner institutions. The preparatory work of CURE should allow a large scale collaborative project to be launched, in order to better characterize the effects of uranium exposure and more generally of alpha particles and low doses of ionizing radiation.

Impact of Uncertainties in Exposure Assessment on Thyroid Cancer Risk among Persons in Belarus Exposed as Children or Adolescents Due to the Chernobyl Accident

Background

The excess incidence of thyroid cancer in Ukraine and Belarus observed a few years after the Chernobyl accident is considered to be largely the result of ¹³¹I released from the reactor. Although the Belarus thyroid cancer prevalence data has been previously analyzed, no account was taken of dose measurement error.

Methods

We examined dose-response patterns in a thyroid screening prevalence cohort of 11,732 persons aged under 18 at the time of the accident, diagnosed during 1996–2004, who had direct thyroid ¹³¹I activity measurement, and were resident in the most radio-actively contaminated regions of Belarus. Three methods of dose-error correction (regression calibration, Monte Carlo maximum likelihood, Bayesian Markov Chain Monte Carlo) were applied.

Results

There was a statistically significant (p<0.001) increasing dose-response for prevalent thyroid cancer, irrespective of regression-adjustment method used. Without adjustment for dose errors the excess odds ratio was 1.51 Gy⁻ (95% CI 0.53, 3.86), which was reduced by 13% when regression-calibration adjustment was used, 1.31 Gy⁻ (95% CI 0.47, 3.31). A Monte Carlo maximum likelihood method yielded an excess odds ratio of 1.48 Gy⁻ (95% CI 0.53, 3.87), about 2% lower than the unadjusted analysis. The Bayesian method yielded a maximum posterior excess odds ratio of 1.16 Gy⁻ (95% BCI 0.20, 4.32), 23% lower than the unadjusted analysis. There were borderline significant (p = 0.053–0.078) indications of downward curvature in the dose response, depending on the adjustment methods used. There were also borderline significant (p = 0.102) modifying effects of gender on the radiation dose trend, but no significant modifying effects of age at time of accident, or age at screening as modifiers of dose response (p>0.2).

Conclusions

In summary, the relatively small contribution of unshared classical dose error in the current study results in comparatively modest effects on the regression parameters.

The two-dimensional Monte Carlo: a new methodologic paradigm for dose reconstruction for epidemiological studies

Retrospective dose estimation, particularly dose reconstruction that supports epidemiological investigations of health risk, relies on various strategies that include models of physical processes and exposure conditions with detail ranging from simple to complex. Quantification of dose uncertainty is an essential component of assessments for health risk studies since, as is well understood, it is impossible to retrospectively determine the true dose for each person. To address uncertainty in dose estimation, numerical simulation tools have become commonplace and there is now an increased understanding about the needs and what is required for models used to estimate cohort doses (in the absence of direct measurement) to evaluate dose response. It now appears that for dose-response algorithms to derive the best, unbiased estimate of health risk, we need to understand the type, magnitude and interrelationships of the uncertainties of model assumptions, parameters and input data used in the associated dose estimation models. Heretofore, uncertainty analysis of dose estimates did not always properly distinguish between categories of errors, e.g., uncertainty that is specific to each subject (i.e., unshared error), and uncertainty of doses from a lack of understanding and knowledge about parameter values that are shared to varying degrees by numbers of subsets of the cohort. While mathematical propagation of errors by Monte Carlo simulation methods has been used for years to estimate the uncertainty of an individual subject's dose, it was almost always conducted without consideration of dependencies between subjects. In retrospect, these types of simple analyses are not suitable for studies with complex dose models, particularly when important input data are missing or otherwise not available. The dose estimation strategy presented here is a simulation method that corrects the previous deficiencies of analytical or simple Monte Carlo error propagation methods and is termed, due to its capability to maintain separation between shared and unshared errors, the two-dimensional Monte Carlo (2DMC) procedure. Simply put, the 2DMC method simulates alternative, possibly true, sets (or vectors) of doses for an entire cohort rather than a single set that emerges when each individual's dose is estimated independently from other subjects. Moreover, estimated doses within each simulated vector maintain proper inter-relationships such that the estimated doses for members of a cohort subgroup that share common lifestyle attributes and sources of uncertainty are properly correlated. The 2DMC procedure simulates inter-individual variability of possibly true doses within each dose vector and captures the influence of uncertainty in the values of dosimetric parameters across multiple realizations of possibly true vectors of cohort doses. The primary characteristic of the 2DMC approach, as well as its strength, are defined by the proper separation between uncertainties shared by members of the entire cohort or members of defined cohort subsets, and uncertainties that are individual-specific and therefore unshared.