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

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.

Single-cell and transcriptomic analyses reveal the influence of diabetes on ovarian cancer

BACKGROUND

There has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.

METHODS

Multiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.

RESULTS

The immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.

CONCLUSION

This study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.

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.

New insights into health risk assessment on soil trace metal(loid)s: Model improvement and parameter optimization

Trace metal(loid)s (TMs) in soils may pose potential health risks to humans. Due to model uncertainty and variability of exposure parameters, the traditional health risk assessment (HRA) model may lead to inaccurate risk assessment results. Therefore, this study developed an improved HRA model to assess health risks by combining two-dimensional Monte Carlo simulation (2-D MCS) with a Logistic Chaotic sequence based on published data from 2000 to 2021. The results showed children and adult females were the high-risks populations for Non-carcinogenic risk and Carcinogenic risk, respectively. Meanwhile, children's Ingestion rate (IngR < 160.233 mg/day) and adult females' Skin adherence factor (0.026 mg/(cm2•d) < AF < 0.263 mg/(cm2•d)) were used as recommended exposure to make the health risk within acceptable range. Additionally, when performing risk assessment using actual exposure parameters, priority control TMs were identified, with As being the priority control TM for Southwest China and Inner Mongolia, whereas Cr and Pb for Tibet and Yunnan, respectively. Compared to health risk assessment, improved models increased risk assessment accuracy and provided recommended exposure parameter for high-risk populations. This study will provide new insights for soil-related health risk assessment.

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.

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.

Monocyte-related gene biomarkers for latent and active tuberculosis

Monocytes are closely associated with tuberculosis (TB). Latent tuberculosis in some patients gradually develops into its active state. This study aimed to investigate the role of hub monocyte-associated genes in distinguishing latent TB infection (LTBI) from active TB. The gene expression profiles of 15 peripheral blood mononuclear cells (PBMCs) samples were downloaded from the gene expression omnibus (GEO) database, GSE54992. The monocyte abundance was high in active TB as evaluated by the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm. The limma test and correlation analysis documented 165 differentially expressed monocyte-related genes (DEMonRGs) between latent TB and active TB. Functional annotation and enrichment analyses of the DEMonRGs using the database for annotation, visualization, and integration discovery (DAVID) tools showed enrichment of inflammatory response mechanisms and immune-related pathways. A protein-protein interaction network was constructed with a node degree ≥10. The expression levels of these hub DEMonRGs (SERPINA1, FUCA2, and HP) were evaluated and verified using several independent datasets and clinical settings. Finally, a single sample scoring method was used to establish a gene signature for the three DEMonRGs, distinguishing active TB from latent TB. The findings of the present study provide a better understanding of monocyte-related molecular fundamentals in TB progression and contribute to the identification of new potential biomarkers for the diagnosis of active TB.

Estimation of radiation gonadal doses for the American-Ukrainian trio study of parental irradiation in Chornobyl cleanup workers and evacuees and germline mutations in their offspring

Radiation doses of parents exposed from the Chornobyl accident as cleanup workers or evacuees were estimated in the National Cancer Institute-National Research Center for Radiation Medicine trio (i.e. father, mother, offspring) study aimed at investigating the radiation effects on germlinede novomutations in children as well as other outcomes. Paternal (testes) and maternal (ovaries) gonadal doses were calculated along with associated uncertainty distributions for the following exposure pathways: (a) external irradiation during the cleanup mission, (b) external irradiation during residence in Pripyat, and (c) external irradiation and (d) ingestion of radiocesium isotopes, such as¹³⁴Cs and¹³⁷Cs, during residence in settlements other than Pripyat. Gonadal doses were reconstructed for 298 trios for the periods from the time of the accident on 26 April 1986 to two time points before the child's date of birth (DOB): 51 (DOB-51) and 38 (DOB-38) weeks. The two doses, DOB-51 and DOB-38 were equal (within 1 mGy) in most instances, except for 35 fathers where the conception of the child occurred within 3 months of exposure or during exposure. The arithmetic mean of gonadal DOB-38 doses was 227 mGy (median: 11 mGy, range 0-4080 mGy) and 8.5 mGy (median: 1.0 mGy, range 0-550 mGy) for fathers and mothers, respectively. Gonadal doses varied considerably depending on the exposure pathway, the highest gonadal DOB-38 doses being received during the cleanup mission (mean doses of 376 and 34 mGy, median of 144 and 7.4 mGy for fathers and mothers, respectively), followed by exposure during residence in Pripyat (7.7 and 13 mGy for mean, 7.2 and 6.2 mGy for median doses) and during residence in other settlements (2.0 and 2.1 mGy for mean, 0.91 and 0.81 mGy for median doses). Monte Carlo simulations were used to estimate the parental gonadal doses and associated uncertainties. The geometric standard deviations (GSDs) in the individual parental stochastic doses due to external irradiation during the cleanup mission varied from 1.2 to 4.7 (mean of 1.8), while during residence in Pripyat they varied from 1.4 to 2.8 (mean of 1.8), while the mean GSD in doses received during residence in settlements other than Pripyat was 1.3 and 1.4 for external irradiation and ingestion of radiocesium isotopes, respectively.

Key Factors for Improving the Carcinogenic Risk Assessment of PAH Inhalation Exposure by Monte Carlo Simulation

Monte Carlo simulation (MCS) is a computational technique widely used in exposure and risk assessment. However, the result of traditional health risk assessment based on the MCS method has always been questioned due to the uncertainty introduced in parameter estimation and the difficulty in result validation. Herein, data from a large-scale investigation of individual polycyclic aromatic hydrocarbon (PAH) exposure was used to explore the key factors for improving the MCS method. Research participants were selected using a statistical sampling method in a typical PAH polluted city. Atmospheric PAH concentrations from 25 sampling sites in the area were detected by GC-MS and exposure parameters of participants were collected by field measurement. The incremental lifetime cancer risk (ILCR) of participants was calculated based on the measured data and considered to be the actual carcinogenic risk of the population. Predicted risks were evaluated by traditional assessment method based on MCS and three improved models including concentration-adjusted, age-stratified, and correlated-parameter-adjusted Monte Carlo methods. The goodness of fit of the models was evaluated quantitatively by comparing with the actual risk. The results showed that the average risk derived by traditional and age-stratified Monte Carlo simulation was 2.6 times higher, and the standard deviation was 3.7 times higher than the actual values. In contrast, the predicted risks of concentration- and correlated-parameter-adjusted models were in good agreement with the actual ILCR. The results of the comparison suggested that accurate simulation of exposure concentration and adjustment of correlated parameters could greatly improve the MCS. The research also reveals that the social factors related to exposure and potential relationship between variables are important issues affecting risk assessment, which require full consideration in assessment and further study in future research.

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.

Thyroid doses in Ukraine due to 131I intake after the Chornobyl accident. Report I: revision of direct thyroid measurements

The increased risk of thyroid cancer among individuals exposed during childhood and adolescence to Iodine-131 (131I) is the main statistically significant long-term effect of the Chornobyl accident. Several radiation epidemiological studies have been carried out or are currently in progress in Ukraine, to assess the risk of radiation-related health effects in exposed populations. About 150,000 measurements of 131I thyroid activity, so-called 'direct thyroid measurements', performed in May-June 1986 in the Ukrainian population served as the main sources of data used to estimate thyroid doses to the individuals of these studies. However, limitations in the direct thyroid measurements have been recently recognized including improper measurement geometry and unknown true values of calibration coefficients for unchecked thyroid detectors. In the present study, a comparative analysis of 131I thyroid activity measured by calibrated and unchecked devices in residents of the same neighboring settlements was conducted to evaluate the correct measurement geometry and calibration coefficients for measuring devices. As a result, revised values of 131I thyroid activity were obtained. On average, in Vinnytsia, Kyiv, Lviv and Chernihiv Oblasts and in the city of Kyiv, the revised values of the 131I thyroid activities were found to be 10-25% higher than previously reported, while in Zhytomyr Oblast, the values of the revised activities were found to be lower by about 50%. New sources of shared and unshared errors associated with estimates of 131I thyroid activity were identified. The revised estimates of thyroid activity are recommended to be used to develop an updated Thyroid Dosimetry system (TD20) for the entire population of Ukraine as well as to revise the thyroid doses for the individuals included in post-Chornobyl radiation epidemiological studies: the Ukrainian-American cohort of individuals exposed during childhood and adolescence, the Ukrainian in utero cohort and the Chornobyl Tissue Bank.

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.

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.

Review of experimental estimates for the protection afforded by eyewear for interventional x-ray staff

This paper attempts to systematise all published experimental results for the dose reduction factor (DRF) offered by leaded eyewear on clinicians performing interventional procedures. We aim to present a comprehensive analysis of the issue and a comparison of the various equipment models at different exposure geometries. The main purpose of the paper is, however, to clarify the best choice for the DRF within the possible diverse contexts and approaches to eye lens dose assessment. Evidence has been obtained that the lowest estimates of DRF are associated with larger scatter incidence angles and that, except for the slightly better performance exhibited by wraparound eyeglasses, there is no real distinction between the DRFs for the different equipment categories. The dataset as a whole confirms that, when measurements for the concerned eyewear model and irradiation conditions are unattainable, assuming DRF = 2 represents an adequately conservative choice. Nonetheless, this value includes only 17% of all results from the literature, whereas their histogram follows a distribution skewed towards higher values, represented by a median equal to 5. Therefore, if more realistic dose reconstructions are necessary, such as for purposes of epidemiological investigations or compensation decisions, the adoption of this central tendency index appears to be more reasonable. The complexity of characterising the DRF behaviour as a function of the various exposure factors reinforces the consideration of a statistical approach to eye lens dose assessment as a viable alternative. In this perspective, assuming for DRF a lognormal distribution with parameters [Formula: see text] and [Formula: see text] which has been verified to satisfactorily approximate the literature data distribution, should be deemed to be an appropriate option.

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.

ORGAN DOSE ESTIMATION ACCOUNTING FOR UNCERTAINTY FOR PEDIATRIC AND YOUNG ADULT CT SCANS IN THE UNITED KINGDOM

Since our previous publication of organ dose for the pediatric CT cohort in the UK, there have been questions about the magnitude of uncertainty in our dose estimates. We therefore quantified shared and unshared uncertainties in empirical CT parameters extracted from 1073 CT films (1978-2008) from 36 hospitals in the study and propagated these uncertainties into organ doses using Monte Carlo random sampling and NCICT organ dose calculator. The average of 500 median brain and marrow doses for the full cohort was 35 (95% confidence interval: 30-40) mGy and 6 (5-7) mGy, respectively. We estimated that shared uncertainty contributed ~99% of coefficient of variation of median brain doses in brain scans compared to unshared uncertainty (1% contribution). We found that the previous brain doses were slightly underestimated for <1990 and overestimated for >1990 compared to the results in the current study due to the revised CTDI models based on CT films.

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.

Tumour size can have an impact on the outcomes of epidemiological studies on second cancers after radiotherapy

Obtaining a correct dose-response relationship for radiation-induced cancer after radiotherapy presents a major challenge for epidemiological studies. The purpose of this paper is to gain a better understanding of the associated uncertainties. To accomplish this goal, some aspects of an epidemiological study on breast cancer following radiotherapy of Hodgkin's disease were simulated with Monte Carlo methods. It is demonstrated that although the doses to the breast volume are calculated by one treatment plan, the locations and sizes of the induced secondary breast tumours can be simulated and, based on these simulated locations and sizes, the absorbed doses at the site of tumour incidence can also be simulated. For the simulations of point dose at tumour site, linear and non-linear mechanistic models which predict risk of cancer induction as a function of dose were applied randomly to the treatment plan. These simulations provided for each second tumour and each simulated tumour size the predicted dose. The predicted-dose-response-characteristic from the analysis of the simulated epidemiological study was analysed. If a linear dose-response relationship for cancer induction was applied to calculate the theoretical doses at the simulated tumour sites, all Monte-Carlo realizations of the epidemiological study yielded strong evidence for a resulting linear risk to predicted-dose-response. However, if a non-linear dose-response of cancer induction was applied to calculate the theoretical doses, the Monte Carlo simulated epidemiological study resulted in a non-linear risk to predicted-dose-response relationship only if the tumour size was small (< 1.5 cm). If the diagnosed breast tumours exceeded an average diameter of 1.5 cm, an applied non-linear theoretical-dose-response relationship for second cancer falsely resulted in strong evidence for a linear predicted-dose relationship from the epidemiological study realizations. For a typical distribution of breast cancer sizes, the model selection probability for a resulting predicted-dose linear model was 61% although a non-linear theoretical-dose-response relationship for cancer induction had been applied. The results of this study, therefore, provide evidence that the shapes of epidemiologically obtained dose-response relationships for cancer induction can be biased by the finite size of the diagnosed second tumour, even though the epidemiological study was done correctly.

Part II: Verification of the TrueBeam head shielding model in Varian VirtuaLinac via out-of-field doses

PURPOSE

A good Monte Carlo model with an accurate head shielding model is important in estimating the long-term risks of unwanted radiation exposure during radiation therapy. The aim of this paper was to validate the Monte Carlo simulation of a TrueBeam linear accelerator (linac) head shielding model. We approach this by evaluating the accuracy of out-of-field dose predictions at extended distances which are comprised of scatter from within the patient and treatment head leakage and thus reflect the accuracy of the head shielding model. We quantify the out-of-field dose of a TrueBeam linac for low-energy photons, 6X and 6X-FFF beams, and compare measurements to Monte Carlo simulations using Varian VirtuaLinac that include a realistic head shielding model, for a variety of jaw sizes and angles up to a distance of 100 cm from the isocenter, in both positive and negative directions. Given the high value and utility of the VirtuaLinac model, it is critical that this model is validated thoroughly and the results be available to the medical physics community.

MATERIALS AND METHOD

Simulations were done using VirtuaLinac, the GEANT4-based Monte Carlo model of the TrueBeam treatment head from Varian Medical Systems, and an in-house GEANT4-based code. VirtuaLinac included a detailed model of the treatment head shielding and was run on the Amazon Web Services cloud to generate spherical phase space files surrounding the treatment head. These phase space files were imported into the in-house code, which modeled the measurement setup with a solid water buildup, the carbon fiber couch, and the gantry stand. For each jaw size (2 × 2 cm² , 4 × 4 cm² , 10 × 10 cm² , and 20 × 20 cm² ) and angular setting (0°, 90°, 45°, 135°), the dose was calculated at intervals of 5 cm along each measurement direction.

RESULTS

For the 10 × 10 cm² jaw size, both 6X and 6X-FFF showed very good agreement between simulation and measurement in both in-plane directions, with no apparent systematic bias. The percentage deviations for these settings were as follows: (mean, STDEV, maximum) (8.34, 6.44, 24.84) for 6X and (13.21, 8.93, 35.56) for 6X-FFF. For all jaw sizes, simulation agreed well in the in-plane direction going away from the gantry, but, some deviations were observed moving toward the gantry at larger distances. At larger distances, for the jaw sizes smaller than 10 × 10 cm² , the simulation underestimates the dose compared with measurement, while for jaw sizes larger than 10 × 10 cm² , it overestimates dose. For all comparisons between ±50 cm from isocenter, average absolute agreement between simulation and measurement was better than 28%.

CONCLUSION

We have validated the Varian VirtuaLinac's head shielding model via out-of-field doses and quantified the differences between TrueBeam head shielding model created out-of-field doses and measurements for an extended distance of 100 cm.

Bioaccessibility-corrected risk assessment of urban dietary methylmercury exposure via fish and rice consumption in China

The role of seafood consumption for dietary methylmercury (MeHg) exposure is well established. Recent studies also reveal that rice consumption can be an important pathway for dietary MeHg exposure in some Hg-contaminated areas. However, little is known about the relative importance of rice versus finfish in MeHg exposure for urban residents in uncontaminated areas. Especially, the lack of data on MeHg bioaccessibility in rice hinders accurately assessing MeHg exposure via rice consumption, and its importance compared to fish. By correcting commonly used risk models with quantified MeHg bioaccessibility, we provide the first bioaccessibility-corrected comparison on MeHg risk in rice and fish for consumers in non-contaminated urban areas of China, on both city- and province-scales. Market-available fish and rice samples were cooked and quantified for MeHg bioaccessibility. Methylmercury bioaccessibility in rice (40.5±9.4%) was significantly (p<0.05) lower than in fish (61.4±14.2%). This difference does not result from selenium content but may result from differences in protein or fiber content. Bioaccessibility-corrected hazard quotients (HQs) were calculated to evaluate consumption hazard of MeHg for consumers in Nanjing city, and Monte Carlo Simulations were employed to evaluate uncertainty and variability. Results indicate that MeHg HQs were 0.14 (P50) and 0.54 (P90). Rice consumption comprised 27.2% of the overall dietary exposure to MeHg in Nanjing, while fish comprised 72.8%. Employing our bioaccessibility data combined with literature parameters, calculated relative contribution to MeHg exposure from rice (versus fish) was high in western provinces of China, including Sichuan (95.6%) and Guizhou (81.5%), and low to moderate in eastern and southern provinces (Guangdong: 6.6%, Jiangsu: 17.7%, Shanghai: 15.1%, Guangxi: 20.6%, Jiangxi: 22.8% and Hunan: 25.9%). This bioaccessibility-corrected comparison of rice versus fish indicates that rice consumption can substantively contribute to dietary MeHg exposure risk for urban populations in Asia, and should be regularly included in dietary MeHg exposure assessment.

A cautionary comment on the generation of Berkson error in epidemiological studies

Exposure measurement error can be seen as one of the most important sources of uncertainty in studies in epidemiology. When the aim is to assess the effects of measurement error on statistical inference or to compare the performance of several methods for measurement error correction, it is indispensable to be able to generate different types of measurement error. This paper compares two approaches for the generation of Berkson error, which have recently been applied in radiation epidemiology, in their ability to generate exposure data that satisfy the properties of the Berkson model. In particular, it is shown that the use of one of the methods produces results that are not in accordance with two important properties of Berkson error.

Shared and unshared exposure measurement error in occupational cohort studies and their effects on statistical inference in proportional hazards models

Exposure measurement error represents one of the most important sources of uncertainty in epidemiology. When exposure uncertainty is not or only poorly accounted for, it can lead to biased risk estimates and a distortion of the shape of the exposure-response relationship. In occupational cohort studies, the time-dependent nature of exposure and changes in the method of exposure assessment may create complex error structures. When a method of group-level exposure assessment is used, individual worker practices and the imprecision of the instrument used to measure the average exposure for a group of workers may give rise to errors that are shared between workers, within workers or both. In contrast to unshared measurement error, the effects of shared errors remain largely unknown. Moreover, exposure uncertainty and magnitude of exposure are typically highest for the earliest years of exposure. We conduct a simulation study based on exposure data of the French cohort of uranium miners to compare the effects of shared and unshared exposure uncertainty on risk estimation and on the shape of the exposure-response curve in proportional hazards models. Our results indicate that uncertainty components shared within workers cause more bias in risk estimation and a more severe attenuation of the exposure-response relationship than unshared exposure uncertainty or exposure uncertainty shared between individuals. These findings underline the importance of careful characterisation and modeling of exposure uncertainty in observational studies.

Development of a source-exposure matrix for occupational exposure assessment of electromagnetic fields in the INTEROCC study

To estimate occupational exposures to electromagnetic fields (EMF) for the INTEROCC study, a database of source-based measurements extracted from published and unpublished literature resources had been previously constructed. The aim of the current work was to summarize these measurements into a source-exposure matrix (SEM), accounting for their quality and relevance. A novel methodology for combining available measurements was developed, based on order statistics and log-normal distribution characteristics. Arithmetic and geometric means, and estimates of variability and maximum exposure were calculated by EMF source, frequency band and dosimetry type. The mean estimates were weighted by our confidence in the pooled measurements. The SEM contains confidence-weighted mean and maximum estimates for 312 EMF exposure sources (from 0 Hz to 300 GHz). Operator position geometric mean electric field levels for radiofrequency (RF) sources ranged between 0.8 V/m (plasma etcher) and 320 V/m (RF sealer), while magnetic fields ranged from 0.02 A/m (speed radar) to 0.6 A/m (microwave heating). For extremely low frequency sources, electric fields ranged between 0.2 V/m (electric forklift) and 11,700 V/m (high-voltage transmission line-hotsticks), whereas magnetic fields ranged between 0.14 μT (visual display terminals) and 17 μT (tungsten inert gas welding). The methodology developed allowed the construction of the first EMF-SEM and may be used to summarize similar exposure data for other physical or chemical agents.

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.

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.

EPI-CT: design, challenges and epidemiological methods of an international study on cancer risk after paediatric and young adult CT

Computed tomography (CT) has great clinical utility and its usage has increased dramatically over the years. Concerns have been raised, however, about health impacts of ionising radiation exposure from CTs, particularly in children, who have a higher risk for some radiation induced diseases. Direct estimation of the health impact of these exposures is needed, but the conduct of epidemiological studies of paediatric CT populations poses a number of challenges which, if not addressed, could invalidate the results. The aim of the present paper is to review the main challenges of a study on the health impact of paediatric CTs and how the protocol of the European collaborative study EPI-CT, coordinated by the International Agency for Research on Cancer (IARC), is designed to address them. The study, based on a common protocol, is being conducted in Belgium, Denmark, France, Germany, the Netherlands, Norway, Spain, Sweden and the United Kingdom and it has recruited over one million patients suitable for long-term prospective follow-up. Cohort accrual relies on records of participating hospital radiology departments. Basic demographic information and technical data on the CT procedure needed to estimate organ doses are being abstracted and passive follow-up is being conducted by linkage to population-based cancer and mortality registries. The main issues which may affect the validity of study results include missing doses from other radiological procedures, missing CTs, confounding by CT indication and socioeconomic status and dose reconstruction. Sub-studies are underway to evaluate their potential impact. By focusing on the issues which challenge the validity of risk estimates from CT exposures, EPI-CT will be able to address limitations of previous CT studies, thus providing reliable estimates of risk of solid tumours and leukaemia from paediatric CT exposures and scientific bases for the optimisation of paediatric CT protocols and patient protection.

Thyroid Dose Estimates for a Cohort of Belarusian Children Exposed to (131)I from the Chernobyl Accident: Assessment of Uncertainties

Deterministic thyroid radiation doses due to iodine-131 ((131)I) intake were reconstructed in a previous article for 11,732 participants of the Belarusian-American cohort study of thyroid cancer and other thyroid diseases in individuals exposed during childhood or adolescence to fallout from the Chernobyl accident. The current article describes an assessment of uncertainties in reconstructed thyroid doses that accounts for the shared and unshared errors. Using a Monte Carlo simulation procedure, 1,000 sets of cohort thyroid doses due to (131)I intake were calculated. The arithmetic mean of the stochastic thyroid doses for the entire cohort was 0.68 Gy. For two-thirds of the cohort the arithmetic mean of individual stochastic thyroid doses was less than 0.5 Gy. The geometric standard deviation of stochastic doses varied among cohort members from 1.33 to 5.12 with an arithmetic mean of 1.76 and a geometric mean of 1.73. The uncertainties in thyroid dose were driven by the unshared errors associated with the estimates of values of thyroid mass and of the (131)I activity in the thyroid of the subject; the contribution of shared errors to the overall uncertainty was small. These multiple sets of cohort thyroid doses will be used to evaluate the radiation risks of thyroid cancer and noncancer thyroid diseases, taking into account the structure of the errors in the dose estimates.

Dose reconstruction for the million worker study: status and guidelines

The primary aim of the epidemiologic study of one million U.S. radiation workers and veterans [the Million Worker Study (MWS)] is to provide scientifically valid information on the level of radiation risk when exposures are received gradually over time and not within seconds, as was the case for Japanese atomic bomb survivors. The primary outcome of the epidemiologic study is cancer mortality, but other causes of death such as cardiovascular disease and cerebrovascular disease will be evaluated. The success of the study is tied to the validity of the dose reconstruction approaches to provide realistic estimates of organ-specific radiation absorbed doses that are as accurate and precise as possible and to properly evaluate their accompanying uncertainties. The dosimetry aspects for the MWS are challenging in that they address diverse exposure scenarios for diverse occupational groups being studied over a period of up to 70 y. The dosimetric issues differ among the varied exposed populations that are considered: atomic veterans, U.S. Department of Energy workers exposed to both penetrating radiation and intakes of radionuclides, nuclear power plant workers, medical radiation workers, and industrial radiographers. While a major source of radiation exposure to the study population comes from external gamma- or x-ray sources, for some of the study groups, there is a meaningful component of radionuclide intakes that requires internal radiation dosimetry assessments. Scientific Committee 6-9 has been established by the National Council on Radiation Protection and Measurements (NCRP) to produce a report on the comprehensive organ dose assessment (including uncertainty analysis) for the MWS. The NCRP dosimetry report will cover the specifics of practical dose reconstruction for the ongoing epidemiologic studies with uncertainty analysis discussions and will be a specific application of the guidance provided in NCRP Report Nos. 158, 163, 164, and 171. The main role of the Committee is to provide guidelines to the various groups of dosimetrists involved in the MWS to ensure that certain dosimetry criteria are considered: calculation of annual absorbed doses in the organs of interest, separation of low and high linear-energy transfer components, evaluation of uncertainties, and quality assurance and quality control. It is recognized that the MWS and its approaches to dosimetry are a work in progress and that there will be flexibility and changes in direction as new information is obtained with regard to both dosimetry and the epidemiologic features of the study components. This paper focuses on the description of the various components of the MWS, the available dosimetry results, and the challenges that have been encountered. It is expected that the Committee will complete its report in 2016.

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

Dosimetic uncertainties, particularly those that are shared among subgroups of a study population, can bias, distort or reduce the slope or significance of a dose response. Exposure estimates in studies of health risks from environmental radiation exposures are generally highly uncertain and thus, susceptible to these methodological limitations. An analysis was published in 2008 concerning radiation-related thyroid nodule prevalence in a study population of 2,994 villagers under the age of 21 years old between August 1949 and September 1962 and who lived downwind from the Semipalatinsk Nuclear Test Site in Kazakhstan. This dose-response analysis identified a statistically significant association between thyroid nodule prevalence and reconstructed doses of fallout-related internal and external radiation to the thyroid gland; however, the effects of dosimetric uncertainty were not evaluated since the doses were simple point "best estimates". In this work, we revised the 2008 study by a comprehensive treatment of dosimetric uncertainties. Our present analysis improves upon the previous study, specifically by accounting for shared and unshared uncertainties in dose estimation and risk analysis, and differs from the 2008 analysis in the following ways: 1. The study population size was reduced from 2,994 to 2,376 subjects, removing 618 persons with uncertain residence histories; 2. Simulation of multiple population dose sets (vectors) was performed using a two-dimensional Monte Carlo dose estimation method; and 3. A Bayesian model averaging approach was employed for evaluating the dose response, explicitly accounting for large and complex uncertainty in dose estimation. The results were compared against conventional regression techniques. The Bayesian approach utilizes 5,000 independent realizations of population dose vectors, each of which corresponds to a set of conditional individual median internal and external doses for the 2,376 subjects. These 5,000 population dose vectors reflect uncertainties in dosimetric parameters, partly shared and partly independent, among individual members of the study population. Risk estimates for thyroid nodules from internal irradiation were higher than those published in 2008, which results, to the best of our knowledge, from explicitly accounting for dose uncertainty. In contrast to earlier findings, the use of Bayesian methods led to the conclusion that the biological effectiveness for internal and external dose was similar. Estimates of excess relative risk per unit dose (ERR/Gy) for males (177 thyroid nodule cases) were almost 30 times those for females (571 cases) and were similar to those reported for thyroid cancers related to childhood exposures to external and internal sources in other studies. For confirmed cases of papillary thyroid cancers (3 in males, 18 in females), the ERR/Gy was also comparable to risk estimates from other studies, but not significantly different from zero. These findings represent the first reported dose response for a radiation epidemiologic study considering all known sources of shared and unshared errors in dose estimation and using a Bayesian model averaging (BMA) method for analysis of the dose response.