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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.

ObjectivesPrevious analyses of cataract in radiation-exposed populations have assessed relative risk; radiogenic excess additive risk (EAR), arguably of more public health importance, has not been estimated. Previous analysis of a large prospective cohort of US radiologic technologists (USRT) quantified excess relative risk of cataract in relation to occupational radiation dose. We aim to assess EARs of cataract.MethodsWe estimated EARs of cataract/cataract surgery in the USRT cohort using generalised additive models in relation to occupational radiation exposure, and assessed risk modification by a priori-selected cataract risk factors (diabetes, body mass index, smoking, race, sex, birth-year, ultraviolet B (UVB) radiation exposure).ResultsThere were 11 345 cataract diagnoses and 5440 of cataract surgery during 832 462 and 888 402 person-years of follow-up, respectively. Cumulative occupational radiation exposure was associated with self-reported cataract, but not with cataract surgery, with EAR/104 person-year Gy=94 (95% CI: 47 to 143, p<0.001) and EAR/104 person-year Gy=13 (95% CI: <0 to 57, p=0.551), respectively. There was marked (p<0.001) variation of EAR by age and by diabetes status, with risk higher among persons ≥75 years and diabetics. There were indications of elevated risk among those with higher UVB radiation (p=0.045), whites (p=0.056) and among those with higher levels of cigarette smoking (p=0.062). Elevated additive risk was observed for estimated occupational radiation eye-lens doses <100 mGy (p=0.004) with no dose–response curvature (p=0.903).ConclusionsThe elevated additive risks associated with low-dose radiation, if confirmed elsewhere, have important public health and clinical implications for radiation workers as well as regulatory measures.

It has long been known that relatively high-dose ionising radiation exposure (> 1 Gy) can induce cataract, but there has been no evidence that this occurs at low doses (< 100 mGy). To assess low-dose risk, participants from the US Radiologie Technologists Study, a large, prospective cohort, were followed from date of mailed questionnaire survey completed during 1994–1998 to the earliest of self-reported diagnosis of cataract/cataract surgery, cancer other than non-melanoma skin, or date of last survey (up to end 2014). Cox proportional hazards models with age as timescale were used, adjusted for a priori selected cataract risk factors (diabetes, body mass index, smoking history, race, sex, birth year, cumulative UVB radiant exposure). 12,336 out of 67,246 eligible technologists reported a history of diagnosis of cataract during 832,479 person years of follow-up, and 5509 from 67,709 eligible technologists reported undergoing cataract surgery with 888,420 person years of follow-up. The mean cumulative estimated 5-year lagged eye-lens absorbed dose from occupational radiation exposures was 55.7 mGy (interquartile range 23.6-69.0 mGy). Five-year lagged occupational radiation exposure was strongly associated with self-reported cataract, with an excess hazard ratio/mGy of 0.69 × 10⁻³ (95% CI 0.27 × 10⁻³ to 1.16 × 10⁻³, p < 0.001). Cataract risk remained statistically significant (p = 0.030) when analysis was restricted to < 100 mGy cumulative occupational radiation exposure to the eye lens. A non-significantly increased excess hazard ratio/mGy of 0.34 × 10⁻³ (95% CI – 0.19 × 10⁻³ to 0.97 × 10⁻³, p = 0.221) was observed for cataract surgery. Our results suggest that there is excess risk for cataract associated with radiation exposure from low-dose and low dose-rate occupational exposures.

It has now been over 60 years since U.S. nuclear testing was conducted in the Pacific islands and Nevada, exposing military personnel to varying levels of ionizing radiation. Actual doses are not well-established, as film badges in the 1950s had many limitations. We sought a means of independently assessing dose for comparison with historical film badge records and dose reconstruction conducted in parallel. For the purpose of quantitative retrospective biodosimetry, peripheral blood samples from 12 exposed veterans and 12 age-matched (>80 years) veteran controls were collected and evaluated for radiation-induced chromosome damage utilizing directional genomic hybridization (dGH), a cytogenomics-based methodology that facilitates simultaneous detection of translocations and inversions. Standard calibration curves were constructed from six male volunteers in their mid-20s to reflect the age range of the veterans at time of exposure. Doses were estimated for each veteran using translocation and inversion rates independently; however, combining them by a weighted-average generally improved the accuracy of dose estimations. Various confounding factors were also evaluated for potential effects on chromosome aberration frequencies. Perhaps not surprisingly, smoking and age-associated increases in background frequencies of inversions were observed. Telomere length was also measured, and inverse relationships with both age and combined weighted dose estimates were observed. Interestingly, smokers in the non-exposed control veteran cohort displayed similar telomere lengths as those in the never-smoker exposed veteran group, suggesting that chronic smoking had as much effect on telomere length as a single exposure to radioactive fallout. Taken together, we find that our approach of combined chromosome aberration-based retrospective biodosimetry provided reliable dose estimation capability, particularly on a group average basis, for exposures above statistical detection limits.

Epidemiological studies of medical radiation workers have found excess risks of leukemia, skin and female breast cancer in those employed before 1950 but little consistent evidence of cancer risk increases subsequently. Occupational radiation-related dose–response data and recent and lifetime cancer risk data are limited for radiologists and radiologic technologists and lacking for physicians and technologists performing fluoroscopically guided procedures. Survey data demonstrate that occupational doses to radiologists and radiologic technologists have declined over time. Eighty mostly small studies of cardiologists and fewer studies of other physicians reveal that effective doses to physicians per interventional procedure vary by more than an order of magnitude. For medical radiation workers, there is an urgent need to expand the limited information on average annual, time-trend and organ doses from occupational radiation exposures and to assess lifetime cancer risks of these workers. For physicians and technologists performing interventional procedures, more information about occupational doses should be collected and long-term follow-up studies of cancer and other serious disease risks should be initiated. Such studies will help optimize standardized protocols for radiologic procedures, determine whether current radiation protection measures for medical radiation workers are adequate, provide guidance on cancer screening needs, and yield valuable insights on cancer risks associated with chronic radiation exposure.

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.

In this article, we describe recent methodological enhancements and findings from the dose reconstruction component of a study of health risks among U.S. radiologic technologists. An earlier version of the dosimetry published in 2006 used physical and statistical models, literature-reported exposure measurements for the years before 1960, and archival personnel monitoring badge data from cohort members through 1984. The data and models previously described were used to estimate annual occupational radiation doses for 90,000 radiological technologists, incorporating information about each individual's employment practices based on a baseline survey conducted in the mid-1980s. The dosimetry methods presented here, while using many of the same methods as before, now estimate 2.23 million annual badge doses (personal dose equivalent) for the years 1916–1997 for 110,374 technologists, but with numerous methodological improvements. Every technologist's annual dose is estimated as a probability density function to reflect uncertainty about the true dose. Multiple realizations of the entire cohort distribution were derived to account for shared uncertainties and possible biases in the input data and assumptions used. Major improvements in the dosimetry methods from the earlier version include: A substantial increase in the number of cohort member annual badge dose measurements; Additional information on individual apron usage obtained from surveys conducted in the mid-1990s and mid-2000s; Refined modeling to develop lognormal annual badge dose probability density functions using censored data regression models; Refinements of cohort-based annual badge probability density functions to reflect individual work patterns and practices reported on questionnaires and to more accurately assess minimum detection limits; and Extensive refinements in organ dose conversion coefficients to account for uncertainties in radiographic machine settings for the radiographic techniques employed. For organ dose estimation, we rely on well-researched assumptions about critical exposure-related variables and their changes over the decades, including the peak kilovoltage and filtration typically used in conducting radiographic examinations, and the usual body location for wearing radiation monitoring badges, the latter based on both literature and national recommendations. We have derived organ dose conversion coefficients based on air-kerma weighting of photon fluences from published X-ray spectra and derived energy-dependent transmission factors for protective lead aprons of different thicknesses. Findings are presented on estimated organ doses for 12 organs and tissues: red bone marrow, female breast, thyroid, brain, lung, heart, colon, ovary, testes, skin of trunk, skin of head and neck and arms, and lens of the eye.

Chromosome translocations are a well-recognized biological marker of radiation exposure and cancer risk. However, there is uncertainty about the lowest dose at which excess translocations can be detected, and whether there is temporal decay of induced translocations in radiation-exposed populations. Dosimetric uncertainties can substantially alter the shape of dose-response relationships; although regression-calibration methods have been used in some datasets, these have not been applied in radio-occupational studies, where there are also complex patterns of shared and unshared errors that these methods do not account for. In this article we evaluated the relationship between estimated occupational ionizing radiation doses and chromosome translocation rates using fluorescent in situ hybridization in 238 U.S. radiologic technologists selected from a large cohort. Estimated cumulative red bone marrow doses (mean 29.3 mGy, range 0–135.7 mGy) were based on available badge–dose measurement data and on questionnaire-reported work history factors. Dosimetric assessment uncertainties were evaluated using regression calibration, Bayesian and Monte Carlo maximum likelihood methods, taking account of shared and unshared error and adjusted for overdispersion. There was a significant dose response for estimated occupational radiation exposure, adjusted for questionnaire-based personal diagnostic radiation, age, sex and study group (5.7 translocations per 100 whole genome cell equivalents per Gy, 95% CI 0.2, 11.3, P = 0.0440). A significant increasing trend with dose continued to be observed for individuals with estimated doses <100 mGy. For combined estimated occupational and personal-diagnostic-medical radiation exposures, there was a borderline-significant modifying effect of age (P = 0.0704), but little evidence (P > 0.5) of temporal decay of induced translocations. The three methods of analysis to adjust for dose uncertainty gave similar results. In summary, chromosome translocation dose-response slopes were detectable down to <100 mGy and were compatible with those observed in other radiation-exposed populations. However, there are substantial uncertainties in both occupational and other (personal-diagnostic-medical) doses that may be imperfectly taken into account in our analysis.

There are well-documented associations of glaucoma with high-dose radiation exposure, but only a single study suggesting risk of glaucoma, and less conclusively macular degeneration, associated with moderate-dose exposure. We assessed risk of glaucoma and macular degeneration associated with occupational eye-lens radiation dose, using participants from the US Radiologic Technologists Study, followed from the date of surveys in 1994–1998, 2003–2005 to the earliest of diagnosis of glaucoma or macular degeneration, cancer other than non-melanoma skin cancer, or date of last survey (2012–2014). We excluded those with baseline disease or previous radiotherapy history. Cox proportional hazards models with age as timescale were used. There were 1631 cases of newly self-reported doctor-diagnosed cases of glaucoma and 1331 of macular degeneration among 69,568 and 69,969 eligible subjects, respectively. Estimated mean cumulative eye-lens absorbed dose from occupational radiation exposures was 0.058 Gy. The excess relative risk/Gy for glaucoma was −0.57 (95% CI −1.46, 0.60, p  = 0.304) and for macular degeneration was 0.32 (95% CI −0.32, 1.27, p  = 0.381), suggesting that there is no appreciable risk for either endpoint associated with low-dose and low dose-rate radiation exposure. Since this is the first examination of glaucoma and macular degeneration associated with low-dose radiation exposure, this result needs to be replicated in other low-dose studies.