2004 update of dosimetry for the Utah Thyroid Cohort Study

A Methodology for Calculation of Internal Dose Following Exposure to Radioactive Fallout from the Detonation of a Nuclear Fission Device

ABSTRACT

The purpose of this paper is to provide a methodology for the calculation of internal doses of radiation following exposure to radioactive fallout from the detonation of a nuclear fission device. Reliance is on methodology previously published in the open literature or in reports not readily available, though some new analysis is also included. Herein, we present two methodologic variations: one simpler to implement, the other more difficult but more flexible. The intention is to provide in one place a comprehensive methodology. Pathways considered are (1) the ingestion of vegetables and fruits contaminated by fallout directly, (2) the ingestion of vegetables and fruits contaminated by continuing deposition by rain- or irrigation-splash and resuspension, (3) the ingestion of vegetables and fruits contaminated by absorption of radionuclides by roots after tillage of soil, (4) the non-equilibrium transfer of short-lived radionuclides through the cow-milk and goat-milk food chains, (5) the equilibrium transfer of long lived radionuclides through milk and meat food chains, and (6) inhalation of descending fallout. Uncertainty in calculated results is considered. This is one of six companion papers that describe a comprehensive methodology for assessing both external and internal dose following exposures to fallout from a nuclear detonation. Input required to implement the dose-estimation model for any particular location consists of an estimate of the post-detonation external gamma-exposure rate and an estimate of the time of arrival of the fallout cloud. The additional data required to make such calculations are included in the six companion papers.

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

ABSTRACT

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

Dose Estimation for Exposure to Radioactive Fallout from Nuclear Detonations

ABSTRACT

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

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

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

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.

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

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

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

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

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.

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

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

Thyroid cancer study among Ukrainian children exposed to radiation after the Chornobyl accident: improved estimates of the thyroid doses to the cohort members

In collaboration with the Ukrainian Research Center for Radiation Medicine, the U.S. National Cancer Institute initiated a cohort study of children and adolescents exposed to Chornobyl fallout in Ukraine to better understand the long-term health effects of exposure to radioactive iodines. All 13,204 cohort members were subjected to at least one direct thyroid measurement between 30 April and 30 June 1986 and resided at the time of the accident in the northern parts of Kyiv, Zhytomyr, or Chernihiv Oblasts, which were the most contaminated territories of Ukraine as a result of radioactive fallout from the Chornobyl accident. Thyroid doses for the cohort members, which had been estimated following the first round of interviews, were re-evaluated following the second round of interviews. The revised thyroid doses range from 0.35 mGy to 42 Gy, with 95% of the doses between 1 mGy and 4.2 Gy, an arithmetic mean of 0.65 Gy, and a geometric mean of 0.19 Gy. These means are 70% of the previous estimates, mainly because of the use of country-specific thyroid masses. Many of the individual thyroid dose estimates show substantial differences because of the use of an improved questionnaire for the second round of interviews. Limitations of the current set of thyroid dose estimates are discussed. For the epidemiologic study, the most notable improvement is a revised assessment of the uncertainties, as shared and unshared uncertainties in the parameter values were considered in the calculation of the 1,000 stochastic estimates of thyroid dose for each cohort member. This procedure makes it possible to perform a more realistic risk analysis.

Childhood thyroid radioiodine exposure and subsequent infertility in the intermountain fallout cohort

BACKGROUND

Above-ground and underground nuclear weapon detonation at the Nevada Test Site (1951-1992) has resulted in radioiodine exposure for nearby populations. Although the long-term effect of environmental radioiodine exposure on thyroid disease has been well studied, little is known regarding the effect of childhood radioiodine exposure on subsequent fertility.

OBJECTIVES

We investigated early childhood thyroid radiation exposure from nuclear testing fallout (supplied predominantly by radioactive isotopes of iodine) and self-reported lifetime incidence of male or female infertility or sterility.

METHODS

Participants were members of the 1965 Intermountain Fallout Cohort, schoolchildren at the time of exposure who were reexamined during two subsequent study phases to collect dietary and reproductive histories. Thyroid radiation exposure was calculated via an updated dosimetry model. We used multivariable logistic regression with robust sandwich estimators to estimate odds ratios for infertility, adjusted for potential confounders and (in separate models) for a medically confirmed history of thyroid disease.

RESULTS

Of 1,389 participants with dosimetry and known fertility history, 274 were classified as infertile, including 30 classified as sterile. Childhood thyroid radiation dose was possibly associated with infertility [adjusted odds ratio (AOR) = 1.17; 95% CI: 0.82, 1.67 and AOR = 1.35; 95% CI: 0.96, 1.90 for the middle and upper tertiles vs. the first tertile of exposure, respectively]. The odds ratios were attenuated (AOR = 1.08; 95% CI: 0.75, 1.55 and AOR = 1.29; 95% CI: 0.91, 1.83 for the middle and upper tertiles, respectively) after adjusting for thyroid disease. There was no association of childhood radiation dose and sterility.

CONCLUSION

Our findings suggest that childhood radioiodine exposure from nuclear testing may be related to subsequent adult infertility. Further research is required to confirm this.

Estimation via corrected scores in general semiparametric regression models with error-prone covariates

This paper considers the problem of estimation in a general semiparametric regression model when error-prone covariates are modeled parametrically while covariates measured without error are modeled nonparametrically. To account for the effects of measurement error, we apply a correction to a criterion function. The specific form of the correction proposed allows Monte Carlo simulations in problems for which the direct calculation of a corrected criterion is difficult. Therefore, in contrast to methods that require solving integral equations of possibly multiple dimensions, as in the case of multiple error-prone covariates, we propose methodology which offers a simple implementation. The resulting methods are functional, they make no assumptions about the distribution of the mismeasured covariates. We utilize profile kernel and backfitting estimation methods and derive the asymptotic distribution of the resulting estimators. Through numerical studies we demonstrate the applicability of proposed methods to Poisson, logistic and multivariate Gaussian partially linear models. We show that the performance of our methods is similar to a computationally demanding alternative. Finally, we demonstrate the practical value of our methods when applied to Nevada Test Site (NTS) Thyroid Disease Study data.

SIMEX and standard error estimation in semiparametric measurement error models

SIMEX is a general-purpose technique for measurement error correction. There is a substantial literature on the application and theory of SIMEX for purely parametric problems, as well as for purely non-parametric regression problems, but there is neither application nor theory for semiparametric problems. Motivated by an example involving radiation dosimetry, we develop the basic theory for SIMEX in semiparametric problems using kernel-based estimation methods. This includes situations that the mismeasured variable is modeled purely parametrically, purely non-parametrically, or that the mismeasured variable has components that are modeled both parametrically and nonparametrically. Using our asymptotic expansions, easily computed standard error formulae are derived, as are the bias properties of the nonparametric estimator. The standard error method represents a new method for estimating variability of nonparametric estimators in semiparametric problems, and we show in both simulations and in our example that it improves dramatically on first order methods.We find that for estimating the parametric part of the model, standard bandwidth choices of order O(n(-1/5)) are sufficient to ensure asymptotic normality, and undersmoothing is not required. SIMEX has the property that it fits misspecified models, namely ones that ignore the measurement error. Our work thus also more generally describes the behavior of kernel-based methods in misspecified semiparametric problems.

Reconstruction of individual radiation doses for a case-control study of thyroid cancer in French Polynesia

Forty-one atmospheric nuclear weapons tests (plus five safety tests) were conducted in French Polynesia between 1966 and 1974. To evaluate the potential role of atmospheric nuclear weapons testing on a high incidence of thyroid cancer observed since 1985 in French Polynesia, a population-based case-control study was performed. The study included 602 subjects, either cases or controls, all aged less than 40 y at the end of nuclear weapons testing in 1974. Radiation doses to the thyroids of the study subjects were assessed based on the available historical results of radiation measurements. These were mainly found in the annual reports on the radiological situation in French Polynesia that had been sent to the UNSCEAR Secretariat. For each atmospheric nuclear weapons test that contributed substantially to the local deposition of radionuclides, the radiation dose to the thyroid from I intake was estimated. In addition, thyroid doses from the intake of short-lived radioiodines (132I, 133I, 135I) and 132Te, external exposure from gamma-emitted radionuclides deposited on the ground, and ingestion of long-lived Cs were reconstructed. The mean thyroid dose among the study subjects was found to be around 3 mGy while the highest dose was estimated to be around 40 mGy. Doses from short-lived iodine and tellurium isotopes ranged up to 10 mGy. Thyroid doses from external exposure ranged up to 3 mGy, while those from internal exposure due to cesium ingestion did not exceed 1 mGy. The dose estimates that have been obtained are based on a rather limited number of radiation measurements performed on a limited number of islands and are highly uncertain. A thorough compilation of the results of all radiation monitoring that was performed in French Polynesia in 1966-1974 would be likely to greatly improve the reliability and the precision of the dose estimates.

Shared uncertainty in measurement error problems, with application to Nevada Test Site fallout data

In radiation epidemiology, it is often necessary to use mathematical models in the absence of direct measurements of individual doses. When complex models are used as surrogates for direct measurements to estimate individual doses that occurred almost 50 years ago, dose estimates will be associated with considerable error, this error being a mixture of (a) classical measurement error due to individual data such as diet histories and (b) Berkson measurement error associated with various aspects of the dosimetry system. In the Nevada Test Site(NTS) Thyroid Disease Study, the Berkson measurement errors are correlated within strata. This article concerns the development of statistical methods for inference about risk of radiation dose on thyroid disease, methods that account for the complex error structure inherence in the problem. Bayesian methods using Markov chain Monte Carlo and Monte-Carlo expectation-maximization methods are described, with both sharing a key Metropolis-Hastings step. Regression calibration is also considered, but we show that regression calibration does not use the correlation structure of the Berkson errors. Our methods are applied to the NTS Study, where we find a strong dose-response relationship between dose and thyroiditis. We conclude that full consideration of mixtures of Berkson and classical uncertainties in reconstructed individual doses are important for quantifying the dose response and its credibility/confidence interval. Using regression calibration and expectation values for individual doses can lead to a substantial underestimation of the excess relative risk per gray and its 95% confidence intervals.

Non-parametric regression estimation from data contaminated by a mixture of Berkson and classical errors

Estimation of a regression function is a well-known problem in the context of errors in variables, where the explanatory variable is observed with random noise. This noise can be of two types, which are known as classical or Berkson, and it is common to assume that the error is purely of one of these two types. In practice, however, there are many situations where the explanatory variable is contaminated by a mixture of the two errors. In such instances, the Berkson component typically arises because the variable of interest is not directly available and can only be assessed through a proxy, whereas the inaccuracy that is related to the observation of the latter causes an error of classical type. We propose a non-parametric estimator of a regression function from data that are contaminated by a mixture of the two errors. We prove consistency of our estimator, derive rates of convergence and suggest a data-driven implementation. Finite sample performance is illustrated via simulated and real data examples.

Pediatric CT research elevates public health concerns: low-dose radiation issues are highly politicized

This article presents an analysis of issues related to low-dose radiation, with a focus on pediatric computed tomography (CT). It references several early studies that are seldom quoted in radiation research papers, then quantifies the excess lifetime fatal cancer yield attributable to an estimated 6.5 million pediatric abdominal CT scans. The authors highlight an important policy document issued jointly by the National Cancer Institute and the Society for Pediatric Radiology--specifically, its conclusion that a small dose from CT represents "a public health concern." Finally, the article identifies several contentious issues and proposes policy initiatives that, if implemented, could result in significant reductions of future radiogenic cancers and chronic injuries. The authors call for discussions between professional radiology societies and public interest health organizations, thereby involving all stakeholders.

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

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

Thyroid Disease Associated With Exposure to the Nevada Nuclear Weapons Test Site Radiation

BACKGROUND

A study was begun in 1965 to 1966 to determine whether children exposed to radioactive iodine from nuclear weapons testing at the Nevada Test Site from 1951 through 1962 were at higher risk of thyroid disease. In 1993, we reported that among those examined in 1985 to 1986 (Phase II) there was an association between radiation from the Nevada Test Site and thyroid neoplasms.

METHODS

We reevaluated the relationship between exposure to Nevada Test Site fallout and thyroid disease using newly corrected dose estimates and disease outcomes from the Phase II study. A prospective cohort of school children 12 to 18 years old living in Utah, Nevada, and Arizona was first examined for thyroid disease in 1965 to 1966 and reexamined in 1985 to 1986. In the Phase II report, 2497 subjects formed the basis for this analysis. Thyroid disease, including thyroid neoplasms and thyroiditis, was expressed as cumulative incidence and risk ratios (RRs) with a dose-response expressed as excess risk ratio (ERR/Gy).

RESULTS

The RR between thyroid radiation dose in the highest dose group and thyroid neoplasms increased from 3.4 (in the earlier analysis) to 7.5. The RR for thyroiditis increased from 1.1 to 2.7 with an ERR/Gy of 4.9 (95% confidence interval = 2.0 to 10.0). There were too few malignant thyroid neoplasms to estimate risk.

CONCLUSIONS

Persons exposed to radioactive iodine as children have an increased risk of thyroid neoplasms and autoimmune thyroiditis up to 30 years after exposure.