Estimation of thyroid radiation doses for the hanford thyroid disease study: results and implications for statistical power of the epidemiological analyses

Radiation-Related Thyroid Cancer

Radiation is an environmental factor that elevates the risk of developing thyroid cancer. Actual and possible scenarios of exposures to external and internal radiation are multiple and diverse. This article reviews radiation doses to the thyroid and corresponding cancer risks due to planned, existing, and emergency exposure situations, and medical, public, and occupational categories of exposures. Any exposure scenario may deliver a range of doses to the thyroid, and the risk for cancer is addressed along with modifying factors. The consequences of the Chornobyl and Fukushima nuclear power plant accidents are described, summarizing the information on thyroid cancer epidemiology, treatment, and prognosis, clinicopathological characteristics, and genetic alterations. The Chornobyl thyroid cancers have evolved in time: becoming less aggressive and driver shifting from fusions to point mutations. A comparison of thyroid cancers from the 2 areas reveals numerous differences that cumulatively suggest the low probability of the radiogenic nature of thyroid cancers in Fukushima. In view of continuing usage of different sources of radiation in various settings, the possible ways of reducing thyroid cancer risk from exposures are considered. For external exposures, reasonable measures are generally in line with the As Low As Reasonably Achievable principle, while for internal irradiation from radioactive iodine, thyroid blocking with stable iodine may be recommended in addition to other measures in case of anticipated exposures from a nuclear reactor accident. Finally, the perspectives of studies of radiation effects on the thyroid are discussed from the epidemiological, basic science, and clinical points of view.

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.

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

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

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.

THE GROWTH OF BIOSTATISTICS AND ESTIMATION OF CANCER RISK ESTIMATES: PAST, CURRENT, AND FUTURE CHALLENGES

There has been a long process of growth and development of statistical approaches to the analysis of cancer incidence and mortality data obtained from the follow-up of radiation exposed populations. The challenges of radiation risk analysis provided impetus for innovative statistical methods, including, the inception and continued improvement of hazard rate regression methods. Key statistical contributions that improved cancer risk estimation include statistical advances pertaining to the measurement error problem. Current statistical problems involve extensions of the measurement error methods to account for shared non-independent uncertainties in dose estimation, 'transportability' of risk coefficients for radioprotection and risk estimation world-wide, and extrapolation from high dose rate to low-dose rate exposures or from low LET to high LET. Future problems include quantification of individual sensitivity to radiation-related diseases due to individual genetic differences (or other factors), and in understanding the synergy (additive, multiplicative, etc.) between underlying individual risk and radiation exposure.

Reconstructing Historical VOC Concentrations in Drinking Water for Epidemiological Studies at a U.S. Military Base: Summary of Results

A U.S. government health agency conducted epidemiological studies to evaluate whether exposures to drinking water contaminated with volatile organic compounds (VOC) at U.S. Marine Corps Base Camp Lejeune, North Carolina, were associated with increased health risks to children and adults. These health studies required knowledge of contaminant concentrations in drinking water—at monthly intervals—delivered to family housing, barracks, and other facilities within the study area. Because concentration data were limited or unavailable during much of the period of contamination (1950s–1985), the historical reconstruction process was used to quantify estimates of monthly mean contaminant-specific concentrations. This paper integrates many efforts, reports, and papers into a synthesis of the overall approach to, and results from, a drinking-water historical reconstruction study. Results show that at the Tarawa Terrace water treatment plant (WTP) reconstructed (simulated) tetrachloroethylene (PCE) concentrations reached a maximum monthly average value of 183 micrograms per liter (μg/L) compared to a one-time maximum measured value of 215 μg/L and exceeded the U.S. Environmental Protection Agency’s current maximum contaminant level (MCL) of 5 μg/L during the period November 1957–February 1987. At the Hadnot Point WTP, reconstructed trichloroethylene (TCE) concentrations reached a maximum monthly average value of 783 μg/L compared to a one-time maximum measured value of 1400 μg/L during the period August 1953–December 1984. The Hadnot Point WTP also provided contaminated drinking water to the Holcomb Boulevard housing area continuously prior to June 1972, when the Holcomb Boulevard WTP came on line (maximum reconstructed TCE concentration of 32 μg/L) and intermittently during the period June 1972–February 1985 (maximum reconstructed TCE concentration of 66 μg/L). Applying the historical reconstruction process to quantify contaminant-specific monthly drinking-water concentrations is advantageous for epidemiological studies when compared to using the classical exposed versus unexposed approach.

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.

Shared dosimetry error in epidemiological dose-response analyses

Radiation dose reconstruction systems for large-scale epidemiological studies are sophisticated both in providing estimates of dose and in representing dosimetry uncertainty. For example, a computer program was used by the Hanford Thyroid Disease Study to provide 100 realizations of possible dose to study participants. The variation in realizations reflected the range of possible dose for each cohort member consistent with the data on dose determinates in the cohort. Another example is the Mayak Worker Dosimetry System 2013 which estimates both external and internal exposures and provides multiple realizations of "possible" dose history to workers given dose determinants. This paper takes up the problem of dealing with complex dosimetry systems that provide multiple realizations of dose in an epidemiologic analysis. In this paper we derive expected scores and the information matrix for a model used widely in radiation epidemiology, namely the linear excess relative risk (ERR) model that allows for a linear dose response (risk in relation to radiation) and distinguishes between modifiers of background rates and of the excess risk due to exposure. We show that treating the mean dose for each individual (calculated by averaging over the realizations) as if it was true dose (ignoring both shared and unshared dosimetry errors) gives asymptotically unbiased estimates (i.e. the score has expectation zero) and valid tests of the null hypothesis that the ERR slope β is zero. Although the score is unbiased the information matrix (and hence the standard errors of the estimate of β) is biased for β≠0 when ignoring errors in dose estimates, and we show how to adjust the information matrix to remove this bias, using the multiple realizations of dose. The use of these methods in the context of several studies including, the Mayak Worker Cohort, and the U.S. Atomic Veterans Study, is discussed.

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.

Representative doses to members of the public from atmospheric releases of (131)I at the Mayak Production Association facilities from 1948 through 1972

Scoping epidemiology studies performed by researchers from the Southern Urals Biophysics Institute revealed an excess prevalence of thyroid nodules and an increased incidence of thyroid cancer among residents of Ozersk, Russia, who were born in the early 1950s. Ozersk is located about 5 km from the facilities where the Mayak Production Association produced nuclear materials for the Russian weapons program. Reactor operations began in June 1948 and chemical separation of plutonium from irradiated fuel began in February 1949. The U.S.-Russia Joint Coordinating Committee on Radiation Effects Research conducted a series of projects over a 10-year period to assess the radiation risks in the Southern Urals. This paper uses data collected under Committee projects to present examples of reconstructed time-dependent thyroid doses to reference individuals living in Ozersk from (131)I released to the atmosphere for all relevant exposure pathways. Between 3.22 × 10(16) and 4.31 × 10(16) Bq of (131)I may have been released during the 1948-1972 time period, and a best estimate is 3.76 × 10(16) Bq. In general, younger children incur greater thyroid doses from (131)I than adults. A child born in 1947 is estimated to have received a cumulative thyroid dose of 2.3 Gy for 1948-1972, with a 95% confidence interval of 0.51-7.3 Gy. Annual doses were the highest in 1949 and a child who was 5 years old in 1949 is estimated to have a received an annual thyroid dose of 0.93 Gy with a 95% confidence interval of 0.19-3.5 Gy.

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.

Incorporating individual-level distributions of exposure error in epidemiologic analyses: an example using arsenic in drinking water and bladder cancer

PURPOSE

Epidemiologic analyses traditionally rely on point estimates of exposure for assessing risk despite exposure error. We present a strategy that produces a range of risk estimates reflecting distributions of individual-level exposure.

METHODS

Quantitative estimates of exposure and its associated error are used to create for each individual a normal distribution of exposure estimates which is then sampled using Monte Carlo simulation. After the exposure estimate is sampled, the relationship between exposure and disease is evaluated; this process is repeated 99 times generating a distribution of risk estimates and confidence intervals. This is demonstrated in a bladder cancer case-control study using individual-level distributions of exposure to arsenic in drinking water.

RESULTS

Sensitivity analyses indicate similar performance for categorical or continuous exposure estimates, and that increases in exposure error translate into a wider range of risk estimates. Bladder cancer analyses yield a wide range of possible risk estimates, allowing quantification of exposure error in the association between arsenic and bladder cancer, typically ignored in conventional analyses.

CONCLUSIONS

Incorporating distributions of individual-level exposure error results in a more nuanced depiction of epidemiologic findings. This approach can be readily adopted by epidemiologists assuming distributions of individual-level exposure.

Ultrasound-detected thyroid nodule prevalence and radiation dose from fallout

Settlements near the Semipalatinsk Test Site (SNTS) in northeastern Kazakhstan were exposed to radioactive fallout during 1949-1962. Thyroid disease prevalence among 2994 residents of eight villages was ascertained by ultrasound screening. Malignancy was determined by cytopathology. Individual thyroid doses from external and internal radiation sources were reconstructed from fallout deposition patterns, residential histories and diet, including childhood milk consumption. Point estimates of individual external and internal dose averaged 0.04 Gy (range 0-0.65) and 0.31 Gy (0-9.6), respectively, with a Pearson correlation coefficient of 0.46. Ultrasound-detected thyroid nodule prevalence was 18% and 39% among males and females, respectively. It was significantly and independently associated with both external and internal dose, the main study finding. The estimated relative biological effectiveness of internal compared to external radiation dose was 0.33, with 95% confidence bounds of 0.09-3.11. Prevalence of papillary cancer was 0.9% and was not significantly associated with radiation dose. In terms of excess relative risk per unit dose, our dose-response findings for nodule prevalence are comparable to those from populations exposed to medical X rays and to acute radiation from the Hiroshima and Nagasaki atomic bombings.

Thyrotropin levels in a population with no clinical, autoantibody, or ultrasonographic evidence of thyroid disease: implications for the diagnosis of subclinical hypothyroidism

CONTEXT

The current debate regarding whether to decrease the upper limit for the TSH reference range to 2.5 microIU/ml has considerable potential impact on the diagnosis and treatment of subclinical hypothyroidism worldwide.

OBJECTIVE

We report an analysis of TSH distribution in a population with no evidence of thyroid disease, including a normal thyroid ultrasound.

DESIGN

A subset of the Hanford Thyroid Disease Study cohort was used to examine the TSH distribution in a population having no evidence of thyroid disease, seronegative thyroid autoantibodies, no history of thyroid medications, and a normal thyroid ultrasound. The shape of the TSH distribution was compared with the Gaussian and lognormal distributions.

SETTING

This study was performed in the general community.

PARTICIPANTS

Of 1861 Hanford Thyroid Disease Study participants with TSH measured by ELISA who also had thyroid peroxidase antibody measurements, 766 comprised the normal reference group 3 (NRG-3) with no evidence of thyroid disease, including no positive antibodies and normal thyroid ultrasound.

MAIN OUTCOME MEASURE

TSH was measured.

RESULTS

The TSH distribution in the NRG (NRG-3) was right skewed and followed an approximate lognormal distribution. The best estimates of the 97.5th percentile, the percentage above 2.5 microIU/ml, and the percentage above 3.0 microIU/ml for TSH by 3rd generation immunochemiluminometric assay are 4.1 microIU/ml, 20% and 10.2%, respectively.

CONCLUSION

These results indicate that the TSH reference range should be narrowed and support a value of approximately 4.0 as the upper-reference limit.

Hypothesis testing, statistical power, and confidence limits in the presence of epistemic uncertainty

Hypothesis testing, statistical power, and confidence limits are concepts from classical statistics that require data from observations. In some important recent applications some of the data are not observational but are reconstructed by computer models. There is generally epistemic uncertainty in model formulations, as well as in parameter and input values. The resulting epistemic uncertainty of the reconstructed data is determined by an uncertainty analysis and is expressed by subjective probability distributions. Sometimes only the mean or median values of the distributions are used in the concepts mentioned above, which hides the uncertainty of the data thereby rendering misleading results. Misleading results are also obtained if the epistemic uncertainty of the data is combined incorrectly with the stochastic variability of the outcome of the actual random complex concerned. This paper argues that an uncertainty analysis of the application of classical statistical concepts is essentially the correct way of dealing with the epistemic uncertainty of the data. A practical example serves as an illustration.

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.

Some statistical implications of dose uncertainty in radiation dose-response analyses

Statistical dose-response analyses in radiation epidemiology can produce misleading results if they fail to account for radiation dose uncertainties. While dosimetries may differ substantially depending on the ways in which the subjects were exposed, the statistical problems typically involve a predominantly linear dose-response curve, multiple sources of uncertainty, and uncertainty magnitudes that are best characterized as proportional rather than additive. We discuss some basic statistical issues in this setting, including the bias and shape distortion induced by classical and Berkson uncertainties, the effect of uncertain dose-prediction model parameters on estimated dose-response curves, and some notes on statistical methods for dose-response estimation in the presence of radiation dose uncertainties.

Cancer mortality among populations residing in counties near the Hanford site, 1950-2000

A descriptive epidemiologic study of cancer mortality among residents of counties near the Hanford nuclear facility site in Richland, Washington, was conducted. Between 1944 and 1957, radioactive 131I was released into the environment from the Hanford site. Cancer mortality from 1950 through 2000 was evaluated in four counties with the highest estimated exposure to 131I and compared with the cancer mortality experience in five demographically similar counties in Washington State with minimal 131I exposure. Overall, cancer rates in the study counties were slightly below those in the comparison counties [relative risk (RR) 0.95; 95% confidence interval (CI) 0.93-0.97], due mainly to a low risk for lung cancer (RR 0.89; 95% CI 0.85-0.93). Thyroid cancer (n=33; RR 0.84; 95% CI 0.56-1.26), female breast cancer (n=1,233; RR 0.99; 95% CI 0.92-1.06), leukemia other than chronic lymphocytic leukemia (n=492; RR 0.95; 95% CI 0.85-1.06), and childhood leukemia (n=71; RR=1.06; 95% CI 0.78-1.43) were not significantly increased in the exposed counties. Furthermore, there was no evidence that the cancer death rates over time differed between study and comparison counties. Patterns over time of thyroid cancer in particular were similar for exposure and comparison counties. Although based on a geographic correlation design, these data suggest that living near the Hanford site has not increased cancer rates.

2004 update of dosimetry for the Utah Thyroid Cohort Study

In the 1980s, individual thyroid doses and uncertainties were estimated for members of a cohort of children identified in 1965 in Utah and Nevada who had potentially been exposed to fallout from the Nevada Test Site. That reconstruction represented the first comprehensive assessment of doses received by the cohort and was the first large effort to assess the uncertainty of dose on an individual person basis. The data on dose and thyroid disease prevalence during different periods were subsequently used in an analysis to determine risks of radiogenic thyroid disease. This cohort has received periodic medical follow-up to observe changes in disease frequency and to reassess the previously reported radiation-related risks, most recently after a Congressional mandate in 1998. In a recent effort to restore the databases and computer codes used to estimate doses in the 1980s, various deficiencies were found in the estimated doses due to improperly operating computer codes, corruption of secondary data files, and lack of quality control procedures. From 2001 through 2004, the dosimetry system was restored and corrected and all doses were recalculated. In addition, two parameter values were updated. While the mean of all doses has not changed significantly, many individual doses have changed by more than an order of magnitude.

Thyroid ultrasound abnormalities in persons exposed during childhood to 131I from the Hanford nuclear site

Approximately 740,000 Ci of 131I were released into the atmosphere from the Hanford Nuclear Site in Washington State during 1944-1957. The Hanford Thyroid Disease Study (HTDS), conducted to determine if thyroid disease is increased among persons exposed as children to that 131I, also investigated whether thyroid ultrasound (US) abnormalities might be increased. The HTDS cohort (n = 5199) was selected from 1940-1946 births to mothers with usual residence in seven Washington counties. Of these, 4350 were located alive, 3447 attended HTDS clinics (1992-1997), and 3440 (1747 females) had evaluable clinical results and sufficient data to characterize their Hanford 131I exposures. US abnormalities were observed in 55.5% of women and 37.4% of men. Thyroid radiation doses from Hanford 131I, which could be estimated for 3191 evaluable participants, ranged from 0.0029 to 2823 mGy (mean, 174 mGy). Estimated dose was not significantly associated with the prevalence of any US abnormality (p = 0.21), US nodules with maximum dimension 5 mm or more (p = 0.64), or average number of US nodules per person (p = 0.80 for nodules with maximum dimension 5 mm or more). These results remained unchanged after accounting for factors that might confound or modify dose-response relationships and for uncertainty of the dose estimates. This study does not support the hypothesis that 131I exposure at Hanford's dose levels and dose rates during infancy and childhood increases the prevalence of adult thyroid US abnormalities.