Thyroid Doses and Risk of Thyroid Cancer from Exposure to I-131 from the Nevada Test Site

This report provides a set of look-up tables of representative thyroid doses and risks of thyroid cancer for individuals exposed to I-131 in fallout from nuclear weapons testing at the Nevada Test Site. These tables are intended to be used by people who do not have access to a computer. The look-up tables contain estimates of doses and risks for eight representative birth cohorts and sixty-seven locations in eight regions around the continental United States. They were obtained using a slightly modified version of the NCI’s online dose and risk calculator for exposures to I-131 in NTS fallout. The look-up tables provided here do not cover all possible exposure situations, but they can be used to estimate the general magnitude of a person’s thyroid dose and risk of thyroid cancer from NTS fallout according to birth cohort, gender, given residence history, and given amount and type of milk consumed. This research was completed money allocated during Round 2 of the Citizens’ Monitoring and Technical Assessment Fund (MTA Fund). Clark University was named conservator of these works. If you have any questions or concerns please contact us at [email protected]://commons.clarku.edu/radiochem/1000/thumbnail.jp

Estimation of Heights and Body Masses of Tuberculosis Patients in the Canadian Fluoroscopy Cohort Study for Use in Individual Dosimetry.

AbstractThis paper documents the estimation of mean heights and body masses, by age and sex, used in development of organ-specific dose conversion coefficients for external radiation for a historical cohort of about 64,000 patients from the Canadian Fluoroscopy Cohort Study. Patients were exposed to repeated fluoroscopy and chest radiography examinations in the course of treatment for tuberculosis in residential medical facilities throughout Canada between 1930 and 1969. Using Canadian national survey data and extensive literature review, mean heights and masses were obtained for the White population of Canada during the time period of interest, and the differences in mean body mass between tuberculosis patients and the general population were estimated. Results in terms of mean height and body mass of Canadian tuberculosis patients, with uncertainties, are reported for selected age groups (children of ages 1, 5, 10, and 15 y and adults age 20+) and for both sexes. Use of estimated average heights and body masses by age and sex permits the adjustment of computerized phantoms for body mass for a given age, thereby increasing the relevance of the organ-specific dose conversion coefficients for the cohort and improving the accuracy of the resulting estimated organ doses

Estimation of Heights and Body Masses of Tuberculosis Patients in the Canadian Fluoroscopy Cohort Study for Use in Individual Dosimetry.

AbstractThis paper documents the estimation of mean heights and body masses, by age and sex, used in development of organ-specific dose conversion coefficients for external radiation for a historical cohort of about 64,000 patients from the Canadian Fluoroscopy Cohort Study. Patients were exposed to repeated fluoroscopy and chest radiography examinations in the course of treatment for tuberculosis in residential medical facilities throughout Canada between 1930 and 1969. Using Canadian national survey data and extensive literature review, mean heights and masses were obtained for the White population of Canada during the time period of interest, and the differences in mean body mass between tuberculosis patients and the general population were estimated. Results in terms of mean height and body mass of Canadian tuberculosis patients, with uncertainties, are reported for selected age groups (children of ages 1, 5, 10, and 15 y and adults age 20+) and for both sexes. Use of estimated average heights and body masses by age and sex permits the adjustment of computerized phantoms for body mass for a given age, thereby increasing the relevance of the organ-specific dose conversion coefficients for the cohort and improving the accuracy of the resulting estimated organ doses

Organ Doses from Chest Radiographs in Tuberculosis Patients in Canada and Their Uncertainties in Periods from 1930 to 1969.

This paper describes a study to estimate absorbed doses to various organs from film-based chest radiographs and their uncertainties in the periods 1930 to 1948, 1949 to 1955, and 1956 to 1969. Estimated organ doses will be used in new analyses of risks of cancer and other diseases in tuberculosis patients in Canada who had chest fluoroscopic and radiographic examinations in those periods. In this paper, doses to lungs, female breast, active bone marrow, and heart from a single chest radiograph in adults and children of ages 1, 5, 10, and 15 y in the Canadian cohort and their uncertainties are estimated using (1) data on the tube voltage (kV), total filtration (mm Al), tube-current exposure-time product (mA s), and tube output (mR [mA s]) in each period; (2) assumptions about patient orientation, distance from the source to the skin of a patient, and film size; and (3) new calculations of sex- and age-specific organ dose conversion coefficients (organ doses per dose in air at skin entrance). Variations in estimated doses to each organ across the three periods are less than 20% in adults and up to about 30% at younger ages. Uncertainties in estimated organ doses are about a factor of 2 to 3 in adults and up to a factor of 4 at younger ages and are due mainly to uncertainties in the tube voltage and tube-current exposure-time product

Methods to account for uncertainties in exposure assessment in studies of environmental exposures.

BackgroundAccurate 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 textWe 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.ConclusionsIn 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

Methods to account for uncertainties in exposure assessment in studies of environmental exposures

Abstract 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