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Title: Shared dosimetry error in epidemiological dose-response analyses

Journal Article · · PLoS ONE
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [9];  [10]
  1. Univ. of Southern California, Los Angeles, CA (United States)
  2. Hirosoft International, Eureka, CA (United States)
  3. Southern Urals Biophysics Institute, Ozersk (Russia)
  4. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  5. Fred Hutchinson Cancer Center, Seattle, WA (United States)
  6. Vanderbilt Univ., Nashville, TN (United States)
  7. U.S. Dept. of Energy, New York, NY (United States)
  8. Risk Assessment Corporation, Neeses, SC (United States)
  9. National Cancer Institute, Rockville, MD (United States)
  10. Leibniz Institute for Prevention Research and Epidemiology (Germany)
+ Show Author Affiliations

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.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
HS0000091; SC0008944
OSTI ID:
1193633
Journal Information:
PLoS ONE, Vol. 10, Issue 3; ISSN 1932-6203
Publisher:
Public Library of ScienceCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 31 works
Citation information provided by
Web of Science

References (30)

Radiation Doses from Hanford Site Releases to the Atmosphere and the Columbia River journal January 1996
Thyroid Cancer Study among Ukrainian Children Exposed to Radiation after the Chornobyl Accident: Improved Estimates of the Thyroid Doses to the Cohort Members journal January 2014
Thyroid cancer in Ukraine after the Chernobyl accident (in the framework of the Ukraine–US Thyroid Project) journal March 2012
Impact of Uncertainties in Exposure Assessment on Estimates of Thyroid Cancer Risk among Ukrainian Children and Adolescents Exposed from the Chernobyl Accident journal January 2014
Estimating uncertainty on internal dose assessments journal June 2007
Lung Cancer Risks from Plutonium: An Updated Analysis of Data from the Mayak Worker Cohort journal February 2013
Power and Uncertainty Analysis of Epidemiological Studies of Radiation-Related Disease Risk in which Dose Estimates are Based on a Complex Dosimetry System: Some Observations journal October 2003
Exposure Measurement Error: Influence on Exposure-Disease Relationships and Methods of Correction journal May 1993
The Effect of Misclassification in the Presence of Covariates journal October 1980
An Estimate of the Magnitude of Random Errors in the DS86 Dosimetry from Data on Chromosome Aberrations and Severe Epilation journal November 1991
The Observed Relationship between the Occurrence of Acute Radiation Effects and Leukemia Mortality among A-Bomb Survivors journal February 1991
Relationship between Cataracts and Epilation in Atomic Bomb Survivors journal October 1995
Absence of evidence for differences in the dose-response for cancer and non-cancer endpoints by acute injury status in the Japanese atomic-bomb survivors journal January 2002
Adjusting for covariate errors with nonparametric assessment of the true covariate distribution journal December 2004
Are there Two Regressions? journal June 1950
Correction of Logistic Regression Relative Risk Estimates and Confidence Intervals for Random Within-Person Measurement Error journal December 1992
Simulation-Extrapolation: The Measurement Error Jackknife journal December 1995
The Utah Leukemia Case-Control Study: Dosimetry Methodology and Results journal January 1995
The Utah Thyroid Cohort Study: Analysis of the Dosimetry Results journal January 1995
Estimation of Thyroid Radiation Doses for the Hanford Thyroid Disease Study: Results and Implications for Statistical Power of the Epidemiological Analyses journal January 2004
The Analysis of Rates and of Survivorship Using Log-Linear Models journal June 1980
Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques journal June 1981
Covariate measurement errors and parameter estimation in a failure time regression model journal January 1982
Measurement error in the explanatory variable of a binary regression: Regression calibration and integrated conditional likelihood in studies of residential radon and lung cancer journal January 2008
A Monte Carlo Maximum Likelihood Method for Estimating Uncertainty Arising from Shared Errors in Exposures in Epidemiological Studies of Nuclear Workers journal December 2007
Regression calibration method for correcting measurement-error bias in nutritional epidemiology journal April 1997
An Approach to Dose Reconstruction for the Urals Population journal July 1996
Semi-Automated Sensitivity Analysis to Assess Systematic Errors in Observational Data journal January 2003
Military Participants at U.S. Atmospheric Nuclear Weapons Testing—Methodology for Estimating Dose and Uncertainty journal May 2014
Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach journal March 1973

Cited By (7)

Dosimetry and uncertainty approaches for the million person study of low-dose radiation health effects: overview of the recommendations in NCRP Report No. 178 journal November 2018
The Million Person Study, whence it came and why journal April 2019
Implications of recent epidemiologic studies for the linear nonthreshold model and radiation protection journal August 2018
Shared and unshared exposure measurement error in occupational cohort studies and their effects on statistical inference in proportional hazards models journal February 2018
Assessment of thyroid cancer risk associated with radiation dose from personal diagnostic examinations in a cohort study of US radiologic technologists, followed 1983–2014 journal May 2018
Impact of Uncertainties in Exposure Assessment on Thyroid Cancer Risk among Persons in Belarus Exposed as Children or Adolescents Due to the Chernobyl Accident journal October 2015
Correction of confidence intervals in excess relative risk models using Monte Carlo dosimetry systems with shared errors journal April 2017

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61 RADIATION PROTECTION AND DOSIMETRY