An Approach to Evaluating Bias and Uncertainty in Estimates of External Dose Obtained from Personal Dosimeters

Abstract

This paper describes an approach to quantifying errors in recorded estimates of external radiation dose obtained from personal dosimeters and applies the approach to dose estimates of workers at the Hanford site. Because a major objective of this evaluation is to provide the information needed for adjusting epidemiologic dose-response analyses of worker data for errors in dose estimates, the paper addresses the extent that errors for different workers are correlated, focuses on recorded doses as estimates of organ doses, and focuses on recorded doses as estimates of organ doses, and gives consideration to both annual and cumulative doses. The evaluation emphasizes errors resulting from the fact that dosimeters are limited in their ability to respond accurately to all radiation energies to which workers are exposed or to radiation coming from all directions. For each of several sources of error, systematic bias factors are estimated for two energy ranges (100--300 keV and 300--1,000 keV), two geometries (anterior-posterior and rotational), and four calendar year periods. These are then combined using information provided by health physicists on energies and geometries in Hanford exposure environments. Except for the period before 1958, deep dose, the objective of modern dosimetry systems, was found to be fairly accurately estimated. Lung dose was found to be overestimated by about 10%, and bone marrow dose was found to be overestimated by about 50%. However, many aspects of this evaluation relied heavily on subjective judgments, and, thus, these factors are subject to considerable uncertainty. Estimates of uncertainty in the bias factors and uncertainty reflecting random error are provided.

Missing annual external radiation dosimetry data among Hanford workers

“…Evaluations of the available annual external dosimetry data are important for interpretation of these studies, and for design of subsequent analyses (Cardis and Esteve, 1991) . Previous evaluations of the Hanford external dosimetry data have given attention to potential underestimated doses due to dosimetry techniques, the nature of exposure (e.g., the angle of exposure, the contribution of neutron, photon, Xray, and tritium doses ) , and recording practices at the facility ( Gilbert, 1990;Gilbert et al, 1996 ). Missing data, which are a more generic concern in occupational epidemiology studies, have been a subject of less discussion.…”

The effect of censoring on cancer risk estimates based on the Canadian National Dose Registry of occupational radiation exposure

“…To explore the degree of overestimation, we conducted a simulation study in which both actual doses and reported doses are known, so that the effect of censoring can be evaluated. Techniques proposed by Inskip et al (1987), Gilbert et al (1996), Mitchell et al (1997), and Xue and Shore (2003) for correcting censored measurements depend on knowledge about individual recorded doses. Since only annual cumulative doses are available for subjects in the NDR, such methods cannot be applied in our case.…”

“…In particular, the dosimeter measurement itself is a proxy for the internal exposure of relevant organs to ionizing radiation. A comprehensive discussion of bias and uncertainty associated with using personal dosimeters to estimate cumulative exposure to radiation can be found in Gilbert et al (1996).…”

“…Although statistical methods for addressing censoring of radiation exposure data have been proposed by Gilbert et al (1996), Mitchell et al (1997) and Xue and Shore (2003), a formal analysis of the effects of censoring in large-scale studies of occupational radiation carcinogenesis has not been reported to date. The purpose of this paper is to investigate the effect of censoring of occupational radiation exposure measurements on cancer risk estimates derived from the NDR of Canada.…”

“…In particular, the dosimeter measurement itself is a proxy for the internal exposure of relevant organs to ionizing radiation. A comprehensive discussion of bias and uncertainty associated with using personal dosimeters to estimate cumulative exposure to radiation can be found in Gilbert et al (1996).Although statistical methods for addressing censoring of radiation exposure data have been proposed by Gilbert et al (1996), Mitchell et al (1997) and Xue and Shore (2003), a formal analysis of the effects of censoring in large-scale studies of occupational radiation carcinogenesis has not been reported to date. The purpose of this paper is to investigate the effect of censoring of occupational radiation exposure measurements on cancer risk estimates derived from the NDR of Canada.…”