The 15-Country Collaborative Study of Cancer Risk among Radiation Workers in the Nuclear Industry: Study of Errors in Dosimetry

Abstract

To provide direct estimates of cancer risk after low-dose protracted exposure to ionizing radiation, a large-scale epidemiological study of nuclear industry workers was conducted in 15 countries. As part of this study, identification and quantification of errors in historical recorded doses was conducted based on a review of dosimetric practices and technologies in participating facilities. The main sources of errors on doses from "high-energy" photons (100-3000 keV) were identified as the response of dosimeters in workplace exposure conditions and historical calibration practices. Errors related to dosimetry technology and radiation fields were quantified to derive period- and facility-specific estimates of bias and uncertainties in recorded doses. This was based on (1) an evaluation of predominant workplace radiation from measurement studies and dosimetry expert assessment and (2) an estimation of the energy and geometry response of dosimeters used historically in study facilities. Coefficients were derived to convert recorded doses to H(p) (10) and organ dose, taking into account different aspects of the calibration procedures. A parametric, lognormal error structure model was developed to describe errors in doses as a function of facility and time period. Doses from other radiation types, particularly neutrons and radionuclide intake, could not be adequately reconstructed in the framework of the 15-Country Study. Workers with substantial doses from these radiation types were therefore identified and excluded from analyses. Doses from "lower-energy" photons (<100 keV) and from "higher-energy" photons (>3 MeV) were estimated to be small.

Errors and Uncertainties in Dose Reconstruction for Radiation Effects Research

“…It will be necessary to go beyond this unbiased assumption of Stram and Kopecky (2003), as was shown in the thought experiments above for group doses with residual bias. Thierry-Chef et al (2007) give "intrinsic sampling variation in measurements inherent to different types of dosimeters, referred to as laboratory error" as an example of "errors that are independent from person to person, and are thus 'unshared.' For these errors, the 'classical error' model applies, in which the estimated values of the input date are assumed to be distributed around the true values of the input data for each subject."…”

“…For example, in Table 7 of Thierry-Chef et al (2007), the largest bias and uncertainty values are for Facility-5, 1943Facility-5, -1952 . A numerical example using larger S G s is shown in Appendix B.…”

“…Different dosimeter technologies will each be associated with one or more Berkson groupings of uncertainty. In works like that of Thierry-Chef et al (2007), there are many categories of Berkson uncertainty, but it isn't clear how the memberships and nature of these categories change over time.…”

“…When such corrections are lognormally distributed and multiplicative, as in Thierry-Chef et al (2007) or Masse et al (1989), care must be used in propagating uncertainty.…”

Cellular radiosensitivity: How much better do we understand it?

“…GI syndrome in manifested by dehydration, diarrhea, infection and in severe cases septic shock and death (Potten 1990 The nature of the lesions in DNA and other macromolecules are relatively well described; survival dose-response curves have been thoroughly analysed with different cell types; the relationship between DNA damage and mutation induction is well established and the carcinogenicity of radiation exposure is well accepted (Teoule 1987, Miller 1995, Wolf 1992. What remains controversial is the risk from exposure to low dose radiation and the shape of the kinetic curves below the range of accidental exposure where effects are more evident (Wall et al 2006, Thierry-Chef et al 2007, Strzelczyk et al 2007 Not surprisingly a greater appreciation of the teratogenic, mutagenic and carcinogenic effects of radiation brought with it the realisation that radiation might be 4 employed as a beneficial tool. The advent of the linear accelerator together with computer-assisted tomographic/magnetic resonance imaging-based computerised treatment planning increased the quality and precision for use of radiotherapy in the treatment of cancer (Goffman et al 1990).…”