Nuclear epidemiologic studies and the estimation of DREF

Abstract

Purpose: Estimating cancer risks for continuous radiation exposures based upon data from acute exposures has been an important public health problem. A dose and dose rate effectiveness factor (DDREF) is typically used to estimate cancer risks for chronic exposures based upon risk estimates from acute exposures. A value of 2 for a DDREF has most often been used as proposed by the ICRP in ICRP60; however, an influential analysis of several cohorts concluded that there is no risk difference between acute and chronic exposures. It is the purpose of this article to analyze the recent nuclear worker studies and estimate the dose rate effectiveness factor, DREF, for solid cancers.

Materials and methods: Twelve mortality studies were identified each with at least 100 cancer deaths and a meta-analysis was then carried out using their individual ratio of low dose rate cancer effect (LDR) to the corresponding high dose rate effect from the A-bomb cohort (LSS). The ratio is denoted by Q and its reciprocal is then an estimate of the DREF.

Results: The result was Q= 0.36 (95% CI = 0.11, 0.60) and DREF = 2.63 (95% confidence interval [CI] = 1.61, 7.14). Clearly, this estimate is more consistent with a DREF of 2 than with a DREF of 1. The difficulty with the estimate Q = 0.36 is that it is driven by only two large and dissimilar worker studies, the INWORKS study (q₁ = 1.14) and the Mayak worker cohort (q₃ = 0.30). The higher exposures for these nuclear workers were often in the early years (e.g. before 1960) with exposures from neutrons and internal emitters that are not included in the risk analyses resulting in likely overestimation of cancer effects per dose which would increase the estimate of the DREF. The Mayak study did, however, adjust for plutonium exposures. Finally, consideration is given to other cohort studies where DREF values may possibly be determined, such as the environmental exposures to the Techa River area residents and the Chernobyl cleanup workers as well as medical X-ray workers. Although dissimilar an overall meta-analysis yielded a Q = 0.45 (95% CI = 0.24, 0.66).

Conclusions: It is concluded that the best estimate of a DREF is still about 2. However, because of the various problems with the epidemiology studies, especially their dosimetry, it is concluded that a DREF of about 2 should be accepted with considerable caution since it is driven solely by the Mayak study.

Keywords:

• Dose rate effectiveness factor
• meta-analysis
• occupational radiation studies

Note

Acknowledgments

This report makes use of data obtained from the Radiation Effects Research Foundation (RERF), Hiroshima and Nagasaki, Japan. RERF is a private, non-profit foundation funded by the Japanese Ministry of Health, Labor and Welfare and the USA. Department of Energy, the latter through the National Academy of Sciences. The conclusions in this report are those of the author and do not necessarily reflect the scientific judgment of RERF or its funding agencies. The author wishes to especially thank Roy Shore for his many helpful comments as well as those by the referees.

Disclosure statement

The author reports no conflicts of interest. The author alone is responsible for the content and writing of this article.

Notes

1 Dose-rate effectiveness factor (DREF). The factor by which the effect caused by a specific type of radiation changes at low doses or low dose rates (protracted or fractionated delivery of dose) as compared to high doses delivered at high (or acute) dose rates. Dose and dose-rate effectiveness factor (DDREF). A judged factor by which the radiation effect, per unit of dose, caused by a given high or moderate dose of radiation received at high dose rates is reduced when doses are low or are received at low dose rates.

Additional information

Funding

This work was supported by the Electric Power Research Institute located in Palo Alto, CA, USA.

Notes on contributors

David G. Hoel

David G. Hoel, PhD, is a Distinguished University Professor in the Department of Public Health Sciences of the Medical University of South Carolina , Charleston, South Carolina, USA.