Impact of considering non-occupational radiation exposure on the association between occupational dose and solid cancer among French nuclear workers

Monte Carlo modelling of cyclotron and radioisotope center (CYRIC) at Tohoku University: a radiation protection study

Protection against ionizing radiations is important in laboratories with radioactive materials and high energy cyclotron beams. The Cyclotron and Radioisotope Center (CYRIC) located in Tohoku University in Miyagi prefecture, Japan and is a well-known nuclear science laboratory with cyclotron beams and substantial number of high activity radioactive materials. Considering this, it is important to perform complete radiation transport computations to ensure the safety of non-occupational and occupational workers. In the present work, we have developed a complete 3-dimensional model of the main cyclotron building and radiation labs using Monte Carlo method. We have found that the dispersed photons and neutrons inside and in the surrounding of the CYRIC building pose no significant risk to occupational and non-occupational workers. The present work and the developed models would be useful in the field of radiation protection.

Strengths and Weaknesses of Dosimetry Used in Studies of Low-Dose Radiation Exposure and Cancer

BACKGROUND

A monograph systematically evaluating recent evidence on the dose-response relationship between low-dose ionizing radiation exposure and cancer risk required a critical appraisal of dosimetry methods in 26 potentially informative studies.

METHODS

The relevant literature included studies published in 2006-2017. Studies comprised case-control and cohort designs examining populations predominantly exposed to sparsely ionizing radiation, mostly from external sources, resulting in average doses of no more than 100 mGy. At least two dosimetrists reviewed each study and appraised the strengths and weaknesses of the dosimetry systems used, including assessment of sources and effects of dose estimation error. An overarching concern was whether dose error might cause the spurious appearance of a dose-response where none was present.

RESULTS

The review included 8 environmental, 4 medical, and 14 occupational studies that varied in properties relative to evaluation criteria. Treatment of dose estimation error also varied among studies, although few conducted a comprehensive evaluation. Six studies appeared to have known or suspected biases in dose estimates. The potential for these biases to cause a spurious dose-response association was constrained to three case-control studies that relied extensively on information gathered in interviews conducted after case ascertainment.

CONCLUSIONS

The potential for spurious dose-response associations from dose information appeared limited to case-control studies vulnerable to recall errors that may be differential by case status. Otherwise, risk estimates appeared reasonably free of a substantial bias from dose estimation error. Future studies would benefit from a comprehensive evaluation of dose estimation errors, including methods accounting for their potential effects on dose-response associations.

Evaluation of Confounding and Selection Bias in Epidemiological Studies of Populations Exposed to Low-Dose, High-Energy Photon Radiation

BACKGROUND

Low-dose, penetrating photon radiation exposure is ubiquitous, yet our understanding of cancer risk at low doses and dose rates derives mainly from high-dose studies. Although a large number of low-dose cancer studies have been recently published, concern exists about the potential for confounding to distort findings. The aim of this study was to describe and assess the likely impact of confounding and selection bias within the context of a systematic review.

METHODS

We summarized confounding control methods for 26 studies published from 2006 to 2017 by exposure setting (environmental, medical, or occupational) and identified confounders of potential concern. We used information from these and related studies to assess evidence for confounding and selection bias. For factors in which direct or indirect evidence of confounding was lacking for certain studies, we used a theoretical adjustment to determine whether uncontrolled confounding was likely to have affected the results.

RESULTS

For medical studies of childhood cancers, confounding by indication (CBI) was the main concern. Lifestyle-related factors were of primary concern for environmental and medical studies of adult cancers and for occupational studies. For occupational studies, other workplace exposures and healthy worker survivor bias were additionally of interest. For most of these factors, however, review of the direct and indirect evidence suggested that confounding was minimal. One study showed evidence of selection bias, and three occupational studies did not adjust for lifestyle or healthy worker survivor bias correlates. Theoretical adjustment for three factors (smoking and asbestos in occupational studies and CBI in childhood cancer studies) demonstrated that these were unlikely to explain positive study findings due to the rarity of exposure (eg, CBI) or the relatively weak association with the outcome (eg, smoking or asbestos and all cancers).

CONCLUSION

Confounding and selection bias are unlikely to explain the findings from most low-dose radiation epidemiology studies.

UNIVERSAL RADIATION PROTECTION SYSTEM (URPS); A NATURAL GLOBAL STANDARDISED TREND FOR HUMAN EXPOSURE CONTROL IN 21st CENTURY

In order to address the many deficiencies with current radiological protection system worldwide, this paper proposes a new Universal Radiation Protection System (URPS) Hypothesis with novel philosophy, concepts and methodologies of applying principles of equal human health-effect risks of an individual per unit radiation dose either from environmental natural background (NBG) or man-made sources; a 'standardised integrated dose system' for integrating all individual doses with emphasis on national NBG doses; considering worker as a member of public; and a 'cause-effect conservation principle' for epidemiology risk estimation. The URPS also a radiation hypothesises fractionation weighting factors (WF); a 'URPS Model' for bridging 'linear no-threshold and hormesis models'; example dose limit for workers; as well as new terms and definitions. State-of-the-art developments on URPS hypothesis are presented and discussed with simple global natural trends for standardised human exposure control in order to protect workers, patients, public and environment by standardised methods independent of source and country of origin in the 21st century.