Lifetime radiation risk of stochastic effects – prospective evaluation for space flight or medicine. (December 2020)

• Record Type: Journal Article
• Authors: Ulanowski, A.; Kaiser, J.C.; Schneider, U.; Walsh, L.
• Is Part Of: Annals of the ICRP. Volume 49(2020)Supplement 1
• Page Start: 200
• Page End: 212
• Publication Date: 2020-12
• Subjects: Radiation exposure; Detrimental effects; Time-integrated risk; Medical radiation exposure; Radiation exposure in space; Radiation -- Safety measures -- Periodicals; Radiation -- Physiological effect -- Periodicals; Radiation -- Toxicology -- Periodicals; Periodicals; 612.01448
• DOI: 10.1177/0146645320956517
• Languages: English
• ISSNs: 0146-6453

Abstract

The concept of lifetime radiation risk of stochastic detrimental health outcomes is important in contemporary radiation protection, being used either to calculate detriment-weighted effective dose or to express risks following radiation accidents or medical uses of radiation. The conventionally applied time-integrated risks of radiation exposure are computed using average values of current population and health statistical data that need to be projected far into the future. By definition, the lifetime attributable risk (AR) is an approximation to more general lifetime risk quantities and is only valid for exposures under 1 Gy. The more general quantities, such as excess lifetime risk (ELR) and risk of exposure-induced cancer, are free of dose range constraints, but rely on assumptions concerning the unknown total radiation effect on demographic and health statistical data, and are more computationally complex than AR. Consideration of highly uncertain competing risks for other radiation-attributed outcomes are required in appropriate assessments of time-integrated risks of specific outcomes following high-dose (>1 Gy) exposures, causing non-linear dose responses in the resulting ELR estimate. Being based on the current population and health statistical data, the conventionally applied time-integrated risks of radiation exposure are: (i) not well suited for projections many years into the future because of the large uncertainties in future secular trends in the population-specific disease rates; and (ii) not optimal for application to atypical groups of exposed persons not well represented by the general population. Specifically, medical patients are atypical in this respect because their prospective risks depend strongly on the original diagnosis, the treatment modality, general cure rates, individual radiation sensitivity, and genetic predisposition. Another situation challenging the application of conventional risk quantities is a projection of occupational radiation risks associated with space flight, both due to higher radiation doses and astronauts' generally excellent health condition due to pre-selection, training, and intensive medical screening. An alternative quantity, named 'radiation-attributed decrease of survival' (RADS), known in past general statistical literature as 'cumulative risk', is recommended here for applications in space and medicine to represent the cumulative radiation risk conditional on survival until a certain age. RADS is only based on the radiation-attributed hazard rendering an insensitivity to competing risks or projections of current population statistics far into the future. Therefore, RADS is highly suitable for assessing semi-personalised radiation risks after radiation exposures from space missions or medical applications of radiation.