Lifetime Mortality Risk from Cancer and Circulatory Disease Predicted from the Japanese Atomic Bomb Survivor Life Span Study Data Taking Account of Dose Measurement Error

A Historical Survey of Key Epidemiological Studies of Ionizing Radiation Exposure

In this article we review the history of key epidemiological studies of populations exposed to ionizing radiation. We highlight historical and recent findings regarding radiation-associated risks for incidence and mortality of cancer and non-cancer outcomes with emphasis on study design and methods of exposure assessment and dose estimation along with brief consideration of sources of bias for a few of the more important studies. We examine the findings from the epidemiological studies of the Japanese atomic bomb survivors, persons exposed to radiation for diagnostic or therapeutic purposes, those exposed to environmental sources including Chornobyl and other reactor accidents, and occupationally exposed cohorts. We also summarize results of pooled studies. These summaries are necessarily brief, but we provide references to more detailed information. We discuss possible future directions of study, to include assessment of susceptible populations, and possible new populations, data sources, study designs and methods of analysis.

Recommendations on statistical approaches to account for dose uncertainties in radiation epidemiologic risk models

PURPOSE

Epidemiological studies of stochastic radiation health effects such as cancer, meant to estimate risks of the adverse effects as a function of radiation dose, depend largely on estimates of the radiation doses received by the exposed group under study. Those estimates are based on dosimetry that always has uncertainty, which often can be quite substantial. Studies that do not incorporate statistical methods to correct for dosimetric uncertainty may produce biased estimates of risk and incorrect confidence bounds on those estimates. This paper reviews commonly used statistical methods to correct radiation risk regressions for dosimetric uncertainty, with emphasis on some newer methods. We begin by describing the types of dose uncertainty that may occur, including those in which an uncertain value is shared by part or all of a cohort, and then demonstrate how these sources of uncertainty arise in radiation dosimetry. We briefly describe the effects of different types of dosimetric uncertainty on risk estimates, followed by a description of each method of adjusting for the uncertainty.

CONCLUSIONS

Each of the method has strengths and weaknesses, and some methods have limited applicability. We describe the types of uncertainty to which each method can be applied and its pros and cons. Finally, we provide summary recommendations and touch briefly on suggestions for further research.

Effects of confounding and effect-modifying lifestyle, environmental and medical factors on risk of radiation-associated cardiovascular disease

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death worldwide. It has been known for some considerable time that radiation is associated with excess risk of CVD. A recent systematic review of radiation and CVD highlighted substantial inter-study heterogeneity in effect, possibly a result of confounding or modifications of radiation effect by non-radiation factors, in particular by the major lifestyle/environmental/medical risk factors and latent period.

METHODS

We assessed effects of confounding by lifestyle/environmental/medical risk factors on radiation-associated CVD and investigated evidence for modifying effects of these variables on CVD radiation dose-response, using data assembled for a recent systematic review.

RESULTS

There are 43 epidemiologic studies which are informative on effects of adjustment for confounding or risk modifying factors on radiation-associated CVD. Of these 22 were studies of groups exposed to substantial doses of medical radiation for therapy or diagnosis. The remaining 21 studies were of groups exposed at much lower levels of dose and/or dose rate. Only four studies suggest substantial effects of adjustment for lifestyle/environmental/medical risk factors on radiation risk of CVD; however, there were also substantial uncertainties in the estimates in all of these studies. There are fewer suggestions of effects that modify the radiation dose response; only two studies, both at lower levels of dose, report the most serious level of modifying effect.

CONCLUSIONS

There are still large uncertainties about confounding factors or lifestyle/environmental/medical variables that may influence radiation-associated CVD, although indications are that there are not many studies in which there are substantial confounding effects of these risk factors.

A generalisation of the method of regression calibration and comparison with Bayesian and frequentist model averaging methods

For many cancer sites low-dose risks are not known and must be extrapolated from those observed in groups exposed at much higher levels of dose. Measurement error can substantially alter the dose-response shape and hence the extrapolated risk. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, there has been considerable attention paid to methods of dealing with shared errors, which are common in many datasets, and particularly important in occupational and environmental settings. In this paper we test Bayesian model averaging (BMA) and frequentist model averaging (FMA) methods, the first of these similar to the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, and both fairly recently proposed, against a very newly proposed modification of the regression calibration method, the extended regression calibration (ERC) method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. The quasi-2DMC with BMA method performs well when a linear model is assumed, but very poorly when a linear-quadratic model is assumed, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5% when the magnitude of shared Berkson error is large (50%). For the linear model the bias is generally under 10%. However, using a linear-quadratic model it produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. FMA performs as well as quasi-2DMC with BMA when a linear model is assumed, and generally much better with a linear-quadratic model, although the coverage probability for the quadratic coefficient is uniformly too high. However both linear and quadratic coefficients have pronounced upward bias, particularly when Berkson error is large. By comparison ERC yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the quasi-2DMC with BMA or FMA methods, particularly for the linear-quadratic model. The bias of the predicted relative risk at a variety of doses is generally smallest for ERC, and largest for the quasi-2DMC with BMA and FMA methods (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between ERC and the other two methods. In general ERC performs best in the scenarios presented, and should be the method of choice in situations where there may be substantial shared error, or suspected curvature in the dose response.

A generalisation of the method of regression calibration and comparison with Bayesian and frequentist model averaging methods

For many cancer sites low-dose risks are not known and must be extrapolated from those observed in groups exposed at much higher levels of dose. Measurement error can substantially alter the dose-response shape and hence the extrapolated risk. Recently, there has been considerable attention paid to methods of dealing with shared errors, which are particularly important in occupational and environmental settings. In this paper we test Bayesian model averaging (BMA) and frequentist model averaging (FMA) methods, the first of these similar to the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, and both fairly recently proposed, against a very newly proposed modification of the regression calibration method, the extended regression calibration (ERC) method. The quasi-2DMC+BMA method performs well when a linear model is assumed, but poorly when a linear-quadratic model is assumed. FMA performs as well as quasi-2DMC+BMA when a linear model is assumed, and generally much better with a linear-quadratic model, although the coverage probability for the quadratic coefficient is uniformly too high. ERC yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the quasi-2DMC+BMA or FMA methods, particularly for the linear-quadratic model. The bias of predicted relative risk at a variety of doses is generally smallest for ERC, and largest for quasi-2DMC+BMA and FMA, with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between ERC and the other two methods. In general ERC performs best in the scenarios presented, and should be the method of choice in situations where there may be substantial shared error, or suspected curvature in the dose response.

Assessing the impact of neutron relative biological effectiveness on all solid cancer mortality risks in the Japanese atomic bomb survivors

PURPOSE

Risk analyses, based on relative biological effectiveness (RBE) estimates for neutrons relative to gammas, were performed; and the change in the curvature of the risk to dose response with increasing neutron RBE was analyzed using all solid cancer mortality data from the Radiation Effect Research Foundation (RERF). Results were compared to those based on incidence data.

MATERIALS AND METHODS

This analysis is based on RERF mortality data with separate neutron and gamma doses for colon doses, from which organ averaged doses could be calculated. A model for risk ratio variation with RBE was developed.

RESULTS

The best estimate of the neutron RBE considering mortality data was 200 (95% confidence interval (CI): 50-1010) for colon dose using the weighted-dose approach and for organ averaged dose 110 (95% CI: 30-350). The ERR risk ratios for all solid cancers combined, for the best fitting neutron RBE estimate and the neutron RBE of 10 result in a ratio of 0.54 (95% CI: 0.17-0.85) for colon dose and 0.55 (95% CI: 0.18-0.87) for organ averaged dose. The risk to dose response curvature became significantly negative (concave down) with increasing RBE, at a neutron RBE of 170 using colon dose and at an RBE of 90 using organ averaged dose for males when fitting a linear-quadratic dose response. For females, the curvature decreased toward linearity with increasing neutron RBE and remained significantly positive until RBE of 80 and 40 using colon and organ averaged dose, respectively. For higher neutron RBEs, no significant conclusion could be drawn about the shape of the dose-response curve.

CONCLUSIONS

Application of neutron RBE values higher than 10 results in substantially reduced cancer mortality risk estimates and a significant reduction in curvature of the risk to dose responses for males. Using mortality data, the best fitting neutron RBE is much higher than when incidence data is used. The neutron RBE ranges covered by the overlap in the CIs from both the mortality and incidence analyses are 50-190 using colon dose and in all cases, the best fitting neutron RBE and lower 95% CI are higher than the value of 10 traditionally applied by the RERF. Therefore, it is recommended to consider uncertainties in neutron RBE values when calculating radiation risks and discussing the shape of dose responses using Japanese A-bomb survivors data.

A generalisation of the method of regression calibration and comparison with the Bayesian 2-dimensional Monte Carlo method

For many cancer sites it is necessary to assess risks from low-dose exposures via extrapolation from groups exposed at moderate and high levels of dose. Measurement error can substantially alter the shape of this relationship and hence the derived population risk estimates. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, much attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. In this paper we test a Bayesian model averaging method, the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, that has been fairly recently proposed against a very newly proposed modification of the regression calibration method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. We also compared both methods against standard regression calibration and Monte Carlo maximum likelihood. The Bayesian 2DMC method performs poorly, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5%, particularly when the magnitudes of classical and Berkson error are both moderate to large (20%-50%). The method also produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. By comparison the extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the Bayesian 2DMC and all other methods. The bias of the predicted relative risk at a variety of doses is generally smallest for extended regression calibration, and largest for the Bayesian 2DMC method (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between the other two methods.

Radiation exposure and leukaemia risk among cohorts of persons exposed to low and moderate doses of external ionising radiation in childhood

BACKGROUND

Many high-dose groups demonstrate increased leukaemia risks, with risk greatest following childhood exposure; risks at low/moderate doses are less clear.

METHODS

We conducted a pooled analysis of the major radiation-associated leukaemias (acute myeloid leukaemia (AML) with/without the inclusion of myelodysplastic syndrome (MDS), chronic myeloid leukaemia (CML), acute lymphoblastic leukaemia (ALL)) in ten childhood-exposed groups, including Japanese atomic bomb survivors, four therapeutically irradiated and five diagnostically exposed cohorts, a mixture of incidence and mortality data. Relative/absolute risk Poisson regression models were fitted.

RESULTS

Of 365 cases/deaths of leukaemias excluding chronic lymphocytic leukaemia, there were 272 AML/CML/ALL among 310,905 persons (7,641,362 person-years), with mean active bone marrow (ABM) dose of 0.11 Gy (range 0-5.95). We estimated significant (P < 0.005) linear excess relative risks/Gy (ERR/Gy) for: AML (n = 140) = 1.48 (95% CI 0.59-2.85), CML (n = 61) = 1.77 (95% CI 0.38-4.50), and ALL (n = 71) = 6.65 (95% CI 2.79-14.83). There is upward curvature in the dose response for ALL and AML over the full dose range, although at lower doses (<0.5 Gy) curvature for ALL is downwards.

DISCUSSION

We found increased ERR/Gy for all major types of radiation-associated leukaemia after childhood exposure to ABM doses that were predominantly (for 99%) <1 Gy, and consistent with our prior analysis focusing on <100 mGy.

A generalisation of the method of regression calibration

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose-response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient [Formula: see text] are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient [Formula: see text] are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for [Formula: see text] that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient [Formula: see text] are substantially upwardly biased.

A generalisation of the method of regression calibration

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose-response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient \(\alpha\) are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient \(\beta\) are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for \(\beta\) that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient \(\beta\) are substantially upwardly biased.

Sparing and enhancing dose protraction effects for radiation damage to the aorta of wild-type mice

PURPOSE

Our previous work indicated the greater magnitude of damage to the thoracic aorta at 6 months after starting 5 Gy irradiation in descending order of exposure to X-rays in 25 fractions > acute X-rays > acute γ-rays > X-rays in 100 fractions ≫ chronic γ-rays, in which the limitations of the study included a lack of data for fractionated γ-ray exposure. To better understand effects of dose protraction and radiation quality, the present study examined changes after exposure to γ-rays in 25 fractions, and compared its biological effectiveness with five other irradiation regimens.

MATERIALS AND METHODS

Male C57BL/6J mice received 5 Gy of 137Cs γ-rays delivered in 25 fractions spread over six weeks. At 6 months after starting irradiation, mice were subjected to echocardiography, followed by tissue sampling. The descending thoracic aorta underwent scanning electron microscopy, immunofluorescence staining and histochemical staining. The integrative analysis of multiple aortic endpoints was conducted for inter-regimen comparisons.

RESULTS

Exposure to γ-rays in 25 fractions induced vascular damage (evidenced by increases in endothelial detachment and vascular endothelial cell death, decreases in endothelial waviness, CD31, endothelial nitric oxide synthase and vascular endothelial cadherin), inflammation (evidenced by increases in tumor necrosis factor α, CD68 and F4/80) and fibrosis (evidenced by increases in transforming growth factor β1, alanine blue stain and intima-media thickness). The integrative analysis revealed biological effectiveness in descending order of exposure to X-rays in 25 fractions > acute X-rays > γ-rays in 25 fractions > acute γ-rays > X-rays in 100 fractions ≫ chronic γ-rays.

CONCLUSIONS

The results suggest that dose protraction effects on aortic damage depend on radiation quality, and are not a simple function of dose rate and the number of fractions.

Noncancer Effects of Ionizing Radiation Exposure on the Eye, the Circulatory System and beyond: Developments made since the 2011 ICRP Statement on Tissue Reactions

For radiation protection purposes, noncancer effects with a threshold-type dose-response relationship have been classified as tissue reactions (formerly called nonstochastic or deterministic effects), and equivalent dose limits aim to prevent occurrence of such tissue reactions. Accumulating evidence demonstrates increased risks for several late occurring noncancer effects at doses and dose rates much lower than previously considered. In 2011, the International Commission on Radiological Protection (ICRP) issued a statement on tissue reactions to recommend a threshold of 0.5 Gy to the lens of the eye for cataracts and to the heart and brain for diseases of the circulatory system (DCS), independent of dose rate. Literature published thereafter continues to provide updated knowledge. Increased risks for cataracts below 0.5 Gy have been reported in several cohorts (e.g., including in those receiving protracted or chronic exposures). A dose threshold for cataracts is less evident with longer follow-up, with limited evidence available for risk of cataract removal surgery. There is emerging evidence for risk of normal-tension glaucoma and diabetic retinopathy, but the long-held tenet that the lens represents among the most radiosensitive tissues in the eye and in the body seems to remain unchanged. For DCS, increased risks have been reported in various cohorts, but the existence or otherwise of a dose threshold is unclear. The level of risk is less uncertain at lower dose and lower dose rate, with the possibility that risk per unit dose is greater at lower doses and dose rates. Target organs and tissues for DCS are also unknown, but may include heart, large blood vessels and kidneys. Identification of potential factors (e.g., sex, age, lifestyle factors, coexposures, comorbidities, genetics and epigenetics) that may modify radiation risk of cataracts and DCS would be important. Other noncancer effects on the radar include neurological effects (e.g., Parkinson's disease, Alzheimer's disease and dementia) of which elevated risk has increasingly been reported. These late occurring noncancer effects tend to deviate from the definition of tissue reactions, necessitating more scientific developments to reconsider the radiation effect classification system and risk management. This paper gives an overview of historical developments made in ICRP prior to the 2011 statement and an update on relevant developments made since the 2011 ICRP statement.

Preleukemic Fusion Genes Induced via Ionizing Radiation

Although the prevalence of leukemia is increasing, the agents responsible for this increase are not definitely known. While ionizing radiation (IR) was classified as a group one carcinogen by the IARC, the IR-induced cancers, including leukemia, are indistinguishable from those that are caused by other factors, so the risk estimation relies on epidemiological data. Several epidemiological studies on atomic bomb survivors and persons undergoing IR exposure during medical investigations or radiotherapy showed an association between radiation and leukemia. IR is also known to induce chromosomal translocations. Specific chromosomal translocations resulting in preleukemic fusion genes (PFGs) are generally accepted to be the first hit in the onset of many leukemias. Several studies indicated that incidence of PFGs in healthy newborns is up to 100-times higher than childhood leukemia with the same chromosomal aberrations. Because of this fact, it has been suggested that PFGs are not able to induce leukemia alone, but secondary mutations are necessary. PFGs also have to occur in specific cell populations of hematopoetic stem cells with higher leukemogenic potential. In this review, we describe the connection between IR, PFGs, and cancer, focusing on recurrent PFGs where an association with IR has been established.

Ionising radiation and cardiovascular disease: systematic review and meta-analysis

OBJECTIVE

To systematically review and perform a meta-analysis of radiation associated risks of cardiovascular disease in all groups exposed to radiation with individual radiation dose estimates.

DESIGN

Systematic review and meta-analysis.

MAIN OUTCOME MEASURES

Excess relative risk per unit dose (Gy), estimated by restricted maximum likelihood methods.

DATA SOURCES

PubMed and Medline, Embase, Scopus, Web of Science Core collection databases.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Databases were searched on 6 October 2022, with no limits on date of publication or language. Animal studies and studies without an abstract were excluded.

RESULTS

The meta-analysis yielded 93 relevant studies. Relative risk per Gy increased for all cardiovascular disease (excess relative risk per Gy of 0.11 (95% confidence interval 0.08 to 0.14)) and for the four major subtypes of cardiovascular disease (ischaemic heart disease, other heart disease, cerebrovascular disease, all other cardiovascular disease). However, interstudy heterogeneity was noted (P<0.05 for all endpoints except for other heart disease), possibly resulting from interstudy variation in unmeasured confounders or effect modifiers, which is markedly reduced if attention is restricted to higher quality studies or those at moderate doses (<0.5 Gy) or low dose rates (<5 mGy/h). For ischaemic heart disease and all cardiovascular disease, risks were larger per unit dose for lower dose (inverse dose effect) and for fractionated exposures (inverse dose fractionation effect). Population based excess absolute risks are estimated for a number of national populations (Canada, England and Wales, France, Germany, Japan, USA) and range from 2.33% per Gy (95% confidence interval 1.69% to 2.98%) for England and Wales to 3.66% per Gy (2.65% to 4.68%) for Germany, largely reflecting the underlying rates of cardiovascular disease mortality in these populations. Estimated risk of mortality from cardiovascular disease are generally dominated by cerebrovascular disease (around 0.94-1.26% per Gy), with the next largest contribution from ischaemic heart disease (around 0.30-1.20% per Gy).

CONCLUSIONS

Results provide evidence supporting a causal association between radiation exposure and cardiovascular disease at high dose, and to a lesser extent at low dose, with some indications of differences in risk between acute and chronic exposures, which require further investigation. The observed heterogeneity complicates a causal interpretation of these findings, although this heterogeneity is much reduced if only higher quality studies or those at moderate doses or low dose rates are considered. Studies are needed to assess in more detail modifications of radiation effect by lifestyle and medical risk factors.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020202036.

Reconstructed lung doses for the million person study cohort of 26,650 Tennessee Eastman corporation workers employed between 1942 and 1947

Tennessee Eastman Corporation workers were exposed to uranium dust resulting in high-linear energy transfer (LET) irradiation to lung tissue. In this work, radiation lung doses were reconstructed for 26 650 men and women working at the plant between 1942 and 1947. Site air monitoring data of uranium concentrations and payroll records were used to determine the daily inhaled activities and annualized lung doses. Variations in the activity median aerodynamic diameter of the uranium dust, the solubility of particulate matter in the lungs and the sex-specific breathing rate were investigated as part of a sensitivity analysis. Male and female mean lung doses of 18.9 and 32.7 mGy, respectively, from high-LET alpha irradiation, and there was general agreement with evaluations from previously published epidemiological studies. Annual lung dose estimates and sensitivity analysis for the 26 650 workers in the TEC cohort have been archived on the United States Department of Energy Comprehensive Epidemiologic Data Resource.

Assessing the impact of different neutron RBEs on the all solid cancer radiation risks obtained from the Japanese A-bomb survivors data

PURPOSE

Development of a model characterizing risk variation with RBE to investigate how the incidence risk for all solid cancers combined varies with higher neutron RBEs and different organ dose types.

MATERIAL AND METHODS

The model is based on RERF data with separate neutron and gamma dose information.

RESULTS

For both additive and multiplicative linear excess risks per unit organ averaged dose, a reduction of 50% in the risk coefficient per weighted dose arises when a neutron RBE of 110 is used instead of 10. Considering risk per unit liver dose, this reduction occurs for an RBE of 130 and for risks per unit colon dose for an RBE of 190. The change in the shape of the dose response curve when using higher neutron RBEs is evaluated. The curvature changed and became significantly negative for males at an RBE of 140 for colon dose, 100 for liver dose and 80 for organ averaged dose. For females this is the case at an RBE of 110, 80 and 60, respectively.

CONCLUSIONS

Uncertainties in neutron RBE values should be considered when radiation risks and the shape of dose responses are deduced from cancer risk data from the atomic bomb survivors.

Low-Dose Extrapolation Factors Implied by Mortality and Incidence Data from the Japanese Atomic Bomb Survivor Life Span Study Data

Assessment of the effect of low dose and low-dose-rate exposure depends critically on extrapolation from groups exposed at high dose and high-dose rates such as the Japanese atomic bomb survivor data, and has often been achieved via application of a dose and dose-rate effectiveness factor (DDREF). An important component of DDREF is the factor determining the effect of extrapolation of dose, the so-called low-dose extrapolation factor (LDEF). To assess LDEF models linear (or linear quadratic) in dose are often fitted. In this report LDEF is assessed via fitting relative rate models that are linear or linear quadratic in dose to the latest Japanese atomic bomb survivor data on solid cancer, leukemia and circulatory disease mortality (followed from 1950 through 2003) and to data on solid cancer, lung cancer and urinary tract cancer incidence. The uncertainties in LDEF are assessed using parametric bootstrap techniques. Analysis is restricted to survivors with <3 Gy dose. There is modest evidence for upward curvature in dose response in the mortality data. For leukemia and for all solid cancer excluding lung, stomach and breast cancer there is significant curvature (P < 0.05). There is no evidence of curvature for circulatory disease (P > 0.5). The estimate of LDEF for all solid cancer mortality is 1.273 [95% confidence intervals (CI) 0.913, 2.182], for all solid cancer mortality excluding lung cancer, stomach cancer and breast cancer is 2.183 (95% CI 1.090, >100) and for leukemia mortality is 11.447 (95% CI 2.390, >100). For stomach cancer mortality LDEF is modestly raised, 1.077 (95% CI 0.526, >100), while for lung cancer, female breast cancer and circulatory disease mortality the LDEF does not much exceed 1. LDEF for solid cancer incidence is 1.186 (95% CI 0.942, 1.626) and for urinary tract cancer is 1.298 (95% CI <0, 7.723), although for lung cancer LDEF is not elevated, 0.842 (95% CI 0.344, >100).

The Evidence for Excess Risk of Cancer and Non-Cancer Disease at Low Doses and Dose Rates

The question of whether there are excess radiation-associated health risks at low dose is controversial. We present evidence of excess cancer risks in a number of (largely pediatrically or in utero exposed) groups exposed to low doses of radiation (<0.1 Gy). Moreover, the available data on biological mechanisms do not provide support for the idea of a low-dose threshold or hormesis for any of these endpoints. There are emerging data suggesting risks of cardiovascular disease and cataract at low doses, but this is less well established. This large body of evidence does not suggest and, indeed, is not statistically compatible with any very large threshold in dose (>10 mGy), or with possible beneficial effects from exposures. The presented data suggest that exposure to low-dose radiation causes excess cancer risks and quite possibly also excess risks of various non-cancer endpoints.

Radiation dose rate effects: what is new and what is needed?

Despite decades of research to understand the biological effects of ionising radiation, there is still much uncertainty over the role of dose rate. Motivated by a virtual workshop on the "Effects of spatial and temporal variation in dose delivery" organised in November 2020 by the Multidisciplinary Low Dose Initiative (MELODI), here, we review studies to date exploring dose rate effects, highlighting significant findings, recent advances and to provide perspective and recommendations for requirements and direction of future work. A comprehensive range of studies is considered, including molecular, cellular, animal, and human studies, with a focus on low linear-energy-transfer radiation exposure. Limits and advantages of each type of study are discussed, and a focus is made on future research needs.

Ionizing radiation, cerebrovascular disease, and consequent dementia: A review and proposed framework relevant to space radiation exposure

Space exploration requires the characterization and management or mitigation of a variety of human health risks. Exposure to space radiation is one of the main health concerns because it has the potential to increase the risk of cancer, cardiovascular disease, and both acute and late neurodegeneration. Space radiation-induced decrements to the vascular system may impact the risk for cerebrovascular disease and consequent dementia. These risks may be independent or synergistic with direct damage to central nervous system tissues. The purpose of this work is to review epidemiological and experimental data regarding the impact of low-to-moderate dose ionizing radiation on the central nervous system and the cerebrovascular system. A proposed framework outlines how space radiation-induced effects on the vasculature may increase risk for both cerebrovascular dysfunction and neural and cognitive adverse outcomes. The results of this work suggest that there are multiple processes by which ionizing radiation exposure may impact cerebrovascular function including increases in oxidative stress, neuroinflammation, endothelial cell dysfunction, arterial stiffening, atherosclerosis, and cerebral amyloid angiopathy. Cerebrovascular adverse outcomes may also promote neural and cognitive adverse outcomes. However, there are many gaps in both the human and preclinical evidence base regarding the long-term impact of ionizing radiation exposure on brain health due to heterogeneity in both exposures and outcomes. The unique composition of the space radiation environment makes the translation of the evidence base from terrestrial exposures to space exposures difficult. Additional investigation and understanding of the impact of low-to-moderate doses of ionizing radiation including high (H) atomic number (Z) and energy (E) (HZE) ions on the cerebrovascular system is needed. Furthermore, investigation of how decrements in vascular systems may contribute to development of neurodegenerative diseases in independent or synergistic pathways is important for protecting the long-term health of astronauts.

Application of radiation omics in the development of adverse outcome pathway networks: an example of radiation-induced cardiovascular disease

BACKGROUND

Epidemiological studies have indicated that exposure of the heart to doses of ionizing radiation as low as 0.5 Gy increases the risk of cardiac morbidity and mortality with a latency period of decades. The damaging effects of radiation to myocardial and endothelial structures and functions have been confirmed radiobiologically at high dose, but much less is known at low dose. Integration of radiation biology and epidemiology data is a recommended approach to improve the radiation risk assessment process. The adverse outcome pathway (AOP) framework offers a comprehensive tool to compile and translate mechanistic information into pathological endpoints which may be relevant for risk assessment at the different levels of a biological system. Omics technologies enable the generation of large volumes of biological data at various levels of complexity, from molecular pathways to functional organisms. Given the quality and quantity of available data across levels of biology, omics data can be attractive sources of information for use within the AOP framework. It is anticipated that radiation omics studies could improve our understanding of the molecular mechanisms behind the adverse effects of radiation on the cardiovascular system. In this review, we explored the available omics studies on radiation-induced cardiovascular disease (CVD) and their applicability to the proposed AOP for CVD.

RESULTS

The results of 80 omics studies published on radiation-induced CVD over the past 20 years have been discussed in the context of the AOP of CVD proposed by Chauhan et al. Most of the available omics data on radiation-induced CVD are from proteomics, transcriptomics, and metabolomics, whereas few datasets were available from epigenomics and multi-omics. The omics data presented here show great promise in providing information for several key events of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix and vascular remodeling.

CONCLUSIONS

The omics data presented here shows promise to inform the various levels of the proposed AOP of CVD. However, the data highlight the urgent need of designing omics studies to address the knowledge gap concerning different radiation scenarios, time after exposure and experimental models. This review presents the evidence to build a qualitative omics-informed AOP and provides views on the potential benefits and challenges in using omics data to assess risk-related outcomes.

Impact of uncertainties in exposure assessment on thyroid cancer risk among cleanup workers in Ukraine exposed due to the Chornobyl accident

A large excess risk of thyroid cancer was observed among Belarusian/Russian/Baltic Chornobyl cleanup workers. A more recent study of Ukraine cleanup workers found more modest excess risks of thyroid cancer. Dose errors in this data are substantial, associated with model uncertainties and questionnaire response. Regression calibration is often used for dose-error adjustment, but may not adequately account for the full error distribution. We aimed to examine the impact of exposure-assessment uncertainties on thyroid cancer among Ukrainian cleanup workers using Monte Carlo maximum likelihood, and compare with results derived using regression calibration. Analyses assessed the sensitivity of results to various components of internal and external dose. Regression calibration yielded an excess odds ratio per Gy (EOR/Gy) of 0.437 (95% CI - 0.042, 1.577, p = 0.100), compared with the EOR/Gy using Monte Carlo maximum likelihood of 0.517 (95% CI - 0.039, 2.035, p = 0.093). Trend risk estimates for follicular morphology tumors exhibited much more extreme effects of full-likelihood adjustment, the EOR/Gy using regression calibration of 3.224 (95% CI - 0.082, 30.615, p = 0.068) becoming ~ 50% larger, 4.708 (95% CI - 0.075, 85.143, p = 0.066) when using Monte Carlo maximum likelihood. Results were sensitive to omission of external components of dose. In summary, use of Monte Carlo maximum likelihood adjustment for dose error led to increases in trend risks, particularly for follicular morphology thyroid cancers, where risks increased by ~ 50%, and were borderline significant. The unexpected finding for follicular tumors needs to be replicated in other exposed groups.

Cancer risks among studies of medical diagnostic radiation exposure in early life without quantitative estimates of dose

BACKGROUND

There is accumulating evidence of excess risk of cancer in various populations exposed at acute doses below several tens of mSv or doses received over a protracted period. There is also evidence that relative risks are generally higher after radiation exposures in utero or in childhood.

METHODS AND FINDINGS

We reviewed and summarised evidence from 89 studies of cancer following medical diagnostic exposure in utero or in childhood, in which no direct estimates of radiation dose are available. In all of the populations studied exposure was to sparsely ionizing radiation (X-rays). Several of the early studies of in utero exposure exhibit modest but statistically significant excess risks of several types of childhood cancer. There is a highly significant (p < 0.0005) negative trend of odds ratio with calendar period of study, so that more recent studies tend to exhibit reduced excess risk. There is no significant inter-study heterogeneity (p > 0.3). In relation to postnatal exposure there are significant excess risks of leukaemia, brain and solid cancers, with indications of variations in risk by cancer type (p = 0.07) and type of exposure (p = 0.02), with fluoroscopy and computed tomography scans associated with the highest excess risk. However, there is highly significant inter-study heterogeneity (p < 0.01) for all cancer endpoints and all but one type of exposure, although no significant risk trend with calendar period of study.

CONCLUSIONS

Overall, this large body of data relating to medical diagnostic radiation exposure in utero provides support for an associated excess risk of childhood cancer. However, the pronounced heterogeneity in studies of postnatal diagnostic exposure, the implied uncertainty as to the meaning of summary measures, and the distinct possibilities of bias, substantially reduce the strength of the evidence from the associations we observe between radiation imaging in childhood and the subsequent risk of cancer being causally related to radiation exposure.

Temporal Changes in Sparing and Enhancing Dose Protraction Effects of Ionizing Irradiation for Aortic Damage in Wild-Type Mice

In medical and occupational settings, ionizing irradiation of the circulatory system occurs at various dose rates. We previously found sparing and enhancing dose protraction effects for aortic changes in wild-type mice at 6 months after starting irradiation with 5 Gy of photons. Here, we further analyzed changes at 12 months after stating irradiation. Irrespective of irradiation regimens, irradiation little affected left ventricular function, heart weight, and kidney weight. Irradiation caused structural disorganizations and intima-media thickening in the aorta, along with concurrent elevations of markers for proinflammation, macrophage, profibrosis, and fibrosis, and reductions in markers for vascular functionality and cell adhesion in the aortic endothelium. These changes were qualitatively similar but quantitatively less at 12 months than at 6 months. The magnitude of such changes at 12 months was not smaller in 25 fractions (Frs) but was smaller in 100 Frs and chronic exposure than acute exposure. The magnitude at 6 and 12 months was greater in 25 Frs, smaller in 100 Frs, and much smaller in chronic exposure than acute exposure. These findings suggest that dose protraction changes aortic damage, in a fashion that depends on post-irradiation time and is not a simple function of dose rate.

ICRP PUBLICATION 152 Approved by the Commission in November 2021

Radiation detriment is a concept developed by the International Commission on Radiological Protection to quantify the burden of stochastic effects from low-dose and/or low-dose-rate exposures to the human population. It is determined from the lifetime risks of cancer for a set of organs and tissues and the risk of heritable effects, taking into account the severity of the consequences. This publication provides a historical review of detriment calculation methodology since ICRP Publication 26, with details of the procedure developed in ICRP Publication 103, which clarifies data sources, risk models, computational methods, and rationale for the choice of parameter values. A selected sensitivity analysis was conducted to identify the parameters and calculation conditions that can be major sources of variation and uncertainty in the calculation of radiation detriment. It has demonstrated that sex, age at exposure, dose and dose-rate effectiveness factor, dose assumption in the calculation of lifetime risk, and lethality fraction have a substantial impact on radiation detriment values. Although the current scheme of radiation detriment calculation is well established, it needs to evolve to better reflect changes in population health statistics and progress in scientific understanding of radiation health effects. In this regard, some key parameters require updating, such as the reference population data and cancer severity. There is also room for improvement in cancer risk models based on the accumulation of recent epidemiological findings. Finally, the importance of improving the comprehensibility of the detriment concept and the transparency of its calculation process is emphasised.© 2022 ICRP. Published by SAGE.

Cardiovascular Disease Risk Modeling for Astronauts: Making the Leap From Earth to Space

NASA has recently completed several long-duration missions to the International Space Station and is solidifying plans to return to the Moon, with an eye toward Mars and beyond. As NASA pushes the boundaries of human space exploration, the hazards of spaceflight, including space radiation, levy an increasing burden on astronaut health and performance. The cardiovascular system may be especially vulnerable due to the combined impacts of space radiation exposure, lack of gravity, and other spaceflight hazards. On Earth, the risk for cardiovascular disease (CVD) following moderate to high radiation doses is well-established from clinical, environmental, and occupational exposures (largely from gamma- and x-rays). Less is known about CVD risks associated with high-energy charged ions found in space and increasingly used in radiotherapy applications on Earth, making this a critical area of investigation for occupational radiation protection. Assessing CVD risk is complicated by its multifactorial nature, where an individual's risk is strongly influenced by factors such as family history, blood pressure, and lipid profiles. These known risk factors provide the basis for development of a variety of clinical risk prediction models (CPMs) that inform the likelihood of medical outcomes over a defined period. These tools improve clinical decision-making, personalize care, and support primary prevention of CVD. They may also be useful for individualizing risk estimates for CVD following radiation exposure both in the clinic and in space. In this review, we summarize unique aspects of radiation risk assessment for astronauts, and we evaluate the most widely used CVD CPMs for their use in NASA radiation risk assessment applications. We describe a comprehensive dual-use risk assessment framework that supports both clinical care and operational management of space radiation health risks using quantitative metrics. This approach is a first step in using personalized medicine for radiation risk assessment to support safe and productive spaceflight and long-term quality of life for NASA astronauts.

Comparison of All Solid Cancer Mortality and Incidence Dose-Response in the Life Span Study of Atomic Bomb Survivors, 1958-2009

Recent analysis of all solid cancer incidence (1958-2009) in the Life Span Study (LSS) revealed evidence of upward curvature in the radiation dose response among males but not females. Upward curvature in sex-averaged excess relative risk (ERR) for all solid cancer mortality (1950-2003) was also observed in the 0-2 Gy dose range. As reasons for non-linearity in the LSS are not completely understood, we conducted dose-response analyses for all solid cancer mortality and incidence applying similar methods [1958-2009 follow-up, DS02R1 doses, including subjects not-in-city (NIC) at the time of the bombing] and statistical models. Incident cancers were ascertained from Hiroshima and Nagasaki cancer registries, while cause of death was ascertained from death certificates throughout Japan. The study included 105,444 LSS subjects who were alive and not known to have cancer before January 1, 1958 (80,205 with dose estimates and 25,239 NIC subjects). Between 1958 and 2009, there were 3.1 million person-years (PY) and 22,538 solid cancers for incidence analysis and 3.8 million PY and 15,419 solid cancer deaths for mortality analysis. We fitted sex-specific ERR models adjusted for smoking to both types of data. Over the entire range of doses, solid cancer mortality dose-response exhibited a borderline significant upward curvature among males (P = 0.062) and significant upward curvature among females (P = 0.010); for solid cancer incidence, as before, we found a significant upward curvature among males (P = 0.001) but not among females (P = 0.624). The sex difference in magnitude of dose-response curvature was statistically significant for cancer incidence (P = 0.017) but not for cancer mortality (P = 0.781). The results of analyses in the 0-2 Gy range and restricted lower dose ranges generally supported inferences made about the sex-specific dose-response shape over the entire range of doses for each outcome. Patterns of sex-specific curvature by calendar period (1958-1987 vs. 1988-2009) and age at exposure (0-19 vs. 20-83) varied between mortality and incidence data, particularly among females, although for each outcome there was an indication of curvature among 0-19-year-old male survivors in both calendar periods and among 0-19-year-old female survivors in the recent period. Collectively, our findings indicate that the upward curvature in all solid cancer dose response in the LSS is neither specific to males nor to incidence data; its evidence appears to depend on the composition of sites comprising all solid cancer group and age at exposure or time. Further follow up and site-specific analyses of cancer mortality and incidence will be important to confirm the emerging trend in dose-response curvature among young survivors and unveil the contributing factors and sites.

Radiation cancer risk at different dose rates: new dose-rate effectiveness factors derived from revised A-bomb radiation dosimetry data and non-tumor doses

The dose rate of atomic bomb (A-bomb) radiation to the survivors has still remained unclear, although the dose-response data of A-bomb cancers has been taken as a standard in estimating the cancer risk of radiation and the dose and dose-rate effectiveness factor (DDREF). Since the applicability of the currently used DDREF of 2 derived from A-bomb data is limited in a narrow dose-rate range, 0.25-75 Gy/min as estimated from analysis of DS86 dosimetry data in the present study, a non-tumor dose (Dnt) was applied in an attempt to gain a more universal dose-rate effectiveness factor (DREF), where Dnt is an empirical parameter defined as the highest dose at which no statistically significant tumor increase is observed above the control level and its magnitude depends on the dose rate. The new DREF values were expressed as a function of the dose rate at four exposure categories, i.e. partial body low LET, whole body low linear energy transfer (LET), partial body high LET and whole body high LET and provided a value of 14 for environmental level radiation at a dose rate of 10-9 Gy/min for whole body low LET.

Review of the risk of cancer following low and moderate doses of sparsely ionising radiation received in early life in groups with individually estimated doses

BACKGROUND

The detrimental health effects associated with the receipt of moderate (0.1-1 Gy) and high (>1 Gy) acute doses of sparsely ionising radiation are well established from human epidemiological studies. There is accumulating direct evidence of excess risk of cancer in a number of populations exposed at lower acute doses or doses received over a protracted period. There is evidence that relative risks are generally higher after radiation exposures in utero or in childhood.

METHODS AND FINDINGS

We reviewed and summarised evidence from 60 studies of cancer or benign neoplasms following low- or moderate-level exposure in utero or in childhood from medical and environmental sources. In most of the populations studied the exposure was predominantly to sparsely ionising radiation, such as X-rays and gamma-rays. There were significant (p < 0.001) excess risks for all cancers, and particularly large excess relative risks were observed for brain/CNS tumours, thyroid cancer (including nodules) and leukaemia.

CONCLUSIONS

Overall, the totality of this large body of data relating to in utero and childhood exposure provides support for the existence of excess cancer and benign neoplasm risk associated with radiation doses < 0.1 Gy, and for certain groups exposed to natural background radiation, to fallout and medical X-rays in utero, at about 0.02 Gy.

Cancer risk following low doses of ionising radiation - Current epidemiological evidence and implications for radiological protection

Recent studies suggest that every year worldwide about a million patients might be exposed to doses of the order of 100 mGy of low-LET radiation, due to recurrent application of radioimaging procedures. This paper presents a synthesis of recent epidemiological evidence on radiation-related cancer risks from low-LET radiation doses of this magnitude. Evidence from pooled analyses and meta-analyses also involving epidemiological studies that, individually, do not find statistically significant radiation-related cancer risks is reviewed, and evidence from additional and more recent epidemiological studies of radiation exposures indicating excess cancer risks is also summarized. Cohorts discussed in the present paper include Japanese atomic bomb survivors, nuclear workers, patients exposed for medical purposes, and populations exposed environmentally to natural background radiation or radioactive contamination. Taken together, the overall evidence summarized here is based on studies including several million individuals, many of them followed-up for more than half a century. In summary, substantial evidence was found from epidemiological studies of exposed groups of humans that ionizing radiation causes cancer at acute and protracted doses above 100 mGy, and growing evidence for doses below 100 mGy. The significant radiation-related solid cancer risks observed at doses of several 100 mGy of protracted exposures (observed, for example, among nuclear workers) demonstrate that doses accumulated over many years at low dose rates do cause stochastic health effects. On this basis, it can be concluded that doses of the order of 100 mGy from recurrent application of medical imaging procedures involving ionizing radiation are of concern, from the viewpoint of radiological protection.

Vascular Damage in the Aorta of Wild-Type Mice Exposed to Ionizing Radiation: Sparing and Enhancing Effects of Dose Protraction

During medical (therapeutic or diagnostic) procedures or in other settings, the circulatory system receives ionizing radiation at various dose rates. Here, we analyzed prelesional changes in the circulatory system of wild-type mice at six months after starting acute, intermittent, or continuous irradiation with 5 Gy of photons. Independent of irradiation regimens, irradiation had little impact on left ventricular function, heart weight, and kidney weight. In the aorta, a single acute exposure delivered in 10 minutes led to structural disorganizations and detachment of the aortic endothelium, and intima-media thickening. These morphological changes were accompanied by increases in markers for profibrosis (TGF-β1), fibrosis (collagen fibers), proinflammation (TNF-α), and macrophages (F4/80 and CD68), with concurrent decreases in markers for cell adhesion (CD31 and VE-cadherin) and vascular functionality (eNOS) in the aortic endothelium. Compared with acute exposure, the magnitude of such aortic changes was overall greater when the same dose was delivered in 25 fractions spread over 6 weeks, smaller in 100 fractions over 5 months, and much smaller in chronic exposure over 5 months. These findings suggest that dose protraction alters vascular damage in the aorta, but in a way that is not a simple function of dose rate.

Quantitative Bias Analysis of the Association between Occupational Radiation Exposure and Ischemic Heart Disease Mortality in UK Nuclear Workers

The scientific question of whether protracted low-dose or low-dose-rate exposure to external radiation is causally related to the risk of circulatory disease continues to be an important issue for radiation protection. Previous analyses of a matched case-control dataset nested in a large cohort of UK nuclear fuel cycle workers indicated that there was little evidence that observed associations between external radiation dose and ischemic heart disease (IHD) mortality risk [OR = 1.35 (95% CI: 0.99-184) for 15-year-lagged exposure] could alternatively be explained by confounding from pre-employment tobacco smoking, BMI or blood pressure, or from socioeconomic status or occupational exposure to excessive noise or shiftwork. To improve causal inference about the observed external radiation dose and IHD mortality association, we estimated the potential magnitude and direction of non-random errors, incorporated sensitivity analyses and simulated bias effects under plausible scenarios. We conducted quantitative bias analyses of plausible scenarios based on 1,000 Monte Carlo samples to explore the impact of exposure measurement error, missing information on tobacco smoking, and unmeasured confounding, and assessed whether observed associations were reliant on the inclusion of specific matched pairs using bootstrapping with 10% of matched pairs randomly excluded in 1,000 samples. We further explored the plausibility that having been monitored for internal exposure, which was an important confounding factor in the case-control analysis for which models were adjusted, was indeed a confounding factor or whether it might have been the result of some form of selection bias. Consistent with the broader epidemiological evidence-base, these analyses provide further evidence that the dose-response association between cumulative external radiation exposure and IHD mortality is non-linear in that it has a linear shape plateauing at an excess risk of 43% (95% CI: 7-92%) on reaching 390 mSv. Analyses of plausible scenarios of patterns of missing data for tobacco smoking at start of employment indicated that this resulted in relatively little bias towards the null in the original analysis. An unmeasured confounder would have had to have been highly correlated (rp > 0.60) with cumulative external radiation dose to importantly bias observed associations. The confounding effect of "having been monitored for internal dose" was unlikely to have been a true confounder in a biological sense, but instead may have been some unknown factor related to differences over time and between sites in selection criteria for internal monitoring, possibly resulting in collider bias. Plausible patterns of exposure measurement error negatively biased associations regardless of the modeled scenario, but did not importantly change the shape of the observed dose-response associations. These analyses provide additional support for the hypothesis that the observed association between external radiation exposure and IHD mortality may be causal.

Methodological improvements to meta-analysis of low dose rate studies and derivation of dose and dose-rate effectiveness factors

Epidemiological studies of cancer rates associated with external and internal exposure to ionizing radiation have been subject to extensive reviews by various scientific bodies. It has long been assumed that radiation-induced cancer risks at low doses or low-dose rates are lower (per unit dose) than those at higher doses and dose rates. Based on a mixture of experimental and epidemiologic evidence the International Commission on Radiological Protection recommended the use of a dose and dose-rate effectiveness factor for purposes of radiological protection to reduce solid cancer risks obtained from moderate-to-high acute dose studies (e.g. those derived from the Japanese atomic bomb survivors) when applied to low dose or low-dose rate exposures. In the last few years there have been a number of attempts at assessing the effect of extrapolation of dose rate via direct comparison of observed risks in low-dose rate occupational studies and appropriately age/sex-adjusted analyses of the Japanese atomic bomb survivors. The usual approach is to consider the ratio of the excess relative risks in the two studies, a measure of the inverse of the dose rate effectiveness factor. This can be estimated using standard meta-analysis with inverse weighting of ratios of relative risks using variances derived via the delta method. In this paper certain potential statistical problems in the ratio of estimated excess relative risks for low-dose rate studies to the excess relative risk in the Japanese atomic bomb survivors are discussed, specifically the absence of a well-defined mean and the theoretically unbounded variance of this ratio. A slightly different method of meta-analysis for estimating uncertainties of these ratios is proposed, motivated by Fieller's theorem, which leads to slightly different central estimates and confidence intervals for the dose rate effectiveness factor. However, given the uncertainties in the data, the differences in mean values and uncertainties from the dose rate effectiveness factor estimated using delta-method-based meta-analysis are not substantial, generally less than 70%.

Modeling Radiation-Induced Neoplastic Cell Transformation In Vitro and Tumor Induction In Vivo with the Local Effect Model

Ionizing radiation induces DNA damage to cycling cells which, if left unrepaired or misrepaired, can cause cell inactivation or heritable, viable mutations. The latter can lead to cell transformation, which is thought to be an initial step of cancer formation. Consequently, the study of radiation-induced cell transformation promises to offer insights into the general properties of radiation carcinogenesis. As for other end points, the effectiveness in inducing cell transformation is elevated for radiation qualities with high linear energy transfer (LET), and the same is true for cancer induction. In considering DNA damage as a common cause of both cell death and transformations, a worthwhile approach is to apply mathematical models for the relative biological effectiveness (RBE) of cell killing to also assess the carcinogenic potential of high-LET radiation. In this work we used an established RBE model for cell survival and clinical end points, the local effect model (LEM), to estimate the transformation probability and the carcinogenic potential of ion radiation. The provided method consists of accounting for the competing processes of cell inactivation and induction of transformations or carcinogenic events after radiation exposure by a dual use of the LEM. Correlations between both processes inferred by the number of particle impacts to individual cells were considered by summing over the distribution of hits that individual cells receive. RBE values for cell transformation in vitro were simulated for three independent data sets, which were also used to gauge the approach. The simulations reflect the general RBE systematics both in magnitude and in energy and LET dependence. To challenge the developed method, in vivo carcinogenesis was investigated using the same concepts, where the probability for cancer induction within an irradiated organ was derived from the probability of finding carcinogenic events in individual cells. The predictions were compared with experimental data of carcinogenesis in Harderian glands of mice. Again, the developed method shows the same characteristics as the experimental data. We conclude that the presented method is helpful to predictively assess RBE for both neoplastic cell transformation and tumor induction after ion exposure within a wide range of LET values. The theoretical concept requires a non-linear component in the photon dose response for carcinogenic end points as a precondition for the observed enhanced effects after ion exposure, thus contributing to a long debate in epidemiology. Future work will use the method for assessing cancer induction in radiation therapy and exposure scenarios frequently discussed in radiation protection.

Evaluation of the lifetime brain/central nervous system cancer risk associated with childhood head CT scanning in Japan

The use of computed tomography (CT) scanning has increased worldwide over the decades, and Japan is one of the leading countries in annual frequency of diagnostic CT. Although benefits of CT scan are undisputable, concerns have been raised about potential health effects of ionizing radiation exposure from CT, particularly among children who are likely more susceptible to radiation than adults. Our study aims to evaluate the cumulated lifetime risk of the brain/central nervous system (CNS) cancer due to head CT examinations performed on Japanese children at age 0 to 10 years in 2012, 2015 and 2018. The frequency and dose distribution of head CT examinations were estimated based on information from recent national statistics and nationwide surveys. The lifetime risk attributable to exposure was calculated by applying risk models based on the study of Japanese atomic-bomb survivors. In contrast to the overall increasing trend, the frequency of childhood CT, especially at age < 5, was decreasing, reflecting a growing awareness for efforts to reduce childhood CT exposure over the past decade. In 2018, 138 532 head CT examinations were performed at age 0 to 10, which would consequently induce a lifetime excess of 22 cases (1 per 6300 scans) of brain/CNS cancers, accounting for 5% of the total cases. More excess cases were estimated among men than among women, and excess cases could emerge at relatively young ages. These results would have useful implications as scientific basis for future large-scale epidemiological studies and also as quantitative evidence to justify the benefits of CT vs risks in Japan.

Low- and moderate-dose non-cancer effects of ionizing radiation in directly exposed individuals, especially circulatory and ocular diseases: a review of the epidemiology

PURPOSE

There are well-known correlations between high and moderate doses (>0.5 Gy) of ionizing radiation exposure and circulatory system damage, also between radiation and posterior subcapsular cataract. At lower dose correlations with circulatory disease are emerging in the Japanese atomic bomb survivors and in some occupationally exposed groups, and are still to some extent controversial. Heterogeneity in excess relative risks per unit dose in epidemiological studies at low (<0.1 Gy) and at low-moderate (>0.1 Gy, <0.5 Gy) doses may result from confounding and other types of bias, and effect modification by established risk factors. There is also accumulating evidence of excess cataract risks at lower dose and low dose rate in various cohorts. Other ocular endpoints, specifically glaucoma and macular degeneration have been little studied. In this paper, we review recent epidemiological findings, and also discuss some of the underlying radiobiology of these conditions. We briefly review some other types of mainly neurological nonmalignant disease in relation to radiation exposure.

CONCLUSIONS

We document statistically significant excess risk of the major types of circulatory disease, specifically ischemic heart disease and stroke, in moderate- or low-dose exposed groups, with some not altogether consistent evidence suggesting dose-response non-linearity, particularly for stroke. However, the patterns of risk reported are not straightforward. We also document evidence of excess risks at lower doses/dose-rates of posterior subcapsular and cortical cataract in the Chernobyl liquidators, US Radiologic Technologists and Russian Mayak nuclear workers, with fundamentally linear dose-response. Nuclear cataracts are less radiogenic. For other ocular endpoints, specifically glaucoma and macular degeneration there is very little evidence of effects at low doses; radiation-associated glaucoma has been documented only for doses >5 Gy, and so has the characteristics of a tissue reaction. There is some evidence of neurological detriment following low-moderate dose (∼0.1-0.2 Gy) radiation exposure in utero or in early childhood.

Cancer incidence risks above and below 1 Gy for radiation protection in space

The risk assessment quantities called lifetime attributable risk (LAR) and risk of exposure-induced cancer (REIC) are used to calculate the cumulative cancer incidence risks for astronauts, attributable to radiation exposure accumulated during long term lunar and Mars missions. These risk quantities are based on the most recently published epidemiological data on the Life Span Study (LSS) of Japanese A-bomb survivors, who were exposed to γ-rays and neutrons. In order to analyze the impact of a different neutron RBE on the risk quantities, a model for the neutron relative biological effectiveness (RBE) relative to gammas in the LSS is developed based on an older dataset with less follow-up time. Since both risk quantities are based on uncertain quantities, such as survival curves, and REIC includes deterministic radiation induced non-cancer mortality risks, modelled with data based on the general population, the risks for astronauts may not be optimally estimated. The suitability of these risk assessment measures for the use of cancer risk calculation for astronauts is discussed. The work presented here shows that the use of a higher neutron RBE than the value of 10, traditionally used in the LSS risk models, can reduce the risks up to almost 50%. Additionally, including an excess absolute risk (EAR) baseline scaling also increases the risks by between 0.4% and 8.1% for the space missions considered in this study. Using just an EAR model instead of an equally weighted EAR and excess relative risk (ERR) model can decrease the cumulative risks for the considered missions by between 0.4% and 4.1% if no EAR baseline scaling is applied. If EAR baseline scaling is included, the calculated risks with the EAR- and the mixed model, as well as the risks calculated with just the ERR model are almost identical and only small differences in the uncertainties are visible.

Ionizing radiation-induced circulatory and metabolic diseases

Risks to health are the prime consideration in all human situations of ionizing radiation exposure and therefore of relevance to radiation protection in all occupational, medical, and public exposure situations. Over the past few decades, advances in therapeutic strategies have led to significant improvements in cancer survival rates. However, a wide range of long-term complications have been reported in cancer survivors, in particular circulatory diseases and their major risk factors, metabolic diseases. However, at lower levels of exposure, the evidence is less clear. Under real-life exposure scenarios, including radiotherapy, radiation effects in the whole organism will be determined mainly by the response of normal tissues receiving relatively low doses, and will be mediated and moderated by systemic effects. Therefore, there is an urgent need for further research on the impact of low-dose radiation. In this article, we review radiation-associated risks of circulatory and metabolic diseases in clinical, occupational or environmental exposure situations, addressing epidemiological, biological, risk modelling, and systems biology aspects, highlight the gaps in knowledge and discuss future directions to address these gaps.

Radiation-induced lens opacities: Epidemiological, clinical and experimental evidence, methodological issues, research gaps and strategy

In 2011, the International Commission on Radiological Protection (ICRP) recommended reducing the occupational equivalent dose limit for the lens of the eye from 150 mSv/year to 20 mSv/year, averaged over five years, with no single year exceeding 50 mSv. With this recommendation, several important assumptions were made, such as lack of dose rate effect, classification of cataracts as a tissue reaction with a dose threshold at 0.5 Gy, and progression of minor opacities into vision-impairing cataracts. However, although new dose thresholds and occupational dose limits have been set for radiation-induced cataract, ICRP clearly states that the recommendations are chiefly based on epidemiological evidence because there are a very small number of studies that provide explicit biological and mechanistic evidence at doses under 2 Gy. Since the release of the 2011 ICRP statement, the Multidisciplinary European Low Dose Initiative (MELODI) supported in April 2019 a scientific workshop that aimed to review epidemiological, clinical and biological evidence for radiation-induced cataracts. The purpose of this article is to present and discuss recent related epidemiological and clinical studies, ophthalmic examination techniques, biological and mechanistic knowledge, and to identify research gaps, towards the implementation of a research strategy for future studies on radiation-induced lens opacities. The authors recommend particularly to study the effect of ionizing radiation on the lens in the context of the wider, systemic effects, including in the retina, brain and other organs, and as such cataract is recommended to be studied as part of larger scale programs focused on multiple radiation health effects.

Adverse outcome pathways, key events, and radiation risk assessment

The overall aim of this contribution to the 'Second Bill Morgan Memorial Special Issue' is to provide a high-level review of a recent report developed by a Committee for the National Council on Radiation Protection and Measurements (NCRP) titled 'Approaches for Integrating Information from Radiation Biology and Epidemiology to Enhance Low-Dose Health Risk Assessment'. It derives from previous NCRP Reports and Commentaries that provide the case for integrating data from radiation biology studies (available and proposed) with epidemiological studies (also available and proposed) to develop Biologically-Based Dose-Response (BBDR) models. In this review, it is proposed for such models to leverage the adverse outcome pathways (AOP) and key events (KE) approach for better characterizing radiation-induced cancers and circulatory disease (as the example for a noncancer outcome). The review discusses the current state of knowledge of mechanisms of carcinogenesis, with an emphasis on radiation-induced cancers, and a similar discussion for circulatory disease. The types of the various informative BBDR models are presented along with a proposed generalized BBDR model for cancer and a more speculative one for circulatory disease. The way forward is presented in a comprehensive discussion of the research needs to address the goal of enhancing health risk assessment of exposures to low doses of radiation. The use of an AOP/KE approach for developing a mechanistic framework for BBDR models of radiation-induced cancer and circulatory disease is considered to be a viable one based upon current knowledge of the mechanisms of formation of these adverse health outcomes and the available technical capabilities and computational advances. The way forward for enhancing low-dose radiation risk estimates will require there to be a tight integration of epidemiology data and radiation biology information to meet the goals of relevance and sensitivity of the adverse health outcomes required for overall health risk assessment at low doses and dose rates.