[en] From 1946 - 1990, i.e. from shortly after the end of World War II and the rise of the cold war until the German reunification, there had been extensive uranium mining both in Saxony and Thuringia, which formed the southern parts of the former German Democratic Republic. Mining activities started in Saxony in the Ore Mountains (German: Erzgebirge). Mining was conducted by a Soviet, since 1954 by a Soviet- German Incorporated Company named Wismut. It is estimated that about 400,000 persons may have worked in this time period with the company, most of them underground or in uranium ore processing facilities. In the early years, exposure to radiation and dust was particularly high for underground workers. After introduction of several ventilation measures and wet drilling from 1955 onwards, the levels of exposures to the various agents steadily decreased. After German reunification, it was decided by the German Federal Ministry for the Environment to save health data that were stored in different places, but which together formed the Wismut Health Data Archives. Based on parts of the information kept in different places by different bodies, a cohort of 64,311 former Wismut employees could be established. The objective of the cohort study was to examine the long-term health effects of chronic exposure to radiation, dust and arsenic as well as their combined effects. Particular focus should be given to the outcome lung cancer, but also to extrapulmonary cancers, cardiovascular and respiratory diseases. This report gives a comprehensive overview on the background of the study, its objectives, material and methods employed so far for data analysis, information on how the cohort was established and which data are available, and descriptive results. All data referred to in this report are based on the cohort's second follow-up for the years 1946 - 2003. (orig.)

[en] Determinations of the lowest colon dose, D_m_i_n, below which there is a statistically significant excess relative risk of all solid cancer, when analyses are restricted to the range [0, D_m_i_n], are of current interest in research related to radiation protection and risk assessment. In reviewing recent cancer mortality reports on the Life Span Study (LSS) of Japanese A-bomb survivors, reported D_m_i_n values were found to vary between different reports. The report 12 (follow-up: 1950-1990) found a D_m_i_n of 50 mGy, but the most recent report 14 (follow-up: 1950-2003) found a D_m_i_n of 200 mGy. There were small dosimetry changes between report 12, which used DS86, and report 14, which used DS02, but these changes are unlikely to account for a difference in D_m_i_n of a factor of 4. This short communication examines the reasons for this difference in D_m_i_n by presenting further investigations into D_m_i_n using different trial values for D_m_i_n and various follow-up time spans, all with the same DS02 dosimetry. Magnitudes of the low-dose risks in different dose ranges are also presented. It is shown here that the main influence on D_m_i_n comes from the length of follow-up and a D_m_i_n of 50 mGy may also be obtained with the most recent LSS mortality data and DS02, if a restricted follow-up is analyzed. A systematic trend was evident of lower D_m_i_n values for earlier mortality follow-up periods, consistent with information from earlier LSS reports. Although it may seem surprising that the D_m_i_n increases with longer follow-up and better statistics, this systematic trend appears to be a consequence of decreasing mortality risks with longer follow-up, even though the error bars on the risks are getting smaller with increasing follow-up. These systematic trends also persisted after accounting for differences between baseline cancer rates for two groups of survivors who were either proximal or distal to the A-bomb hypocenter. Similar systematic trends, although much less pronounced, were also found in the LSS cancer incidence data. Some evidence is provided here that results on low-dose radiation risks from earlier follow-up periods should not be ignored by radiation protection authorities, once the results from the new extended follow-ups are published. This is because of the possibility that the new data for extended follow-up beyond a certain calendar time, which pertain to very long times since exposure, may be contributing to an overall reduction in radiation related risks per unit dose compared to analogous risks determined from earlier follow-up periods, because of the risk effect modification of time since exposure. (orig.)

[en] The impact of including model-averaged excess radiation risks (ER) into a measure of radiation attributed decrease of survival (RADS) for the outcome all solid cancer incidence and the impact on the uncertainties is demonstrated. It is shown that RADS applying weighted model averaged ER based on AIC weights result in smaller risk estimates with narrower 95% CI than RADS using ER based on BIC weights. Further a multi-method-multi-model inference approach is introduced that allows calculating one general RADS estimate providing a weighted average risk estimate for a lunar and a Mars mission. For males the general RADS estimate is found to be 0.42% (95% CI: 0.38%; 0.45%) and for females 0.67% (95% CI: 0.59%; 0.75%) for a lunar mission and 2.45% (95% CI: 2.23%; 2.67%) for males and 3.91% (95% CI: 3.44%; 4.39%) for females for a Mars mission considering an age at exposure of 40 years and an attained age of 65 years. It is recommended to include these types of uncertainties and to include model-averaged excess risks in astronaut risk assessment.

[en] It has generally been assumed that the neutron and γ-ray absorbed doses in the data from the life span study (LSS) of the Japanese A-bomb survivors are too highly correlated for an independent separation of the all solid cancer risks due to neutrons and due to γ-rays. However, with the release of the most recent data for all solid cancer incidence and the increased statistical power over previous datasets, it is instructive to consider alternatives to the usual approaches. Simple excess relative risk (ERR) models for radiation-induced solid cancer incidence fitted to the LSS epidemiological data have been applied with neutron and γ-ray absorbed doses as separate explanatory covariables. A simple evaluation of the degree of independent effects from γ-ray and neutron absorbed doses on the all solid cancer risk with the hierarchical partitioning (HP) technique is presented here. The degree of multi-collinearity between the γ-ray and neutron absorbed doses has also been considered. The results show that, whereas the partial correlation between the neutron and γ-ray colon absorbed doses may be considered to be high at 0.74, this value is just below the level beyond which remedial action, such as adding the doses together, is usually recommended. The resulting variance inflation factor is 2.2. Applying HP indicates that just under half of the drop in deviance resulting from adding the γ-ray and neutron absorbed doses to the baseline risk model comes from the joint effects of the neutrons and γ-rays - leaving a substantial proportion of this deviance drop accounted for by individual effects of the neutrons and γ-rays. The average ERR/Gy γ-ray absorbed dose and the ERR/Gy neutron absorbed dose that have been obtained here directly for the first time, agree well with previous indirect estimates. The average relative biological effectiveness (RBE) of neutrons relative to γ-rays, calculated directly from fit parameters to the all solid cancer ERR model with both colon absorbed dose covariables, is 65 (95 %CI: 11; 170). Therefore, although the 95 % CI is quite wide, reference to the colon doses with a neutron weighting of 10 may not be optimal as the basis for the determination of all solid cancer risks. Further investigations into the neutron RBE are required, ideally based on the LSS data with organ-specific neutron and γ-ray absorbed doses for all organs rather than the RBE weighted absorbed doses currently provided. The HP method is also suggested for use in other epidemiological cohort analyses that involve correlated explanatory covariables. (orig.)

[en] A previous analysis of the radon-related lung cancer mortality risk, in the German uranium miners cohort, using Poisson modeling techniques, noted internal (spontaneous) rates that were higher on average than the external rates by 16.5% (95% CI: 9%; 24%). The main purpose of the present paper is to investigate the nature of, and possible reasons for, this difference by comparing patterns in spontaneous lung cancer mortality rates in a cohort of male miners involved in uranium extraction at the former Wismut mining company in East Germany with national male rates from the former German Democratic Republic. The analysis is based on miner data for 3,001 lung cancer deaths, 1.76 million person-years for the period 1960-2003, and national rates covering the same calendar-year range. Simple ''age-period-cohort'' graphical analyses were applied to assess the main qualitative differences between the national and cohort baseline lung cancer rates. Some differences were found to occur mainly at higher attained ages above 70 years. Although many occupational risk factors may have contributed to these observed age differences, only the effects of smoking have been assessed here by applying the Peto-Lopez indirect method for calculating smoking attributability. It is inferred that the observed age differences could be due to the greater prevalence of smoking and more mature smoking epidemic in the Wismut cohort compared to the general population of the former German Democratic Republic. In view of these observed differences between external population-based rates and internal (spontaneous) cohort baseline lung cancer rates, it is strongly recommended to apply only the internal rates in future analyses of uranium miner cohorts. (orig.)

[en] Radiation-related risks of cancer can be transported from one population to another population at risk, for the purpose of calculating lifetime risks from radiation exposure. Transfer via excess relative risks (ERR) or excess absolute risks (EAR) or a mixture of both (i.e., from the life span study (LSS) of Japanese atomic bomb survivors) has been done in the past based on qualitative weighting. Consequently, the values of the weights applied and the method of application of the weights (i.e., as additive or geometric weighted means) have varied both between reports produced at different times by the same regulatory body and also between reports produced at similar times by different regulatory bodies. Since the gender and age patterns are often markedly different between EAR and ERR models, it is useful to have an evidence-based method for determining the relative goodness of fit of such models to the data. This paper identifies a method, using Akaike model weights, which could aid expert judgment and be applied to help to achieve consistency of approach and quantitative evidence-based results in future health risk assessments. The results of applying this method to recent LSS cancer incidence models are that the relative EAR weighting by cancer solid cancer site, on a scale of 0-1, is zero for breast and colon, 0.02 for all solid, 0.03 for lung, 0.08 for liver, 0.15 for thyroid, 0.18 for bladder and 0.93 for stomach. The EAR weighting for female breast cancer increases from 0 to 0.3, if a generally observed change in the trend between female age-specific breast cancer incidence rates and attained age, associated with menopause, is accounted for in the EAR model. Application of this method to preferred models from a study of multi-model inference from many models fitted to the LSS leukemia mortality data, results in an EAR weighting of 0. From these results it can be seen that lifetime risk transfer is most highly weighted by EAR only for stomach cancer. However, the generalization and interpretation of radiation effect estimates based on the LSS cancer data, when projected to other populations, are particularly uncertain if considerable differences exist between site-specific baseline rates in the LSS and the other populations of interest. Definitive conclusions, regarding the appropriate method for transporting cancer risks, are limited by a lack of knowledge in several areas including unknown factors and uncertainties in biological mechanisms and genetic and environmental risk factors for carcinogenesis; uncertainties in radiation dosimetry; and insufficient statistical power and/or incomplete follow-up in data from radio-epidemiological studies. (orig.)

[en] In the assessment of health risks after nuclear accidents, some health consequences require special attention. For example, in their 2013 report on health risk assessment after the Fukushima nuclear accident, the World Health Organisation (WHO) panel of experts considered risks of breast cancer, thyroid cancer and leukaemia. For these specific cancer types, use was made of already published excess relative risk (ERR) and excess absolute risk (EAR) models for radiation-related cancer incidence fitted to the epidemiological data from the Japanese A-bomb Life Span Study (LSS). However, it was also considered important to assess all other types of solid cancer together and the WHO, in their above-mentioned report, stated ''No model to calculate the risk for all other solid cancer excluding breast and thyroid cancer risks is available from the LSS data''. Applying the LSS models for all solid cancers along with the models for the specific sites means that some cancers have an overlap in the risk evaluations. Thus, calculating the total solid cancer risk plus the breast cancer risk plus the thyroid cancer risk can overestimate the total risk by several per cent. Therefore, the purpose of this paper was to publish the required models for all other solid cancers, i.e. all solid cancers other than those types of cancer requiring special attention after a nuclear accident. The new models presented here have been fitted to the same LSS data set from which the risks provided by the WHO were derived. Although it is known already that the EAR and ERR effect modifications by sex are statistically significant for the outcome ''all solid cancer'', it is shown here that sex modification is not statistically significant for the outcome ''all solid cancer other than thyroid and breast cancer''. It is also shown here that the sex-averaged solid cancer risks with and without the sex modification are very similar once breast and thyroid cancers are factored out. Some other notable model differences between those already published for all solid cancers and those presented here for all other solid cancers are also given here. The models presented here can be used to improve on the methodology adopted by WHO after Fukushima and could contribute to emergency preparedness for future nuclear accidents. (orig.)

[en] A recent analysis of leukaemia mortality in Japanese A-bomb survivors has applied descriptive models, collected together from previous studies, to derive a joint excess relative risk estimate (ERR) by multi-model inference (MMI) (Walsh and Kaiser in Radiat Environ Biophys 50:21-35, 2011). The models use a linear-quadratic dose response with differing dose effect modifiers. In the present study, a set of more than 40 models has been submitted to a rigorous statistical selection procedure which fosters the parsimonious deployment of model parameters based on pairwise likelihood ratio tests. Nested models were consequently excluded from risk assessment. The set comprises models of the excess absolute risk (EAR) and two types of non-standard ERR models with sigmoidal responses or two line spline functions with a changing slope at a break point. Due to clearly higher values of the Akaike Information Criterion, none of the EAR models has been selected, but two non-standard ERR models qualified for MMI. The preferred ERR model applies a purely quadratic dose response which is slightly damped by an exponential factor at high doses and modified by a power function for attained age. Compared to the previous analysis, the present study reports similar point estimates and confidence intervals (CI) of the ERR from MMI for doses between 0.5 and 2.5 Sv. However, at lower doses, the point estimates are markedly reduced by factors between two and five, although the reduction was not statistically significant. The 2.5 % percentiles of the ERR from the preferred quadratic-exponential model did not fall below zero risk in exposure scenarios for children, adolescents and adults at very low doses down to 10 mSv. Yet, MMI produced risk estimates with a positive 2.5 % percentile only above doses of some 300 mSv. Compared to CI from a single model of choice, CI from MMI are broadened in cohort strata with low statistical power by a combination of risk extrapolations from several models. Reverting to MMI can relieve the dilemma of needing to choose between models with largely different consequences for risk assessment in public health. (orig.)

[en] An illustrative sample mission of a Mars swing-by mission lasting one calendar year was chosen to highlight the application of European risk assessment software to cancer (all solid cancer plus leukaemia) risks from radiation exposures in space quantified with organ dose equivalent rates from model calculations based on the quantity Radiation Attributed Decrease of Survival (RADS). The relevant dose equivalent to the colon for radiation exposures from this Mars swing-by mission were found to vary between 198 and 482 mSv. These doses depend on sex and the two other factors investigated here of: solar activity phase (maximum or minimum); and the choice of space radiation quality factor used in the calculations of dose equivalent. Such doses received at typical astronaut ages around 40 years old will result in: the probability of surviving until retirement age (65 years) being reduced by a range from 0.38% (95%CI: 0.29; 0.49) to 1.29% (95%CI: 1.06; 1.56); and the probability of surviving cancer free until retirement age being reduced by a range from 0.78% (95%CI: 0.59; 0.99) to 2.63% (95%CI: 2.16; 3.18). As expected from the features of the models applied to quantify the general dosimetric and radiation epidemiology parameters, the cancer incidence risks in terms of surviving cancer free, are higher than the cancer mortality risks in terms of surviving, the risks for females are higher than for males, and the risks at solar minimum are higher than at solar maximum.

[en] Purpose: Phenomenological risk models for radiation-induced cancer are frequently applied to estimate the risk of radiation-induced cancers at radiotherapy doses. Such models often include the effect modification, of the main risk to radiation dose response, by age at exposure and attained age. The aim of this paper is to compare the patterns in risk effect modification by age, between models obtained from the Japanese atomic-bomb (A-bomb) survivor data and models for cancer risks previously reported for radiotherapy patients. Patterns in risk effect modification by age from the epidemiological studies of radiotherapy patients were also used to refine and extend the risk effect modification by age obtained from the A-bomb survivor data, so that more universal models can be presented here. Methods: Simple log-linear and power functions of age for the risk effect modification applied in models of the A-bomb survivor data are compared to risks from epidemiological studies of second cancers after radiotherapy. These functions of age were also refined and fitted to radiotherapy risks. The resulting age models provide a refined and extended functional dependence of risk with age at exposure and attained age especially beyond 40 and 65 yr, respectively, and provide a better representation than the currently available simple age functions. Results: It was found that the A-bomb models predict risk similarly to the outcomes of testicular cancer survivors. The survivors of Hodgkin’s disease show steeper variations of risk with both age at exposure and attained age. The extended models predict solid cancer risk increase as a function of age at exposure beyond 40 yr and the risk decrease as a function of attained age beyond 65 yr better than the simple models. Conclusions: The standard functions for risk effect modification by age, based on the A-bomb survivor data, predict second cancer risk in radiotherapy patients for ages at exposure prior to 40 yr and attained ages before 55 yr reasonably well. However, for larger ages, the refined and extended models can be applied to predict the risk as a function of age