Multi-model inference of adult and childhood leukaemia excess relative risks based on the Japanese A-bomb survivors mortality data (1950–2000)

Some relatively new issues that augment the usual practice of ignoring model uncertainty, when making inference about parameters of a specific model, are brought to the attention of the radiation protection community here. Nine recently published leukaemia risk models, developed with the Japanese A-bomb epidemiological mortality data, have been included in a model-averaging procedure so that the main conclusions do not depend on just one type of model or statistical test. The models have been centred here at various adult and young ages at exposure, for some short times since exposure, in order to obtain specially computed childhood Excess Relative Risks (ERR) with uncertainties that account for correlations in the fitted parameters associated with the ERR dose–response. The model-averaged ERR at 1 Sv was not found to be statistically significant for attained ages of 7 and 12 years but was statistically significant for attained ages of 17, 22 and 55 years. Consequently, such risks when applied to other situations, such as children in the vicinity of nuclear installations or in estimates of the proportion of childhood leukaemia incidence attributable to background radiation (i.e. low doses for young ages and short times since exposure), are only of very limited value, with uncertainty ranges that include zero risk. For example, assuming a total radiation dose to a 5-year-old child of 10 mSv and applying the model-averaged risk at 10 mSv for a 7-year-old exposed at 2 years of age would result in an ERR = 0.33, 95% CI: −0.51 to 1.22. One model (United Nations scientific committee on the effects of atomic radiation report. Volume 1. Annex A: epidemiological studies of radiation and cancer, United Nations, New York, 2006) weighted model-averaged risks of leukaemia most strongly by half of the total unity weighting and is recommended for application in future leukaemia risk assessments that continue to ignore model uncertainty. However, on the basis of the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.     

Cancer mortality risk among workers at the Mayak nuclear complex

At present, direct data on risk from protracted or fractionated radiation exposure at low dose rates have been limited largely to studies of populations exposed to low cumulative doses with resulting low statistical power. We evaluated the cancer risks associated with protracted exposure to external whole-body gamma radiation at high cumulative doses (the average dose is 0.8 Gy and the highest doses exceed 10 Gy) in Russian nuclear workers. Cancer deaths in a cohort of about 21,500 nuclear workers who began working at the Mayak complex between 1948 and 1972 were ascertained from death certificates and autopsy reports with follow-up through December 1997. Excess relative risk models were used to estimate solid cancer and leukemia risks associated with external gamma-radiation dose with adjustment for effects of plutonium exposures. Both solid cancer and leukemia death rates increased significantly with increasing gamma-ray dose (P < 0.001). Under a linear dose-response model, the excess relative risk for lung, liver and skeletal cancers as a group (668 deaths) adjusted for plutonium exposure is 0.30 per gray (P < 0.001) and 0.08 per gray (P < 0.001) for all other solid cancers (1062 deaths). The solid cancer dose-response functions appear to be nonlinear, with the excess risk estimates at doses of less than 3 Gy being about twice those predicted by the linear model. Plutonium exposure was associated with increased risks both for lung, liver and skeletal cancers (the sites of primary plutonium deposition) and for other solid cancers as a group. A significant dose response, with no indication of plutonium exposure effects, was found for leukemia. Excess risks for leukemia exhibited a significant dependence on the time since the dose was received. For doses received within 3 to 5 years of death the excess relative risk per gray was estimated to be about 7 (P < 0.001), but this risk was only 0.45 (P = 0.02) for doses received 5 to 45 years prior to death. External gamma-ray exposures significantly increased risks of both solid cancers and leukemia in this large cohort of men and women with occupational radiation exposures. Risks at doses of less than 1 Gy may be slightly lower than those seen for doses arising from acute exposures in the atomic bomb survivors. As dose estimates for the Mayak workers are improved, it should be possible to obtain more precise estimates of solid cancer and leukemia risks from protracted external radiation exposure in this cohort.     

Radiation effects on breast cancer risk: a pooled analysis of eight cohorts

Breast cancer incidence rates after radiation exposure in eight large cohorts are described and compared. The nature of the exposures varies appreciably, ranging from a single or a small number of high-dose-rate exposures (Japanese atomic bomb survivors, U.S. acute post-partum mastitis patients, Swedish benign breast disease patients, and U.S. infants with thymic enlargement) to highly fractionated high-dose-rate exposures (two U.S. tuberculosis cohorts) and protracted low-dose-rate exposure (two Swedish skin hemangioma cohorts). There were 1,502 breast cancers among 77,527 women (about 35,000 of whom were exposed) with 1.8 million woman-years of follow-up. The excess risk depends linearly on dose with a downturn at high doses. No simple unified summary model adequately describes the excess risks in all groups. Excess risks for the thymus, tuberculosis, and atomic bomb survivor cohorts have similar temporal patterns, depending on attained age for relative risk models and on both attained age and age at exposure for excess rate models. Excess rates were similar in these cohorts, whereas, related in part to the low breast cancer background rates for Japanese women, the excess relative risk per unit dose in the bomb survivors was four times that in the tuberculosis or thymus cohorts. Excess rates were higher for the mastitis and benign breast disease cohorts. The hemangioma cohorts showed lower excess risks suggesting ameliorating dose-rate effects for protracted low-dose-rate exposures. For comparable ages at exposure (approximately 0.5 years), the excess risk in the hemangioma cohorts was about one-seventh that in the thymus cohort, whose members received acute high-dose-rate exposures. The results support the linearity of the radiation dose response for breast cancer, highlight the importance of age and age at exposure on the risks, and suggest a similarity in risks for acute and fractionated high-dose-rate exposures with much smaller effects from low-dose-rate protracted exposures. There is also a suggestion that women with some benign breast conditions may be at elevated risk of radiation-associated breast cancer.     

Monte Carlo mixture model of lifetime cancer incidence risk from radiation exposure on shuttle and international space station

Estimating uncertainty in lifetime cancer risk for human exposure to space radiation is a unique challenge. Conventional risk assessment with low-linear-energy-transfer (LET)-based risk from Japanese atomic bomb survivor studies may be inappropriate for relativistic protons and nuclei in space due to track structure effects. This paper develops a Monte Carlo mixture model (MCMM) for transferring additive, National Institutes of Health multiplicative, and multiplicative excess cancer incidence risks based on Japanese atomic bomb survivor data to determine excess incidence risk for various US astronaut exposure profiles. The MCMM serves as an anchor point for future risk projection methods involving biophysical models of DNA damage from space radiation. Lifetime incidence risks of radiation-induced cancer for the MCMM based on low-LET Japanese data for nonleukemia (all cancers except leukemia) were 2.77 (90% confidence limit, 0.75-11.34) for males exposed to 1 Sv at age 45 and 2.20 (90% confidence limit, 0.59-10.12) for males exposed at age 55. For females, mixture model risks for nonleukemia exposed separately to 1 Sv at ages of 45 and 55 were 2.98 (90% confidence limit, 0.90-11.70) and 2.44 (90% confidence limit, 0.70-10.30), respectively. Risks for high-LET 200 MeV protons (LET=0.45 keV/micrometer), 1 MeV alpha-particles (LET=100 keV/micrometer), and 600 MeV iron particles (LET=180 keV/micrometer) were scored on a per particle basis by determining the particle fluence required for an average of one particle per cell nucleus of area 100 micrometer(2). Lifetime risk per proton was 2.68x10(-2)% (90% confidence limit, 0.79x10(-3)%-0. 514x10(-2)%). For alpha-particles, lifetime risk was 14.2% (90% confidence limit, 2.5%-31.2%). Conversely, lifetime risk per iron particle was 23.7% (90% confidence limit, 4.5%-53.0%). Uncertainty in the DDREF for high-LET particles may be less than that for low-LET radiation because typically there is very little dose-rate dependence. Probability density functions for high-LET radiation quality and dose-rate may be preferable to conventional risk assessment approaches. Nuclear reactions and track structure effects in tissue may not be properly estimated by existing data using in vitro models for estimating RBEs. The method used here is being extended to estimate uncertainty in spacecraft shielding effectiveness in various space radiation environments.     

Lung cancer risk of Mayak workers: modelling of carcinogenesis and bystander effect

Lung cancer mortality in the period of 1948-2002 has been analysed for 6,293 male workers of the Mayak Production Association, for whose information on smoking, annual external doses and annual lung doses due to plutonium exposures was available. Individual likelihoods were maximized for the two-stage clonal expansion (TSCE) model of carcinogenesis and for an empirical risk model. Possible detrimental and protective bystander effects on mutation and malignant transformation rates were taken into account in the TSCE model. Criteria for non-nested models were used to evaluate the quality of fit. Data were found to be incompatible with the model including a detrimental bystander effect. The model with a protective bystander effect did not improve the quality of fit over models without a bystander effect. The preferred TSCE model was sub-multiplicative in the risks due to smoking and internal radiation, and more than additive. Smoking contributed 57% to the lung cancer deaths, the interaction of smoking and radiation 27%, radiation 10%, and others cause 6%. An assessment of the relative biological effectiveness of plutonium was consistent with the ICRP recommended value of 20. At age 60 years, the excess relative risk (ERR) per lung dose was 0.20 (95% CI: 0.13; 0.40) Sv(-1), while the excess absolute risk (EAR) per lung dose was 3.2 (2.0; 6.2) per 10(4) PY Sv. With increasing age attained the ERR decreased and the EAR increased. In contrast to the atomic bomb survivors, a significant elevated lung cancer risk was also found for age attained younger than 55 years. For cumulative lung doses below 5 Sv, the excess risk depended linearly on dose. The excess relative risk was significantly lower in the TSCE model for ages attained younger than 55 than that in the empirical model. This reflects a model uncertainty in the results, which is not expressed by the standard statistical uncertainty bands.     

A short review of model selection techniques for radiation epidemiology

A common type of statistical challenge, widespread across many areas of research, involves the selection of a preferred model to describe the main features and trends in a particular data set. The objective of model selection is to balance the quality of fit to data against the complexity and predictive ability of the model achieving that fit. Several model selection techniques, including two information criteria, which aim to determine which set of model parameters the data best support, are reviewed here. The techniques rely on computing the probabilities of the different models, given the data, rather than considering the allowed values of the fitted parameters. Such information criteria have only been applied to the field of radiation epidemiology recently, even though they have longer traditions of application in other areas of research. The purpose of this review is to make two information criteria more accessible by fully detailing how to calculate them in a practical way and how to interpret the resulting values. This aim is supported with the aid of some examples involving the computation of risk models for radiation-induced solid cancer mortality fitted to the epidemiological data from the Japanese A-bomb survivors. These examples illustrate that the Bayesian information criterion is particularly useful in concluding that the weight of evidence is in favour of excess relative risk models that depend on age-at-exposure and excess relative risk models that depend on age-attained.     

A method for determining weights for excess relative risk and excess absolute risk when applied in the calculation of lifetime risk of cancer from radiation exposure

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.     

Neutron relative biological effectiveness for solid cancer incidence in the Japanese A-bomb survivors: an analysis considering the degree of independent effects from γ-ray and neutron absorbed doses with hierarchical partitioning

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.     

Studies of the mortality of atomic bomb survivors. report 12, part I. Cancer: 1950-1990

This continues the series of periodic general reports on cancer mortality in the cohort of A-bomb survivors followed by the Radiation Effects Research Foundation. The follow-up is extended by the 5 years 1986-1990, and analysis includes an additional 10,500 survivors with recently estimated radiation doses. Together these extensions add about 550,000 person-years of follow-up. The cohort analyzed consists of 86,572 subjects, of which about 60% have dose estimates of at least 0.005 Sv. During 1950-1990 there have been 3086 and 4741 cancer deaths for the less than and greater than 0.005 Sv groups, respectively. It is estimated that among these there have been approximately 420 excess cancer deaths during 1950-1990, of which about 85 were due to leukemia. For cancers other than leukemia (solid cancers), about 25% of the excess deaths in 1950-1990 occurred during the last 5 years; for those exposed as children this figure is nearly 50%. For leukemia only about 3% of the excess deaths in 1950-1990 occurred in the last 5 years. Whereas most of the excess for leukemia occurred in the first 15 years after exposure, for solid cancers the pattern of excess risk is apparently more like a life-long elevation of the natural age-specific cancer risk. Taking advantage of the lengthening follow-up, increased attention is given to clarifying temporal patterns of the excess cancer risk. Emphasis is placed on describing these patterns in terms of absolute excess risk, as well as relative risk. For example: (a) although it is becoming clearer that the excess relative risk for those exposed as children has declined over the follow-up, the excess absolute risk has increased rapidly with time; and (b) although the excess relative risk at a given age depends substantially on sex and age at exposure, the age-specific excess absolute risk depends little on these factors. The primary estimates of excess risk are now given as specific to sex and age at exposure, and these include projections of dose-specific lifetime risks for this cohort. The excess lifetime risk per sievert for solid cancers for those exposed at age 30 is estimated at 0.10 and 0.14 for males and females, respectively. Those exposed at age 50 have about one-third these risks. Projection of lifetime risks for those exposed at age 10 is more uncertain. Under a reasonable set of assumptions, estimates for this group range from about 1.0-1.8 times the estimates for those exposed at age 30. The excess life-time risk for leukemia at 1 Sv for those exposed at either 10 or 30 years is estimated as about 0.015 and 0.008 for males and females, respectively. Those exposed at age 50 have about two-thirds that risk. Excess risks for solid cancer appear quite linear up to about 3 Sv, but for leukemia apparent nonlinearity in dose results in risks at 0.1 Sv estimated at about 1/20 of those for 1.0 Sv. Site-specific risk estimates are given, but it is urged that great care be taken in interpreting these, because most of their variation can be explained simply by imprecision in the estimates.     

Lung Cancer Mortality (1950-1999) among Eldorado Uranium Workers: A Comparison of Models of Carcinogenesis and Empirical Excess Risk Models

Lung cancer mortality after exposure to radon decay products (RDP) among 16,236 male Eldorado uranium workers was analyzed. Male workers from the Beaverlodge and Port Radium uranium mines and the Port Hope radium and uranium refinery and processing facility who were first employed between 1932 and 1980 were followed up from 1950 to 1999. A total of 618 lung cancer deaths were observed. The analysis compared the results of the biologically-based two-stage clonal expansion (TSCE) model to the empirical excess risk model. The spontaneous clonal expansion rate of pre-malignant cells was reduced at older ages under the assumptions of the TSCE model. Exposure to RDP was associated with increase in the clonal expansion rate during exposure but not afterwards. The increase was stronger for lower exposure rates. A radiation-induced bystander effect could be a possible explanation for such an exposure response. Results on excess risks were compared to a linear dose-response parametric excess risk model with attained age, time since exposure and dose rate as effect modifiers. In all models the excess relative risk decreased with increasing attained age, increasing time since exposure and increasing exposure rate. Large model uncertainties were found in particular for small exposure rates.     

Incidence of cancer among Finnish airline cabin attendants, 1967-92.

OBJECTIVE--To assess whether occupational exposure among commercial airline cabin attendants are associated with risk of cancer. DESIGN--Record linkage study. SETTING--Finland. SUBJECTS-1577 female and 187 male cabin attendants who had worked for the Finnish airline companies. MAIN OUTCOME MEASURE--Standardised incidence ratio; expected number of cases based on national cancer incidences. RESULTS--A significant excess of breast cancer (standardised incidence ratio 1.87 (95% confidence interval 1.15 to 2.23)) and bone cancer (15.10 (1.82 to 54.40)) was found among female workers. The risk of breast cancer was most prominent 15 years after recruitment. Risks of leukaemia (3.57 (0.43 to 12.9)) and skin melanoma (2.11 (0.43 to 6.15) were not significantly raised. Among men, one lymphoma and one Kaposi''s sarcoma were found (expected number of cases 1.6). CONCLUSIONS--Although the lifestyle of cabin attendants is different from that of the reference population--for example, in terms of social status and parity--concentration of the excess risks to primary sites sensitive to radiation suggests that ionising radiation during flights may add to the cancer risk of all flight personnel. Otherwise the lifestyle of cabin attendants did not seem to affect their risks of cancer. Estimates of the effect of reproductive risk factors only partly explained the increased risk of breast cancer. If present estimates of health hazards due to radiation are also valid for cosmic radiation, then the radiation doses of cabin attendants seem too small to account entirely for the observed excess risk.     

A Bayesian hierarchical approach to account for left-censored and missing radiation doses prone to classical measurement error when analyzing lung cancer mortality due to γ-ray exposure in the French cohort of uranium miners

Epidemiological data on cohorts of occupationally exposed uranium miners are currently used to assess health risks associated with chronic exposure to low doses of ionizing radiation. Nevertheless, exposure uncertainty is ubiquitous and questions the validity of statistical inference in these cohorts. This paper highlights the flexibility and relevance of the Bayesian hierarchical approach to account for both missing and left-censored (i.e. only known to be lower than a fixed detection limit) radiation doses that are prone to measurement error, when estimating radiation-related risks. Up to the authors’ knowledge, this is the first time these three sources of uncertainty are dealt with simultaneously in radiation epidemiology. To illustrate the issue, this paper focuses on the specific problem of accounting for these three sources of uncertainty when estimating the association between occupational exposure to low levels of γ-radiation and lung cancer mortality in the post-55 sub-cohort of French uranium miners. The impact of these three sources of dose uncertainty is of marginal importance when estimating the risk of death by lung cancer among French uranium miners. The corrected excess hazard ratio (EHR) is 0.81 per 100 mSv (95% credible interval: [0.28; 1.75]). Interestingly, even if the 95% credible interval of the corrected EHR is wider than the uncorrected one, a statistically significant positive association remains between γ-ray exposure and the risk of death by lung cancer, after accounting for dose uncertainty. Sensitivity analyses show that the results obtained are robust to different assumptions. Because of its flexible and modular nature, the Bayesian hierarchical models proposed in this work could be easily extended to account for high proportions of missing and left-censored dose values or exposure data, prone to more complex patterns of measurement error.

     

Environmental Risks at Finnish Shooting Ranges—A Case Study

We studied three Finnish shooting ranges in order to define the extent of the risks associated with elevated environmental concentrations of metals and PAHs. A scoring system revealed that lead, arsenic, and antimony were the most critical contaminants. On Site 3, the concentration of lead in groundwater exceeded the drinking water standard indicating evident health risks. For the remaining two sites we calculated Acceptable Daily Doses (ADD) based on the Reasonable Maximum Exposure (RME) approach and compared them with safe exposure levels. We also used a pharmacokinetic model to determine blood lead levels (PbBs). Risks to biota were assessed using ecological benchmarks and exposure and accumulation models. Prediction of leaching was based on laboratory tests and a distribution model. The health risk assessment for lead resulted in the maximum hazard quotient (HQ) of 1.2 whereas the HQs of As and Sb remained less than 1. Some exposure scenarios produced PbB estimates exceeding 10 μ g dl^?1 but based on the uncertainty analysis we expect the health risks to remain insignificant. However, leaching of contaminants presents a risk to groundwater quality. At site 1 the ecotoxicity-based HQs demonstrate high risks to soil biota, small mammals, terrestrial plants and aquatic organisms.     

Predicted cancer risks induced by computed tomography examinations during childhood,by a quantitative risk assessment approach

The potential adverse effects associated with exposure to ionizing radiation from computed tomography (CT) in pediatrics must be characterized in relation to their expected clinical benefits. Additional epidemiological data are, however, still awaited for providing a lifelong overview of potential cancer risks. This paper gives predictions of potential lifetime risks of cancer incidence that would be induced by CT examinations during childhood in French routine practices in pediatrics. Organ doses were estimated from standard radiological protocols in 15 hospitals. Excess risks of leukemia, brain/central nervous system, breast and thyroid cancers were predicted from dose–response models estimated in the Japanese atomic bomb survivors’ dataset and studies of medical exposures. Uncertainty in predictions was quantified using Monte Carlo simulations. This approach predicts that 100,000 skull/brain scans in 5-year-old children would result in eight (90 % uncertainty interval (UI) 1–55) brain/CNS cancers and four (90 % UI 1–14) cases of leukemia and that 100,000 chest scans would lead to 31 (90 % UI 9–101) thyroid cancers, 55 (90 % UI 20–158) breast cancers, and one (90 % UI <0.1–4) leukemia case (all in excess of risks without exposure). Compared to background risks, radiation-induced risks would be low for individuals throughout life, but relative risks would be highest in the first decades of life. Heterogeneity in the radiological protocols across the hospitals implies that 5–10 % of CT examinations would be related to risks 1.4–3.6 times higher than those for the median doses. Overall excess relative risks in exposed populations would be 1–10 % depending on the site of cancer and the duration of follow-up. The results emphasize the potential risks of cancer specifically from standard CT examinations in pediatrics and underline the necessity of optimization of radiological protocols.     

A reanalysis of liver cancer incidence in Danish patients administered thorotrast using a two-mutation carcinogenesis model

In recent years, a two-mutation carcinogenesis (TMC) model has been used to analyze epidemiological data and estimate the radiation risks at low doses for the organs affected. Here the TMC model was used to reanalyze the liver cancer incidence in the Danish population in general and in patients administered Thorotrast, and to estimate the radiation risks for the liver. The data for 807 patients for whom sufficient data on the injected volumes of Thorotrast were available were used in this reanalysis. These data were combined with data on liver cancer incidence in the Danish population as the baseline or background incidence. Because males and females show different baseline liver cancer incidences, separate fits were made for males and females. The fits showed that the radiation effect could be ascribed entirely to the radiation dependence of the first mutation rate of the TMC model, which was higher for females than for males. The second mutation rate was not significantly dependent on dose. The radiation risks for the liver were calculated on the basis of the model parameters. These risks for lifetime exposures are about the same for males and females and are between a factor of 2 and 10 higher than current estimates. The discrepancy between the model results and previous risk estimates probably arises because the model calculations give more complete lifetime radiation risk estimates. For short-term exposures of the liver to ionizing radiation, the maximum radiation-induced excess liver cancer risk per unit dose applies to exposures at the age of about 10; exposures at ages above 35 have a radiation effect of less than approximately 15% of this maximum.     

Treatments of Uncertainty and Variability in Ecological Risk Assessment of Single-Species Populations

The selection of the most appropriate model for an ecological risk assessment depends on the application, the data and resources available, the knowledge base of the assessor, the relevant endpoints, and the extent to which the model deals with uncertainty. Since ecological systems are highly variable and our knowledge of model input parameters is uncertain, it is important that models include treatments of uncertainty and variability, and that results are reported in this light. In this paper we discuss treatments of variation and uncertainty in a variety of population models. In ecological risk assessments, the risk relates to the probability of an adverse event in the context of environmental variation. Uncertainty relates to ignorance about parameter values, e.g., measurement error and systematic error. An assessment of the full distribution of risks, under variability and parameter uncertainty, will give the most comprehensive and flexible endpoint. In this paper we present the rationale behind probabilistic risk assessment, identify the sources of uncertainty relevant for risk assessment and provide an overview of a range of population models. While all of the models reviewed have some utility in ecology, some have more comprehensive treatments of uncertainty than others. We identify the models that allow probabilistic assessments and sensitivity analyses, and we offer recommendations for further developments that aim towards more comprehensive and reliable ecological risk assessments for populations.     

Solid cancer incidence in atomic bomb survivors: 1958-1998

This is the second general report on radiation effects on the incidence of solid cancers (cancers other than malignancies of the blood or blood-forming organs) among members of the Life Span Study (LSS) cohort of Hiroshima and Nagasaki atomic bomb survivors. The analyses were based on 17,448 first primary cancers (including non-melanoma skin cancer) diagnosed from 1958 through 1998 among 105,427 cohort members with individual dose estimates who were alive and not known to have had cancer prior to 1958. Radiation-associated relative risks and excess rates were considered for all solid cancers as a group, for 19 specific cancer sites or groups of sites, and for five histology groups. Poisson regression methods were used to investigate the magnitude of the radiation-associated risks, the shape of the dose response, how these risks vary with gender, age at exposure, and attained age, and the evidence for inter-site variation in the levels and patterns of the excess risk. For all solid cancers as a group, it was estimated that about 850 (about 11%) of the cases among cohort members with colon doses in excess of 0.005 Gy were associated with atomic bomb radiation exposure. The data were consistent with a linear dose response over the 0- to 2-Gy range, while there was some flattening of the dose response at higher doses. Furthermore, there is a statistically significant dose response when analyses were limited to cohort members with doses of 0.15 Gy or less. The excess risks for all solid cancers as a group and many individual sites exhibit significant variation with gender, attained age, and age at exposure. It was estimated that, at age 70 after exposure at age 30, solid cancer rates increase by about 35% per Gy (90% CI 28%; 43%) for men and 58% per Gy (43%; 69%) for women. For all solid cancers as a group, the excess relative risk (ERR per Gy) decreases by about 17% per decade increase in age at exposure (90% CI 7%; 25%) after allowing for attained-age effects, while the ERR decreased in proportion to attained age to the power 1.65 (90% CI 2.1; 1.2) after allowing for age at exposure. Despite the decline in the ERR with attained age, excess absolute rates appeared to increase throughout the study period, providing further evidence that radiation-associated increases in cancer rates persist throughout life regardless of age at exposure. For all solid cancers as a group, women had somewhat higher excess absolute rates than men (F:M ratio 1.4; 90% CI 1.1; 1.8), but this difference disappears when the analysis was restricted to non-gender-specific cancers. Significant radiation-associated increases in risk were seen for most sites, including oral cavity, esophagus, stomach, colon, liver, lung, non-melanoma skin, breast, ovary, bladder, nervous system and thyroid. Although there was no indication of a statistically significant dose response for cancers of the pancreas, prostate and kidney, the excess relative risks for these sites were also consistent with that for all solid cancers as a group. Dose-response estimates for cancers of the rectum, gallbladder and uterus were not statistically significant, and there were suggestions that the risks for these sites may be lower than those for all solid cancers combined. However, there was emerging evidence from the present data that exposure as a child may increase risks of cancer of the body of the uterus. Elevated risks were seen for all of the five broadly classified histological groups considered, including squamous cell carcinoma, adenocarcinoma, other epithelial cancers, sarcomas and other non-epithelial cancers. Although the data were limited, there was a significant radiation-associated increase in the risk of cancer occurring in adolescence and young adulthood. In view of the persisting increase in solid cancer risks, the LSS should continue to provide important new information on radiation exposure and solid cancer risks for at least another 15 to 20 years.     

Flexible dose-response models for Japanese atomic bomb survivor data: Bayesian estimation and prediction of cancer risk

Generalised absolute risk models were fitted to the latest Japanese atomic bomb survivor cancer incidence data using Bayesian Markov Chain Monte Carlo methods, taking account of random errors in the DS86 dose estimates. The resulting uncertainty distributions in the relative risk model parameters were used to derive uncertainties in population cancer risks for a current UK population. Because of evidence for irregularities in the low-dose dose response, flexible dose-response models were used, consisting of a linear-quadratic-exponential model, used to model the high-dose part of the dose response, together with piecewise-linear adjustments for the two lowest dose groups. Following an assumed administered dose of 0.001 Sv, lifetime leukaemia radiation-induced incidence risks were estimated to be 1.11 x 10(-2) Sv(-1) (95% Bayesian CI -0.61, 2.38) using this model. Following an assumed administered dose of 0.001 Sv, lifetime solid cancer radiation-induced incidence risks were calculated to be 7.28 x 10(-2) Sv(-1) (95% Bayesian CI -10.63, 22.10) using this model. Overall, cancer incidence risks predicted by Bayesian Markov Chain Monte Carlo methods are similar to those derived by classical likelihood-based methods and which form the basis of established estimates of radiation-induced cancer risk.     

Risk coefficient for gamma-rays with regard to solid cancer

A previous investigation has uncoupled the solid cancer risk coefficient for neutrons from the low dose estimates of the relative biological effectiveness (RBE) of neutrons and the photon risk coefficient, and has related it to two more tangible quantities, the excess relative risk (ERR1) due to an intermediate reference dose D1 = 1 Gy of gamma-rays and the RBE of neutrons, R1, against this reference dose. With tentatively assumed RBE values between 20 and 50 and in terms of organ-averaged doses--rather than the usually invoked colon doses--the neutron risk factor was seen to be in general agreement with the current risk estimate of the International Commission on Radiation Protection (ICRP). The present assessment of the risk coefficient for gamma-rays incorporates--in terms of the unchanged A-bomb dosimetry system, DS86--this treatment of the neutrons, but is otherwise largely analogous to the evaluation of the A-bomb data for the ICRP report and for the recent report of the United Nations Scientific Committee on the effects of ionizing radiation, UNSCEAR. The resulting central estimate of the lifetime attributable risk (LAR) for solid cancer mortality is 0.043/Gy for a working population (ages 25-65), and is nearly the same whether the age at exposure or the attained age model is used for risk projection. For a population of all ages 0.042/Gy is obtained with the attained age model and 0.068/Gy with the age at exposure model. The values do not include a dose and dose rate effectiveness factor (DDREF), and they are only half as large as the new UNSCEAR estimates of 0.082/Gy (attained age model and all ages) and 0.13/Gy (age at exposure model and all ages). The difference is only partly due to the more explicit treatment of the neutrons. It reflects also the fact that UNSCEAR has converted ERR into LAR in a way that differs from the ICRP procedure, and that it has summed the overall risk coefficient for solid tumor mortality and incidence from separate estimates for eight solid tumor categories, whereas the present study employs a combined computation for all solid tumors and uses the ICRP procedure for the conversion of ERR into LAR. The appendix gives results for the solid cancer incidence data.