Lung Cancer in the Mayak Workers Cohort: Risk Estimation and Uncertainty Analysis.

The workers at the Mayak nuclear facility near Ozyorsk, Russia are a primary source of information about exposure to radiation at low-dose rates, since they were subject to protracted exposures to external gamma rays and to internal exposures from plutonium inhalation. Here we re-examine lung cancer mortality rates and assess the effects of external gamma and internal plutonium exposures using recently developed Monte Carlo dosimetry systems. Using individual lagged mean annual lung doses computed from the dose realizations, we fit excess relative risk (ERR) models to the lung cancer mortality data for the Mayak Workers Cohort using risk-modeling software. We then used the corrected-information matrix (CIM) approach to widen the confidence intervals of ERR by taking into account the uncertainty in doses represented by multiple realizations from the Monte Carlo dosimetry systems. Findings of this work revealed that there were 930 lung cancer deaths during follow-up. Plutonium lung doses (but not gamma doses) were generally higher in the new dosimetry systems than those used in the previous analysis. This led to a reduction in the risk per unit dose compared to prior estimates. The estimated ERR/Gy for external gamma-ray exposure was 0.19 (95% CI: 0.07 to 0.31) for both sexes combined, while the ERR/Gy for internal exposures based on mean plutonium doses were 3.5 (95% CI: 2.3 to 4.6) and 8.9 (95% CI: 3.4 to 14) for males and females at attained age 60. Accounting for uncertainty in dose had little effect on the confidence intervals for the ERR associated with gamma-ray exposure, but had a marked impact on confidence intervals, particularly the upper bounds, for the effect of plutonium exposure [adjusted 95% CIs: 1.5 to 8.9 for males and 2.7 to 28 for females]. In conclusion, lung cancer rates increased significantly with both external gamma-ray and internal plutonium exposures. Accounting for the effects of dose uncertainty markedly increased the width of the confidence intervals for the plutonium dose response but had little impact on the external gamma dose effect estimate. Adjusting risk estimate confidence intervals using CIM provides a solution to the important problem of dose uncertainty. This work demonstrates, for the first time, that it is possible and practical to use our recently developed CIM method to make such adjustments in a large cohort study.

Lung Cancer Risk from Plutonium: A Pooled Analysis of the Mayak and Sellafield Worker Cohorts.

In this study, lung cancer risk from occupational plutonium exposure was analyzed in a pooled cohort of Mayak and Sellafield workers, two of the most informative cohorts in the world with detailed plutonium urine monitoring programs. The pooled cohort comprised 45,817 workers: 23,443 Sellafield workers first employed during 1947-2002 with follow-up until the end of 2005 and 22,374 Mayak workers first employed during 1948-1982 with follow-up until the end of 2008. In the pooled cohort 1,195 lung cancer deaths were observed (789 Mayak, 406 Sellafield) but only 893 lung cancer incidences (509 Mayak, 384 Sellafield, due to truncated follow-up in the incidence analysis). Analyses were performed using Poisson regression models, and were based on doses derived from individual radiation monitoring data using an updated dose assessment methodology developed in the study. There was clear evidence of a linear association between cumulative internal plutonium lung dose and risk of both lung cancer mortality and incidence in the pooled cohort. The pooled point estimates of the excess relative risk (ERR) from plutonium exposure for both lung cancer mortality and incidence were within the range of 5-8 per Gy for males at age 60. The ERR estimates in relationship to external gamma radiation were also significantly raised and in the range 0.2-0.4 per Gy of cumulative gamma dose to the lung. The point estimates of risk, for both external and plutonium exposure, were comparable between the cohorts, which suggests that the pooling of these data was valid. The results support point estimates of relative biological effectiveness (RBE) in the range of 10-25, which is in broad agreement with the value of 20 currently adopted in radiological protection as the radiation weighting factor for alpha particles, however, the uncertainty on this value (RBE = 21; 95% CI: 9-178) is large. The results provide direct evidence that the plutonium risks in each cohort are of the same order of magnitude but the uncertainty on the Sellafield cohort plutonium risk estimates is large, with observed risks consistent with no plutonium risk, and risks five times larger than those observed in the Mayak cohort.

Correction of confidence intervals in excess relative risk models using Monte Carlo dosimetry systems with shared errors.

In epidemiological studies, exposures of interest are often measured with uncertainties, which may be independent or correlated. Independent errors can often be characterized relatively easily while correlated measurement errors have shared and hierarchical components that complicate the description of their structure. For some important studies, Monte Carlo dosimetry systems that provide multiple realizations of exposure estimates have been used to represent such complex error structures. While the effects of independent measurement errors on parameter estimation and methods to correct these effects have been studied comprehensively in the epidemiological literature, the literature on the effects of correlated errors, and associated correction methods is much more sparse. In this paper, we implement a novel method that calculates corrected confidence intervals based on the approximate asymptotic distribution of parameter estimates in linear excess relative risk (ERR) models. These models are widely used in survival analysis, particularly in radiation epidemiology. Specifically, for the dose effect estimate of interest (increase in relative risk per unit dose), a mixture distribution consisting of a normal and a lognormal component is applied. This choice of asymptotic approximation guarantees that corrected confidence intervals will always be bounded, a result which does not hold under a normal approximation. A simulation study was conducted to evaluate the proposed method in survival analysis using a realistic ERR model. We used both simulated Monte Carlo dosimetry systems (MCDS) and actual dose histories from the Mayak Worker Dosimetry System 2013, a MCDS for plutonium exposures in the Mayak Worker Cohort. Results show our proposed methods provide much improved coverage probabilities for the dose effect parameter, and noticeable improvements for other model parameters.

Mortality from solid cancers other than lung, liver, and bone in relation to external dose among plutonium and non-plutonium workers in the Mayak Worker Cohort.

Exposure to ionizing radiation has well-documented long-term effects on cancer rates and other health outcomes in humans. While in vitro experimental studies had demonstrated that the nature of some radiation effects depend on both total dose of the radiation and the dose rate (i.e., the pattern of dose distribution over time), the question of whether or not the carcinogenic effect of radiation exposure depends on the dose rate remains unanswered. Another issue of interest concerns whether or not concomitant exposure to external gamma rays and inhaled plutonium aerosols has any effect on the external exposure effects. The analyses of the present paper focus on the risk of solid cancers at sites other than lung, liver, and bone in Mayak workers. Recent findings are reviewed indicating that there is no evidence of plutonium dose response for these cancers in the Mayak worker cohort. Then the evidence for differences in the external dose effects among workers with and without the potential for exposure to alpha particles from inhaled plutonium is examined. It is found that there is no evidence that exposure to plutonium aerosols significantly affects the risk associated with external exposure. While the Mayak external dose risk estimate of an excess relative risk of 0.16 per Gy is somewhat lower than an appropriately normalized risk estimate from the Life Span Study of Japanese atomic bomb survivors, the uncertainties in these estimates preclude concluding that the external dose excess relative risks of this group of solid cancers differ in the two cohorts.

In utero exposure to radiation and haematological malignancies: pooled analysis of Southern Urals cohorts.

BACKGROUND: It is scientifically uncertain whether in utero exposure to low-dose ionising radiation increases the lifetime risk of haematological malignancies. METHODS: We pooled two cohorts from the Southern Urals comprising offspring of female workers of a large nuclear facility (the Mayak Production Association) and of women living in areas along the Techa River contaminated by nuclear accidents/waste from the same facility, with detailed dosimetry. RESULTS: The combined cohort totalled 19 536 subjects with 700 504 person-years at risk over the period of incidence follow-up, and slightly more over the period of mortality follow-up, yielding 58 incident cases and 36 deaths up to age 61 years. Risk was increased in subjects who received in utero doses of ⩾80 mGy (excess relative risk (ERR): 1.27; 95% confidence interval (CI): -0.20 to 4.71), and the risk increased consistently per 100 mGy of continuous exposure in utero (ERR: 0.77; CI: 0.02 to 2.56). No association was apparent in mortality-based analyses. Results for leukaemia and lymphoma were similar. A very weak positive association was observed between incidence and postnatal exposure. CONCLUSIONS: In summary, the results suggest a positive association between in utero exposure to ionising radiation and risk of haematological malignancies, but the small number of outcomes and inconsistent incidence and mortality findings preclude firm conclusions.

Estimates of Radiation Effects on Cancer Risks in the Mayak Worker, Techa River and Atomic Bomb Survivor Studies.

For almost 50 y, the Life Span Study cohort of atomic bomb survivor studies has been the primary source of the quantitative estimates of cancer and non-cancer risks that form the basis of international radiation protection standards. However, the long-term follow-up and extensive individual dose reconstruction for the Russian Mayak worker cohort (MWC) and Techa River cohort (TRC) are providing quantitative information about radiation effects on cancer risks that complement the atomic bomb survivor-based risk estimates. The MWC, which includes ~26 000 men and women who began working at Mayak between 1948 and 1982, is the primary source for estimates of the effects of plutonium on cancer risks and also provides information on the effects of low-dose rate external gamma exposures. The TRC consists of ~30 000 men and women of all ages who received low-dose-rate, low-dose exposures as a consequence of Mayak's release of radioactive material into the Techa River. The TRC data are of interest because the exposures are broadly similar to those experienced by populations exposed as a consequence of nuclear accidents such as Chernobyl. In this presentation, it is described the strengths and limitations of these three cohorts, outline and compare recent solid cancer and leukemia risk estimates and discussed why information from the Mayak and Techa River studies might play a role in the development and refinement of the radiation risk estimates that form the basis for radiation protection standards.

Incidence and Mortality of Solid Cancers in People Exposed In Utero to Ionizing Radiation: Pooled Analyses of Two Cohorts from the Southern Urals, Russia.

BACKGROUND: Previous studies have shown that acute external in utero exposure to ionizing radiation can increase cancer risk. It is not known whether chronic exposure at low dose rates, including due to radionuclide intake, influences the lifetime risk of solid cancers in the offspring. The objective of this study was to investigate solid cancer risk after in utero irradiation. METHODS: Cancer incidence and mortality over a 60-year period (from January 1950 to December 2009) were analyzed in the Urals Prenatally Exposed Cohort (UPEC). The cohort comprised in utero exposed offspring of Mayak Production Association female workers and of female residents of Techa River villages. Some of the offspring also received postnatal exposure, either due to becoming radiation workers themselves or due to continuing to live in the contaminated areas of the Techa River. The mortality analyses comprised 16,821 subjects (601,372 person-years), and the incidence analyses comprised 15,813 subjects (554,411 person-years). Poisson regression was used to quantify the relative risk as a function of the in utero soft tissue dose (with cumulative doses up to 944.9 mGy, mean dose of 14.1 mGy in the pooled cohort) and the postnatal stomach dose for solid cancer incidence and mortality. RESULTS: When a log-linear model was used, relative risk of cancer per 10 mGy of in utero dose was 0.99 (95% confidence interval (CI) = 0.96 to 1.01) based on incidence data and 0.98 (CI = 0.94 to 1.01) based on mortality data. Postnatal exposure to ionizing radiation was positively associated with the solid cancer risk in members of the UPEC, with a relative risk of 1.02 per 10mGy CI = 1.00 to 1.04). CONCLUSIONS: No strong evidence was found that chronic low-dose-rate exposure of the embryo and fetus increased the risk of solid cancers in childhood or in adulthood. For both incidence and mortality, a tendency towards a decreased relative risk was noted with increasing doses to soft tissues of the fetus. Further follow-up will provide more precise radiation risk estimates of solid cancer as cohort members are approaching their 60s and cancer becomes more common.

Beyond two-stage models for lung carcinogenesis in the Mayak workers: implications for plutonium risk.

Mechanistic multi-stage models are used to analyze lung-cancer mortality after Plutonium exposure in the Mayak-workers cohort, with follow-up until 2008. Besides the established two-stage model with clonal expansion, models with three mutation stages as well as a model with two distinct pathways to cancer are studied. The results suggest that three-stage models offer an improved description of the data. The best-fitting models point to a mechanism where radiation increases the rate of clonal expansion. This is interpreted in terms of changes in cell-cycle control mediated by bystander signaling or repopulation following cell killing. No statistical evidence for a two-pathway model is found. To elucidate the implications of the different models for radiation risk, several exposure scenarios are studied. Models with a radiation effect at an early stage show a delayed response and a pronounced drop-off with older ages at exposure. Moreover, the dose-response relationship is strongly nonlinear for all three-stage models, revealing a marked increase above a critical dose.

Shared dosimetry error in epidemiological dose-response analyses.

Radiation dose reconstruction systems for large-scale epidemiological studies are sophisticated both in providing estimates of dose and in representing dosimetry uncertainty. For example, a computer program was used by the Hanford Thyroid Disease Study to provide 100 realizations of possible dose to study participants. The variation in realizations reflected the range of possible dose for each cohort member consistent with the data on dose determinates in the cohort. Another example is the Mayak Worker Dosimetry System 2013 which estimates both external and internal exposures and provides multiple realizations of "possible" dose history to workers given dose determinants. This paper takes up the problem of dealing with complex dosimetry systems that provide multiple realizations of dose in an epidemiologic analysis. In this paper we derive expected scores and the information matrix for a model used widely in radiation epidemiology, namely the linear excess relative risk (ERR) model that allows for a linear dose response (risk in relation to radiation) and distinguishes between modifiers of background rates and of the excess risk due to exposure. We show that treating the mean dose for each individual (calculated by averaging over the realizations) as if it was true dose (ignoring both shared and unshared dosimetry errors) gives asymptotically unbiased estimates (i.e. the score has expectation zero) and valid tests of the null hypothesis that the ERR slope ß is zero. Although the score is unbiased the information matrix (and hence the standard errors of the estimate of ß) is biased for ß≠0 when ignoring errors in dose estimates, and we show how to adjust the information matrix to remove this bias, using the multiple realizations of dose. The use of these methods in the context of several studies including, the Mayak Worker Cohort, and the U.S. Atomic Veterans Study, is discussed.

Radiation effects on mortality from solid cancers other than lung, liver, and bone cancer in the Mayak worker cohort: 1948-2008.

Radiation effects on mortality from solid cancers other than lung, liver, and bone cancer in the Mayak worker cohort: 1948-2008. The cohort of Mayak Production Association (PA) workers in Russia offers a unique opportunity to study the effects of prolonged low dose rate external gamma exposures and exposure to plutonium in a working age population. We examined radiation effects on the risk of mortality from solid cancers excluding sites of primary plutonium deposition (lung, liver, and bone surface) among 25,757 workers who were first employed in 1948-1982. During the period 1948-2008, there were 1,825 deaths from cancers other than lung, liver and bone. Using colon dose as a representative external dose, a linear dose response model described the data well. The excess relative risk per Gray for external gamma exposure was 0.16 (95% CI: 0.07 - 0.26) when unadjusted for plutonium exposure and 0.12 (95% CI 0.03 - 0.21) when adjusted for plutonium dose and monitoring status. There was no significant effect modification by sex or attained age. Plutonium exposure was not significantly associated with the group of cancers analyzed after adjusting for monitoring status. Site-specific risks were uncertainly estimated but positive for 13 of the 15 sites evaluated with a statistically significant estimate only for esophageal cancer. Comparison with estimates based on the acute exposures in atomic bomb survivors suggests that the excess relative risk per Gray for prolonged external exposure in Mayak workers may be lower than that for acute exposure but, given the uncertainties, the possibility of equal effects cannot be dismissed.

Possible expressions of radiation-induced genomic instability, bystander effects or low-dose hypersensitivity in cancer epidemiology.

Recent publications on the integration of radiobiological effects in the two-step clonal expansion (TSCE) model of carcinogenesis and applications to radioepidemiological data are reviewed and updated. First, a model version with radiation-induced genomic instability was shown to be a possible explanation for the age dependence of the radiation-induced cancer mortality in the Techa River Cohort. Second, it is demonstrated that inclusion of a bystander effect with a dose threshold allows an improved description of the lung cancer mortality risk for the Mayak workers cohort due to incorporation of plutonium. The threshold for the annual lung dose is estimated to 12 (90%CI: 4; 14)mGy/year. This threshold applies to the initiation of preneoplastic cells and to hyperplastic growth. There is, however, no evidence for a threshold for the effects of gamma radiation. Third, models with radiation-induced cell inactivation tend to predict lower cancer risks among the atomic bomb survivors with exposure at young age than conventionally used empirical models. Also, risks after exposures with doses in the order of 100mGy are predicted to be higher in models with low-dose hypersensitivity than in models with conventional cell survival curves. In the reviewed literature, models of carcinogenesis tend to describe radioepidemiological data better than conventionally used empirical models.

Lung, liver and bone cancer mortality in Mayak workers.

Workers at the Mayak nuclear facility in the Russian Federation offer the only adequate human data for evaluating cancer risks from exposure to plutonium. Risks of mortality from cancers of the lung, liver and bone, the organs receiving the largest doses from plutonium, were evaluated in a cohort of 17,740 workers initially hired 1948-1972 using, for the first time, recently improved individual organ dose estimates. Excess relative risk (ERR) models were used to evaluate risks as functions of internal (plutonium) dose, external (primarily gamma) dose, gender, attained age and smoking. By December 31, 2003, 681 lung cancer deaths, 75 liver cancer deaths and 30 bone cancer deaths had occurred. Of these 786 deaths, 239 (30%) were attributed to plutonium exposure. Significant plutonium dose-response relationships (p < 0.001) were observed for all 3 endpoints, with lung and liver cancer risks reasonably described by linear functions. At attained age 60, the ERRs per Gy for lung cancer were 7.1 for males and 15 for females; the averaged-attained age ERRs for liver cancer were 2.6 and 29 for males and females, respectively; those for bone cancer were 0.76 and 3.4. This study is the first to present and compare dose-response analyses for cancers of all 3 organs. The unique Mayak cohort with its high exposures and well characterized doses has allowed quantification of the plutonium dose-response for lung, liver and bone cancer risks based on direct human data. These results will play an important role in plutonium risk assessment.