Markus Eidemüller

Breast cancer risk among Swedish hemangioma patients and possible consequences of radiation-induced genomic instability.

Breast cancer incidence among 17,158 female Swedish hemangioma patients was analyzed with empirical excess relative risk models and with a biologically-based model of carcinogenesis. The patients were treated in infancy mainly by external application of radium-226. The mean and median absorbed doses to the breast were 0.29 and 0.04Gy, and a total of 678 breast cancer cases have been observed. Both models agree very well in the risk estimates with an excess relative risk and excess absolute risk at the age of 50 years, about the mean age of breast cancer incidence, of 0.25Gy(-1)(95% CI 0.14; 0.37) and 30.7 (10(5) BYR Gy)(-1) (95% CI 16.9; 42.8), respectively. Models incorporating effects of radiation-induced genomic instability were developed and applied to the hemangioma cohort. The biologically-based description of the radiation risk was significantly improved with a model of genomic instability at an early stage of carcinogenesis.

Breast cancer risk and possible mechanisms of radiation-induced genomic instability in the Swedish hemangioma cohort after reanalyzed dosimetry

The cohort of 17,200 female Swedish hemangioma patients, who had been exposed to ionizing radiation because of skin hemangioma, was analyzed for breast cancer incidence with descriptive excess relative risk models and mechanistic models of carcinogenesis. The dosimetry system has recently been updated, leading to substantially reduced doses for the most highly exposed part of the Stockholm cohort. The follow-up includes persons until December 2009 with 877 breast cancer cases. All models agree on the risk estimates. The excess relative and excess absolute risk at the age of 50 years are 0.48 Gy(-1) (95% CI 0.28; 0.69) and 10.4 (10(4)PYR Gy)(-1) (95% CI 6.1; 14.4) (95% CI 6.1; 14.4), respectively. These risk estimates are about a factor of 2 higher than previous analyses of this cohort as a consequence of the re-evaluation of the dosimetry system. Explicit models incorporating effects of genomic instability were developed and applied to the hemangioma cohort. It was found that a radiation-induced transition towards genomic instability was highly significant. The models indicate that the main effect of radiation-induced genomic instability is to increase the rate of transition of non-initiated cells to initiated cells with a proliferative advantage. The magnitude of such an acceleration cannot be inferred from epidemiological data alone, but must be complemented by radiobiological measurements.

Ischemic Heart Disease in Workers at Mayak PA: Latency of Incidence Risk after Radiation Exposure

We present an updated analysis of incidence and mortality from atherosclerotic induced ischemic heart diseases in the cohort of workers at the Mayak Production Association (PA). This cohort constitutes one of the most important sources for the assessment of radiation risk. It is exceptional because it comprises information on several other risk factors. While most of the workers have been exposed to external gamma radiation, a large proportion has additionally been exposed to internal radiation from inhaled plutonium. Compared to a previous study by Azizova et al. 2012, the updated dosimetry system MWDS-2008 has been applied and methods of analysis have been revised. We extend the analysis of the significant incidence risk and observe that main detrimental effects of external radiation exposure occur after more than about 30 years. For mortality, significant risk was found in males with an excess relative risk per dose of 0.09 (95% CI: 0.02; 0.16) while risk was insignificant for females. With respect to internal radiation exposure no association to risk could be established.

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.

Integration of a radiation biomarker into modeling of thyroid carcinogenesis and post-Chernobyl risk assessment

Strong evidence for the statistical association between radiation exposure and disease has been produced for thyroid cancer by epidemiological studies after the Chernobyl accident. However, limitations of the epidemiological approach in order to explore health risks especially at low doses of radiation appear obvious. Statistical fluctuations due to small case numbers dominate the uncertainty of risk estimates. Molecular radiation markers have been searched extensively to separate radiation-induced cancer cases from sporadic cases. The overexpression of the CLIP2 gene is the most promising of these markers. It was found in the majority of papillary thyroid cancers (PTCs) from young patients included in the Chernobyl tissue bank. Motivated by the CLIP2 findings we propose a mechanistic model which describes PTC development as a sequence of rate-limiting events in two distinct paths of CLIP2-associated and multistage carcinogenesis. It integrates molecular measurements of the dichotomous CLIP2 marker from 141 patients into the epidemiological risk analysis for about 13 000 subjects from the Ukrainian-American cohort which were exposed below age 19 years and were put under enhanced medical surveillance since 1998. For the first time, a radiation risk has been estimated solely from marker measurements. Cross checking with epidemiological estimates and model validation suggests that CLIP2 is a marker of high precision. CLIP2 leaves an imprint in the epidemiological incidence data which is typical for a driver gene. With the mechanistic model, we explore the impact of radiation on the molecular landscape of PTC. The model constitutes a unique interface between molecular biology and radiation epidemiology.

Biologically-based mechanistic models of radiation-related carcinogenesis applied to epidemiological data

Abstract Purpose: Biologically-based mechanistic models that are used in combining current understanding of human carcinogenesis with epidemiological studies were reviewed. Assessment was made of how well they fit the data, whether they account for non-linear radiobiological low-dose effects, and whether they suggest any implications for the dose response at low doses and dose rates. However, the present paper does not make an attempt to provide a complete review of the existing literature on biologically-based models and their application to epidemiological data. Conclusion: In most studies the two-stage clonal expansion (TSCE) model of carcinogenesis was used. The model provided robust estimates of identifiable parameters and radiation risk. While relatively simple, it is flexible, so that more stages can easily be added, and tests made of various types of radiation action. In general, the model performed similarly or better than descriptive excess absolute and excess relative risk models, in terms of quality of fit and number of parameters. Only very rarely the shape of dose-response predicted by the models was investigated. For some tumors, when more detailed biological information was known, additional pathways were included in the model. The future development of these models will benefit from growing knowledge on carcinogenesis processes, and in particular from use of biobank tissue samples and advances in omics technologies. Their use appears a promising approach to investigate the radiation risk at low doses and low dose rates. However, the uncertainties involved are still considerable, and the models provide only a simplified description of the underlying complexity of carcinogenesis. Current assumptions in radiation protection including the linear-non-threshold (LNT) model are not in contradiction to what is presently known on the process of cancer development.

Breast cancer risk after radiation treatment at infancy: potential consequences of radiation-induced genomic instability

Swedish hemangioma patients were treated in infancy mainly by external application of radium-226 starting from 1920. This work analysed the radiation risk among 17,158 women with a total of 678 breast cancer incidence cases with models of carcinogenesis and empirical excess relative risk models. Models incorporating effects of genomic instability were developed and applied to the hemangioma cohort. The description of the radiation risk was significantly improved with a model of genomic instability at an early stage of carcinogenesis.

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.

Does deep inspiration breath-hold prolong life? Individual risk estimates of ischaemic heart disease after breast cancer radiotherapy

PURPOSE Aim of the current comparative modelling study was to estimate the individual radiation-induced risk for death of ischaemic heart disease (IHD) under free breathing (FB) and deep inspiration breath-hold (DIBH) in a real-world population. MATERIALS AND METHODS Eighty-nine patients with left-sided early breast cancer were enrolled in the prospective SAVE-HEART study. For each patient three-dimensional conformal treatment plans were created in FB and DIBH and corresponding radiation-induced risks of IHD mortality were estimated based on expected survival, individual IHD risk factors and the relative radiation-induced risk. RESULTS With the use of DIBH, mean heart doses were reduced by 35% (interquartile range: 23-46%) as compared to FB. Mean expected years of life lost (YLL) due to radiation-induced IHD mortality were 0.11 years in FB, and 0.07 years in DIBH. YLL were remarkably independent of age at treatment in patients with a favourable tumour prognosis. DIBH led to more pronounced reductions in YLL in patients with high baseline risk (0.08 years for upper vs 0.02 years for lower quartile), with favourable tumour prognosis (0.05 years for patients without vs 0.02 years for those with lymph-node involvement), and in patients with high mean heart doses in FB (0.09 years for doses >3 Gy vs 0.02 years for doses <1.5 Gy). CONCLUSION Ideally, the DIBH technique should be offered to all patients with left-sided breast cancer. However, highest benefits are expected for patients with a favourable tumour prognosis, high mean heart dose or high baseline IHD risk, independent of their age.

A mechanistic model for atherosclerosis and its application to the cohort of Mayak workers

We propose a stochastic model for use in epidemiological analysis, describing the age-dependent development of atherosclerosis with adequate simplification. The model features the uptake of monocytes into the arterial wall, their proliferation and transition into foam cells. The number of foam cells is assumed to determine the health risk for clinically relevant events such as stroke. In a simulation study, the model was checked against the age-dependent prevalence of atherosclerotic lesions. Next, the model was applied to incidence of atherosclerotic stroke in the cohort of male workers from the Mayak nuclear facility in the Southern Urals. It describes the data as well as standard epidemiological models. Based on goodness-of-fit criteria the risk factors smoking, hypertension and radiation exposure were tested for their effect on disease development. Hypertension was identified to affect disease progression mainly in the late stage of atherosclerosis. Fitting mechanistic models to incidence data allows to integrate biological evidence on disease progression into epidemiological studies. The mechanistic approach adds to an understanding of pathogenic processes, whereas standard epidemiological methods mainly explore the statistical association between risk factors and disease outcome. Due to a more comprehensive scientific foundation, risk estimates from mechanistic models can be deemed more reliable. To the best of our knowledge, such models are applied to epidemiological data on cardiovascular diseases for the first time.