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Purpose: The Organisation for Economic Co-operation and Development (OECD) Adverse Outcome Pathway (AOP) Development Programme is being explored in the radiation field, as an overarching framework to identify and prioritize research needs that best support strengthening of radiation risk assessment and risk management strategies. To advance the use of AOPs, an international horizon-style exercise (HSE) was initiated through the Radiation/Chemical AOP Joint Topical Group (JTG) formed by the OECD Nuclear Energy Agency (NEA) High-Level Group on Low Dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The intent of the HSE was to identify key research questions for consideration in AOP development that would help to reduce uncertainties in estimating the health risks following exposures to low dose and low dose-rate ionizing radiation. The HSE was conducted in several phases involving the solicitation of relevant questions, a collaborative review of open-ended candidate questions and an elimination exercise that led to the selection of 25 highest priority questions for the stated purpose. These questions were further ranked by over 100 respondents through an international survey. This final set of questions was judged to provide insights into how the OECD's AOP approach can be put into practice to meet the needs of hazard and risk assessors, regulators, and researchers. This paper examines the 25 priority questions in the context of hazard/risk assessment framework for ionizing radiation., Conclusion: By addressing the 25 priority questions, it is anticipated that constructed AOPs will have a high level of specificity, making them valuable tools for simplifying and prioritizing complex biological processes for use in developing revised radiation hazard and risk assessment strategies.

Introduction: Pleural effusions frequently signal disseminated cancer. Diagnostic markers of pleural malignancy at presentation that would assess cancer risk and would streamline diagnostic decisions remain unidentified., Methods: A consecutive cohort of 323 patients with pleural effusion (PE) from different etiologies were recruited between 2013 and 2017 and was retrospectively analyzed. Data included history, chest X-ray, and blood/pleural fluid cell counts and biochemistry. Group comparison, receiver-operator characteristics, unsupervised hierarchical clustering, binary logistic regression, and random forests were used to develop the malignant pleural effusion detection (MAPED) score. MAPED was validated in an independent retrospective UK cohort (n = 238)., Results: Five variables showed significant diagnostic power and were incorporated into the 5-point MAPED score. Age > 55 years, effusion size > 50% of the most affected lung field, pleural neutrophil count 〈 2,500/mm 3 , effusion protein 〉 3.5 g/dL, and effusion lactate dehydrogenase > 250 U/L, each scoring one point, predicted underlying cancer with the area under curve(AUC) = 0.819 (P < 10 -15 ) in the derivation cohort. The integrated discrimination improvement of MAPED scores showed an increase compared to cytology (p <0.001). Decision curve analysis indicated that the MAPED score generated net clinical benefit. In the validation dataset, the AUC of MAPED scores was 0.723 ( P = 3 × 10 -9 ) for the MAPED score. Interestingly, MAPED correctly identified 33/42(79%) of cytology-negative patients that indeed had cancer., Conclusions: The MAPED score identifies malignant pleural effusions with satisfactory accuracy and can be used complementary to cytology to streamline diagnostic procedures., Condensed Abstract: Diagnostic markers for malignant pleural effusions remain uncertain. The MAPED score identifies malignant pleural effusions and complements cytology and confers no additional risk to the patient or cost to the healthcare system., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Ioannis Psallidas is employed as a Global Clinical Head by Astra Zeneca Pharmaceutical in a field that is non-related with the publication. The remaining authors have declared that no conflict of interest exists., (Copyright © 2023. Published by Elsevier Inc.)

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology., (© 2022. The Author(s).)

Colorectal adenoma are precursor lesions on the pathway to cancer. Their removal in screening colonoscopies has markedly reduced rates of cancer incidence and death. Generic models of adenoma growth and transition to cancer can guide the implementation of screening strategies. But adenoma shape has rarely featured as a relevant risk factor. Against this backdrop we aim to demonstrate that shape influences growth dynamics and cancer risk. Stochastic cell-based models are applied to a data set of 197,347 Bavarian outpatients who had colonoscopies from 2006-2009, 50,649 patients were reported with adenoma and 296 patients had cancer. For multi-stage clonal expansion (MSCE) models with up to three initiating stages parameters were estimated by fits to data sets of all shapes combined, and of sessile (70% of all adenoma), peduncular (17%) and flat (13%) adenoma separately for both sexes. Pertinent features of adenoma growth present themselves in contrast to previous assumptions. Stem cells with initial molecular changes residing in early adenoma predominantly multiply within two-dimensional structures such as crypts. For these cells mutation and division rates decrease with age. The absolute number of initiated cells in an adenoma of size 1 cm is small around 103, related to all bulk cells they constitute a share of about 10-5. The notion of very few proliferating stem cells with age-decreasing division rates is supported by cell marker experiments. The probability for adenoma transiting to cancer increases with squared linear size and shows a shape dependence. Compared to peduncular and flat adenoma, it is twice as high for sessile adenoma of the same size. We present a simple mathematical expression for the hazard ratio of interval cancers which provides a mechanistic understanding of this important quality indicator. We conclude that adenoma shape deserves closer consideration in screening strategies and as risk factor for transition to cancer., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Simonetto et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The extent of elective nodal irradiation (ENI) in patients undergoing definitive chemoradiotherapy (dCRT) for esophageal squamous cell carcinoma (ESCC) remains unclear. The aim of this dosimetric study was to evaluate the extent of incidental nodal irradiation using modern radiation techniques. A planning target volume (PTV) was generated for 30 patients with node-negative esophageal carcinoma (13 cervical/upper third, 7 middle third, 10 lower third/abdomen). Thereby, no elective nodal irradiation (ENI) was intended. Both three-dimensional conformal radiotherapy (3D-CRT) and volumetric-modulated arc therapy (VMAT) treatment plans (50 Gy in 25 fractions) were calculated for all patients. Fifteen nodal stations were contoured according to the definitions of the AJCC and investigated in regard to dosimetric parameters. Compared to 3D-CRT, VMAT was associated with lower dose distribution to the organs at risk (lower D mean , V20 and V30 for the lungs and lower D mean and V30 for the heart). For both techniques, the median D mean surpassed 40 Gy in 12 of 15 (80%) nodal stations. However, VMAT resulted in significantly lower D means and equivalent uniform doses (EUD) compared to 3D-CRT for eight nodal stations (1L, 2L, 2R, 4L, 7, 8L, 10L, 15), while differences did not reach significance for seven nodal station (1R, 4R, 8U, 8M, 10R, 16). For dCRT of ESCC, the use of VMAT was associated with significantly lower median (incidental) doses to eight of 15 regional lymph node areas compared to 3D-CRT. However, given the small absolute differences, these differences probably do not impair (regional) tumor control rates., (© 2022. The Author(s).)

Mathematical models are able to reflect biological processes and to capture epidemiologic data. Thus, they may help elucidate roles of risk factors in disease progression. We propose to account for smoking, hypertension, and dyslipidemia in a previously published process-oriented model that describes the development of atherosclerotic lesions resulting in myocardial infarction (MI). The model is sex-specific and incorporates individual heterogeneity. It was applied to population-based individual risk factors and MI rates (Cooperative Health Research in the Region of Augsburg (KORA) study) together with subclinical atherosclerotic lesion data (Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study). Different model variants were evaluated, testing the association of risk factors with different disease processes. Best fits were obtained for smoking affecting a late-stage disease process, suggesting a thrombogenic role. Hypertension was mainly related to complicated, vulnerable lesions. Dyslipidemia was consistent with increasing the number of initial lesions. By accounting for heterogeneity, individual hazard ratios differ from the population average. The mean individual hazard ratio for smoking was twice the population-based hazard ratio for men and even more for women. Atherosclerotic lesion progression and MI incidence data can be related in a mathematical model to illuminate how risk factors affect different phases of this pathological process., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)

Background: Survival after curative resection of early-stage lung adenocarcinoma (LUAD) varies and prognostic biomarkers are urgently needed., Methods: Large-format tissue samples from a prospective cohort of 200 patients with resected LUAD were immunophenotyped for cancer hallmarks TP53, NF1, CD45, PD-1, PCNA, TUNEL and FVIII, and were followed for a median of 2.34 (95% CI 1.71-3.49) years., Results: Unsupervised hierarchical clustering revealed two patient subgroups with similar clinicopathological features and genotype, but with markedly different survival: "proliferative" patients (60%) with elevated TP53, NF1, CD45 and PCNA expression had 50% 5-year overall survival, while "apoptotic" patients (40%) with high TUNEL had 70% 5-year survival (hazard ratio 2.23, 95% CI 1.33-3.80; p=0.0069). Cox regression and machine learning algorithms including random forests built clinically useful models: a score to predict overall survival and a formula and nomogram to predict tumour phenotype. The distinct LUAD phenotypes were validated in The Cancer Genome Atlas and KMplotter data, and showed prognostic power supplementary to International Association for the Study of Lung Cancer tumour-node-metastasis stage and World Health Organization histologic classification., Conclusions: Two molecular subtypes of LUAD exist and their identification provides important prognostic information., Competing Interests: Conflict of interest: The authors declare no potential conflicts of interest., (Copyright ©The authors 2022. For reproduction rights and permissions contact permissions@ersnet.org.)

This study aims to identify key anatomic features that govern the individual variability of lung doses from breast-cancer radiotherapy. 3D conformal, intensity-modulated and hybrid techniques with 50.4 Gy whole-breast dose were planned for 128 patients. From their CT images, 17 anatomic measures were assessed and tested as predictors for lung dose-volume characteristics. Tangential techniques yielded mean ipsilateral lung doses in the range of 3-11 Gy. This inter-patient variability was explained to almost 40% by central lung distance, and to almost 60% if this measure was complemented by midplane lung width and maximum heart distance. Also the variability in further dose-volume metrics such as volume fractions receiving 5, 20 or 40 Gy could be largely explained by the anatomy. Multi-field intensity-modulated radiotherapy reduced high-exposed lung volumes, but resulted in higher mean ipsilateral lung doses and larger low-dose burden. Contralateral lung doses ranged from 0.3 to 1 Gy. The results highlight that there are large differences in lung doses among breast-cancer patients. Most of this inter-individual variability can be explained by a few anatomic features. The results will be implemented in a dedicated software tool to provide personalized estimates of long-term health risks related to breast-cancer radiotherapy. The results may also be used to identify favourable as well as problematic anatomies, and serve as a quick quantitative benchmark for individual treatment plans., (© 2022. The Author(s).)

There is large inter-individual heterogeneity in risk of coronary heart disease (CHD). Risk factors traditionally used in primary risk assessment only partially explain this heterogeneity. Residual, unobserved heterogeneity leads to age-related attenuation of hazard rates and underestimation of hazard ratios. Its magnitude is unknown. Therefore, we aimed to estimate a lower and an approximate upper bound. Heterogeneity was parametrized by a log-normal distribution with shape parameter σ. Analysis was based on published data. From concordance indices of studies including traditional risk factors and additional diagnostic imaging data, we calculated the part of heterogeneity explained by imaging data. For traditional risk assessment, this part typically remains unexplained, thus constituting a lower bound on unobserved heterogeneity. Next, the potential impact of heterogeneity on CHD hazard rates in several large countries was investigated. CHD rates increase with age but the increase attenuates with age. Presuming this attenuation to be largely caused by heterogeneity, an approximate upper bound on σ was derived. Taking together both bounds, unobserved heterogeneity in studies without imaging information can be described by a shape parameter in the range σ = 1-2. It substantially contributes to observed age-dependences of hazard ratios and may lead to underestimation of hazard ratios by a factor of about two. Therefore, analysis of studies for primary CHD risk assessment should account for unobserved heterogeneity., (© 2022. The Author(s).)

Background: Epidemiological studies have indicated that exposure of the heart to doses of ionizing radiation as low as 0.5 Gy increases the risk of cardiac morbidity and mortality with a latency period of decades. The damaging effects of radiation to myocardial and endothelial structures and functions have been confirmed radiobiologically at high dose, but much less are known at low dose. Integration of radiation biology and epidemiology data is a recommended approach to improve the radiation risk assessment process. The adverse outcome pathway (AOP) framework offers a comprehensive tool to compile and translate mechanistic information into pathological endpoints which may be relevant for risk assessment at the different levels of a biological system. Omics technologies enable the generation of large volumes of biological data at various levels of complexity, from molecular pathways to functional organisms. Given the quality and quantity of available data across levels of biology, omics data can be attractive sources of information for use within the AOP framework. It is anticipated that radiation omics studies could improve our understanding of the molecular mechanisms behind the adverse effects of radiation on the cardiovascular system. In this review, we explored the available omics studies on radiation-induced cardiovascular disease (CVD) and their applicability to the proposed AOP for CVD., Results: The results of 80 omics studies published on radiation-induced CVD over the past 20 years have been discussed in the context of the AOP of CVD proposed by Chauhan et al. Most of the available omics data on radiation-induced CVD are from proteomics, transcriptomics, and metabolomics, whereas few datasets were available from epigenomics and multi-omics. The omics data presented here show great promise in providing information for several key events (KEs) of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix (ECM), and vascular remodeling., Conclusions: The omics data presented here shows promise to inform the various levels of the proposed AOP of CVD. However, the data highlight the urgent need of designing omics studies to address the knowledge gap concerning different radiation scenarios, time after exposure, and experimental models. This review presents the evidence to build a qualitative omics-informed AOP and provides views on the potential benefits and challenges in using omics data to assess risk-related outcomes.

Purpose: The Adverse Outcome Pathway (AOP) framework, a systematic tool that can link available mechanistic data with phenotypic outcomes of relevance to regulatory decision-making, is being explored in areas related to radiation risk assessment. To examine the challenges including the use of AOPs to support the radiation protection community, an international horizon-style exercise was initiated through the Organisation for Economic Co-operation and Development Nuclear Energy Agency High-Level Group on Low Dose Research Radiation/Chemical AOP Joint Topical Group. The objective of the HSE was to facilitate the collection of ideas from a range of experts, to short-list a set of priority research questions that could, if answered, improve the description of the radiation dose-response relationship for low dose/dose-rate exposures, as well as reduce uncertainties in estimating the risk of developing adverse health outcomes following such exposures., Materials and Methods: The HSE was guided by an international steering committee of radiation risk experts. In the first phase, research questions were solicited on areas that can be supported by the AOP framework, or challenges on the use of AOPs in radiation risk assessment. In the second phase, questions received were refined and sorted by the SC using a best-worst scaling method. During a virtual 3-day workshop, the list of questions was further narrowed. In the third phase, an international survey of the broader radiation protection community led to an orderly ranking of the top questions., Results: Of the 271 questions solicited, 254 were accepted and categorized into 9 themes. These were further refined to the top 25 prioritized questions. Among these, the higher ranked questions will be considered as 'important' to drive future initiatives in the low dose radiation protection community. These included questions on the ability of AOPs to delineate responses across different levels of biological organization, and how AOPs could be applied to address research questions on radiation quality, doses or dose-rates, exposure time patterns and deliveries, and uncertainties in low dose/dose-rate effects. A better understanding of these concepts is required to support the use of the AOP framework in radiation risk assessment., Conclusion: Through dissemination of these results and considerations on next steps, the JTG will address select priority questions to advance the development and use of AOPs in the radiation protection community. The major themes observed will be discussed in the context of their relevance to areas of research that support the system of radiation protection.

Analyzing epidemiological data with simplified mathematical models of disease development provides a link between the time-course of incidence and the underlying biological processes. Here we point out that considerable modeling flexibility is gained if the model is solved by simulation only. To this aim, a model of atherosclerosis is proposed: a Markov Chain with continuous state space which represents the coronary artery intimal surface area involved with atherosclerotic lesions of increasing severity. Myocardial infarction rates are assumed to be proportional to the area of most severe lesions. The model can be fitted simultaneously to infarction incidence rates observed in the KORA registry, and to the age-dependent prevalence and extent of atherosclerotic lesions in the PDAY study. Moreover, the simulation approach allows for non-linear transition rates, and to consider at the same time randomness and inter-individual heterogeneity. Interestingly, the fit revealed significant age dependence of parameters in females around the age of menopause, qualitatively reproducing the known vascular effects of female sex hormones. For males, the incidence curve flattens for higher ages. According to the model, frailty explains this flattening only partially, and saturation of the disease process plays also an important role. This study shows the feasibility of simulating subclinical and epidemiological data with the same mathematical model. The approach is very general and may be extended to investigate the effects of risk factors or interventions. Moreover, it offers an interface to integrate quantitative individual health data as assessed, for example, by imaging., (© 2021 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

Risks to health are the prime consideration in all human situations of ionizing radiation exposure and therefore of relevance to radiation protection in all occupational, medical, and public exposure situations. Over the past few decades, advances in therapeutic strategies have led to significant improvements in cancer survival rates. However, a wide range of long-term complications have been reported in cancer survivors, in particular circulatory diseases and their major risk factors, metabolic diseases. However, at lower levels of exposure, the evidence is less clear. Under real-life exposure scenarios, including radiotherapy, radiation effects in the whole organism will be determined mainly by the response of normal tissues receiving relatively low doses, and will be mediated and moderated by systemic effects. Therefore, there is an urgent need for further research on the impact of low-dose radiation. In this article, we review radiation-associated risks of circulatory and metabolic diseases in clinical, occupational or environmental exposure situations, addressing epidemiological, biological, risk modelling, and systems biology aspects, highlight the gaps in knowledge and discuss future directions to address these gaps., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Purpose: Thyroid cancer of papillary histology (PTC) is the dominant type in radio-epidemiological cohorts established after nuclear accidents or warfare. Studies on post-Chernobyl PTC and on thyroid cancer in the life span study (LSS) of Japanese a-bomb survivors consistently revealed high radiation risk after exposure during childhood and adolescence. For post-Chernobyl risk assessment overexpression of the CLIP2 gene was proposed as molecular biomarker to separate radiogenic from sporadic PTC. Based on such binary marker a biologically-based risk model of PTC carcinogenesis has been developed for observational Chernobyl data. The model featured two independent molecular pathways of disease development, of which one was associated with radiation exposure. To gain credibility the concept for a mechanistic risk model must be based on general biological features which transcend findings in a single cohort. The purpose of the present study is therefore to demonstrate portability of the model concept by application to PTC incidence data in the LSS. By exploiting the molecular two-path concept we improve the determination of the probability of radiation causing cancer (POC)., Materials and Methods: The current analysis uses thyroid cancer incidence data of the LSS with thyroid cancer diagnoses and papillary histology ( n  = 292) from the follow-up period between 1958 and 2005. Risk analysis was performed with both descriptive and biologically-based models., Results: Judged by goodness-of-fit all applied models described the data almost equally well. They yielded similar risk estimates in cohorts post-Chernobyl and LSS. The preferred mechanistic model was selected by biological plausibility. It reflected important features of an imperfect radiation marker which are not easily addressed by descriptive models. Precise model predictions of marker prevalence in strata of epidemiological covariables can be tested by molecular measurements. Application of the radiation-related molecular pathway from our preferred model in retrospective risk assessment decreases the threshold dose for 50% POC from 0.33 (95% confidence interval (CI) 0.18; 0.64) Gy to 0.04 (95% CI 0.01; 0.19) Gy for females and from 0.43 (95% CI 0.17; 1.84) Gy to 0.19 (95% CI 0.05; 1.00) Gy for males. These improvements are still not sufficient to separate radiation-induced from sporadic PTC cases at very low doses <0.015 Gy typical for the Fukushima accident., Conclusions: Successful application of our preferred mechanistic model to LSS incidence data confirms and improves the biological two-path concept of radiation-induced PTC. Model predictions suggest further molecular validation studies to consolidate the basis of biologically-based risk estimation.

Background: The circulatory system distributes nutrients, signaling molecules, and immune cells to vital organs and soft tissues. Epidemiological, animal, and in vitro cellular mechanistic studies have highlighted that exposure to ionizing radiation (IR) can induce molecular changes in cellular and subcellular milieus leading to long-term health impacts, particularly on the circulatory system. Although the mechanisms for the pathologies are not fully elucidated, endothelial dysfunction is proven to be a critical event via radiation-induced oxidative stress mediators. To delineate connectivities of events specifically to cardiovascular disease (CVD) initiation and progression, the adverse outcome pathway (AOP) approach was used with consultation from field experts. AOPs are a means to organize information around a disease of interest to a regulatory question. An AOP begins with a molecular initiating event and ends in an adverse outcome via sequential linkages of key event relationships that are supported by evidence in the form of the modified Bradford-Hill criteria. Detailed guidelines on building AOPs are provided by the Organisation for Economic Cooperation and Development (OECD) AOP program. Here, we report on the questions and discussions needed to develop an AOP for CVD resulting from IR exposure. A recent workshop jointly organized by the MELODI (Multidisciplinary European Low Dose Initiative) and the ALLIANCE (European Radioecology Alliance) associations brought together experts from the OECD to present the AOP approach and tools with examples from the toxicology field. As part of this workshop, four working groups were formed to discuss the identification of adverse outcomes relevant to radiation exposures and development of potential AOPs, one of which was focused on IR-induced cardiovascular effects. Each working group comprised subject matter experts and radiation researchers interested in the specific disease area and included an AOP coach., Conclusion: The CVD working group identified the critical questions of interest for AOP development, including the exposure scenario that would inform the evidence, the mechanisms of toxicity, the initiating event, intermediate key events/relationships, and the type of data currently available. This commentary describes the four-day discussion of the CVD working group, its outcomes, and demonstrates how collaboration and expert consultation is vital to informing AOP construction.

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.

Background: Radiotherapy treatment of head and neck cancer affects local arteries and increases the risk of stroke. This study aimed at a closer characterization of this damage and its development in time with a longitudinal study set up., Methods: Male patients treated between 2011 and 2016 for hypopharyngeal carcinoma were identified from the in-house clinical data base. They were included into the study if besides the planning CT at least one additional CT image was available from follow-up (13 patients) or at least two MRI scans (16 patients of which 2 were already included). All patients received radiotherapy, and chemotherapy was administered to 16 patients. The time from the beginning of radiotherapy to the last available image ranged from 2 months to 4.5 years. For six segments of the carotid arteries, the number and volume of atherosclerotic plaques were determined from the CT scans, and the intima media thickness from the MRI scans. Information on comorbid cardiovascular disease, hypertension and diabetes mellitus was retrieved from medical records., Results: Total plaque volume rose from 0.25 cm 3 before to 0.33 cm 3 after therapy but this was not significant (p = 0.26). The mean number of plaques increased from 5.7 to 8.1 (p = 0.002), and the intima media thickened from 1.17 mm to 1.35 mm (p = 0.002). However, the mean intima media thickness practically did not change in patients with comorbid diabetes mellitus (p-value for homogeneity: 0.03). For patients without diabetes mellitus, dynamics of both plaque number and intima media thickness, was consistent with an increase until about one year after therapy and no further progression thereafter., Conclusion: Our study confirmed the thickening of artery walls and the increase in the number of plaques. Results imply that definitive radiation damage to the artery walls can be determined not earlier than about one year after radiotherapy and there is no substantial deterioration thereafter. Reasons for the absence of an observable intima media thickening in patients with diabetes are unclear.

Recent analyses of the Canadian fluoroscopy cohort study reported significantly increased radiation risks of mortality from ischemic heart diseases (IHD) with a linear dose-response adjusted for dose fractionation. This cohort includes 63,707 tuberculosis patients from Canada who were exposed to low-to-moderate dose fractionated X-rays in 1930s-1950s and were followed-up for death from non-cancer causes during 1950-1987. In the current analysis, we scrutinized the assumption of linearity by analyzing a series of radio-biologically motivated nonlinear dose-response models to get a better understanding of the impact of radiation damage on IHD. The models were weighted according to their quality of fit and were then mathematically superposed applying the multi-model inference (MMI) technique. Our results indicated an essentially linear dose-response relationship for IHD mortality at low and medium doses and a supra-linear relationship at higher doses (> 1.5 Gy). At 5 Gy, the estimated radiation risks were fivefold higher compared to the linear no-threshold (LNT) model. This is the largest study of patients exposed to fractionated low-to-moderate doses of radiation. Our analyses confirm previously reported significantly increased radiation risks of IHD from doses similar to those from diagnostic radiation procedures.

Background and Aims: Risk assessment studies on the impact of carotid intima-media thickness (CIMT) on cardiovascular events (CVEs) often apply a linear relationship in Cox models of proportional hazards. However, CVEs are mostly induced through rupture of plaques driven by nonlinear mechanical properties of the arterial wall. Hence, the risk response might be nonlinear as well and should be detectable in CVE incidence data when associated with CIMT as surrogate variable for atherosclerotic wall degeneration., Methods: To test this hypothesis, we investigate the KORA F4 study comprising 2580 participants with CIMT measurements and 153 first CVEs (86 strokes and 67 myocardial infarctions). CIMT is only a moderate predictor of CVE risk due to confounding by attained age. Biological evidence suggests that age-related CIMT growth is not entirely connected with atherosclerosis. To explore the complex relations between age, CIMT and CVE risk, we apply linear and nonlinear models of both CIMT and dnCIMT, defined as deviation from a sex and age-adjusted normal value., Results: Based on goodness-of-fit and biological plausibility, threshold and logistic step models clearly reveal nonlinear risk response relations for vascular covariables CIMT and dnCIMT. The effect is more pronounced for models involving dnCIMT as novel risk factor, which is not correlated with age., Conclusions: Compared to the standard approach of risk assessment with linear models involving CIMT, the application of excess dnCIMT with nonlinear risk responses leads to a more precise identification of asymptomatic high risk patients, especially at younger age., Competing Interests: Declaration of competing interest The authors declared they do not have anything to disclose regarding conflict of interest with respect to this manuscript., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Current radiological emergency response recommendations have been provided by the International Commission on Radiological Protection and adopted by the International Atomic Energy Agency in comprehensive Safety Standards. These standards provide dose-based guidance for decision making (e.g., on sheltering or relocation) via generic criteria in terms of effective dose in the range from 20 mSv per year, during transition from emergency to existing exposure situation, to 100 mSv, acute or annual, in the urgent phase of a nuclear accident. The purpose of this paper was to examine how such dose reference levels directly translate into radiation-related risks of the main stochastic detrimental health effects (cancer). Methodologies, provided by the World Health Organization after the Fukushima accident, for calculating the lifetime and 20 year cancer risks and for attributing relevant organ doses from effective doses, have been applied here for this purpose with new software, designed to be available for use immediately after a nuclear accident. A new feature in this software is a comprehensive accounting for uncertainty via simulation technique, so that the risks may now be presented with realistic confidence intervals. The types of cancer risks considered here are time-integrated over lifetime and the first 20 years after exposure for all solid cancers and either the most radiation-sensitive types of cancer, i.e., leukaemia and female breast cancer, or the most radiation-relevant type of cancer occurring early in life, i.e., thyroid. It is demonstrated here how reference dose levels translate differently into specific cancer risk levels (with varying confidence interval sizes), depending on age at exposure, gender, time-frame at-risk and type of cancer considered. This demonstration applies German population data and considers external exposures. Further work is required to comprehensively extend this methodology to internal exposures that are likely to be important in the early stages of a nuclear accident. A discussion is provided here on the potential for such risk-based information to be used by decision makers, in the urgent and transition phases of nuclear emergencies, to identify protective measures (e.g., sheltering, evacuation) in a differential way (i.e., for particularly susceptible sub-groups of a population).

KRAS mutations of lung adenocarcinoma (LADC) are associated with smoking but little is known on other exposure-oncogene associations. Hypothesizing that different inciting agents may cause different driver mutations, we aimed to identify distinct molecular pathways to LADC, applying two entirely different approaches. First, we examined clinicopathologic features and genomic signatures of environmental exposures in the large LADC Campbell data set. Second, we designed a molecular mechanistic risk model of LADC (M3LADC) that links environmental exposure to incidence risk by mathematically emulating the disease process. This model was applied to incidence data of Japanese atom-bomb survivors which contains information on radiation and smoking exposure. Grouping the clinical data by driver mutations revealed two main distinct molecular pathways to LADC: one unique to transmembrane receptor-mutant patients that displayed robust signatures of radiation exposure and one shared between submembrane transducer-mutant patients and patients with no evident driver mutation that carried the signature of smoking. Consistently, best fit of the incidence data was achieved with a M3LADC with two pathways: in one LADC risk increased with radiation exposure and in the other with cigarette consumption. We conclude there are two main molecular pathways to LADC associated with different environmental exposures. Future molecular measurements in lung cancer tissue of atom-bomb survivors may allow to further test quantitatively the M3LADC-predicted link of radiation to transmembrane receptor mutations. Moreover, the developed molecular mechanistic model showed that for low doses, as relevant e.g. for medical imaging, smokers have the same radiation risk compared with never smokers., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The problem of expressing cumulative detrimental effect of radiation exposure is revisited. All conventionally used and computationally complex lifetime or time-integrated risks are based on current population and health statistical data, with unknown future secular trends, that are projected far into the future. It is shown that application of conventionally used lifetime or time-integrated attributable risks (LAR, AR) should be limited to exposures under 1 Gy. More general quantities, such as excess lifetime risk (ELR) and, to a lesser extent, risk of exposure-induced death (REID), are free of dose constraints, but are even more computationally complex than LAR and AR and rely on the unknown total radiation effect on demographic and health statistical data. Appropriate assessment of time-integrated risk of a specific outcome following high-dose (more than 1 Gy) exposure requires consideration of competing risks for other radiation-attributed outcomes and the resulting ELR estimate has an essentially non-linear dose response. Limitations caused by basing conventionally applied time-integrated risks on current population and health statistical data are that they are: (a) not well suited for risk estimates for atypical groups of exposed persons not readily represented by the general population; and (b) not optimal for risk projections decades into the future due to large uncertainties in developments of the future secular trends in the population-specific disease rates. Alternative disease-specific quantities, baseline and attributable survival fractions, based on reduction of survival chances are considered here and are shown to be very useful in circumventing most aspects of these limitations. Another main quantity, named as radiation-attributed decrease of survival (RADS), is recommended here to represent cumulative radiation risk conditional on survival until a certain age. RADS, historically known in statistical literature as "cumulative risk", is only based on the radiation-attributed hazard and is insensitive to competing risks. Therefore, RADS is eminently suitable for risk projections in emergency situations and for estimating radiation risks for persons exposed after therapeutic or interventional medical applications of radiation or in other highly atypical groups of exposed persons, such as astronauts.

Exposure-lag-response associations shed light on the duration of pathogenesis for radiation-induced diseases. To investigate such relations for lung cancer mortality in the German uranium miners of the Wismut company, we apply distributed lag non-linear models (DLNMs) which offer a flexible description of the lagged risk response to protracted radon exposure. Exposure-lag functions are implemented with B-Splines in Cox models of proportional hazards. The DLNM approach yielded good agreement of exposure-lag-response surfaces for the German cohort and for the previously studied cohort of American Colorado miners. For both cohorts, a minimum lag of about 2 year for the onset of risk after first exposure explained the data well, but possibly with large uncertainty. Risk estimates from DLNMs were directly compared with estimates from both standard radio-epidemiological models and biologically based mechanistic models. For age > 45 year, all models predict decreasing estimates of the Excess Relative Risk (ERR). However, at younger age, marked differences appear as DLNMs exhibit ERR peaks, which are not detected by the other models. After comparing exposure-responses for biological processes in mechanistic risk models with exposure-responses for hazard ratios in DLNMs, we propose a typical period of 15 year for radon-related lung carcinogenesis. The period covers the onset of radiation-induced inflammation of lung tissue until cancer death. The DLNM framework provides a view on age-risk patterns supplemental to the standard radio-epidemiological approach and to biologically based modeling.

A comprehensive characterization of lung adenocarcinoma (LADC) clinical features is currently missing. We prospectively evaluated Caucasian patients with early-stage LADC. Patients with LADC diagnosed between 2011 and 2015 were prospectively assessed for lung resection with curative intent. Fifty clinical, pathologic, radiologic, and molecular variables were recorded. Patients were followed till death/study conclusion. The main findings were compared to a separate cohort from France. Of 1943 patients evaluated, 366 were enrolled (18.8%; 181 female; 75 never-smokers; 28% of registered Bavarian cases over the study period). Smoking and obstruction were significantly more prevalent in GLAD compared with adult Bavarians (P < 0.0001). Ever-smoker tumors were preferentially localized to the upper lobes. We observed 120 relapses and 74 deaths over 704 cumulative follow-up years. Median overall and disease-free survival were >7.5 and 3.6 years, respectively. Patients aged <45 or >65 years, resected >60 days postdiagnosis, with abnormal FVC/DL CO V A , N2/N3 stage, or solid histology had significantly decreased survival estimates. These were fit into a weighted locoregional LADC death risk score that outperformed pTNM7 in predicting survival in the GLAD and in our second cohort. We define the clinical gestalt of locoregional LADC and provide a new clinical tool to predict survival, findings that may aid future management and research design., (© 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

The scientific community faces important discussions on the validity of the linear no-threshold (LNT) model for radiation-associated cardiovascular diseases at low and moderate doses. In the present study, mortalities from cerebrovascular diseases (CeVD) and heart diseases from the latest data on atomic bomb survivors were analyzed. The analysis was performed with several radio-biologically motivated linear and nonlinear dose-response models. For each detrimental health outcome one set of models was identified that all fitted the data about equally well. This set was used for multi-model inference (MMI), a statistical method of superposing different models to allow risk estimates to be based on several plausible dose-response models rather than just relying on a single model of choice. MMI provides a more accurate determination of the dose response and a more comprehensive characterization of uncertainties. It was found that for CeVD, the dose-response curve from MMI is located below the linear no-threshold model at low and medium doses (0-1.4 Gy). At higher doses MMI predicts a higher risk compared to the LNT model. A sublinear dose-response was also found for heart diseases (0-3 Gy). The analyses provide no conclusive answer to the question whether there is a radiation risk below 0.75 Gy for CeVD and 2.6 Gy for heart diseases. MMI suggests that the dose-response curves for CeVD and heart diseases in the Lifespan Study are sublinear at low and moderate doses. This has relevance for radiotherapy treatment planning and for international radiation protection practices in general.

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.

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.

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., (© The Author 2016. Published by Oxford University Press.)

A previous study on papillary thyroid carcinomas (PTC) in young patients who were exposed to (131)iodine from the Chernobyl fallout revealed an exclusive gain of chromosomal band 7q11.23 in exposed cases compared to an age-matched control cohort. CLIP2, a gene located within band 7q11.23 was shown to be differentially expressed between exposed and non-exposed cases at messenger RNA and protein level. Therefore, a standardized procedure for CLIP2 typing of PTCs has been developed in a follow-up study. Here we used CLIP2 typing data on 117 post-Chernobyl PTCs from two cohorts of exposed patients with individual dose estimates and 24 non-exposed controls to investigate a possible quantitative dose-response relationship of the CLIP2 marker. The 'Genrisk-T' cohort consisted of 45 PTCs and the 'UkrAm' cohort of 72 PTCs. Both cohorts differed in mean dose (0.59 Gy Genrisk-T, 1.2 Gy UkrAm) and mean age at exposure (AaE) (2 years Genrisk-T, 8 years UkrAm), whilst the median latency (16 years Genrisk-T, 18 years UkrAm) was comparable. We analyzed the association between the binary CLIP2 typing and continuous thyroid dose with logistic regression. A clear positive dose-response relationship was found for young PTC cases [age at operation (AaO) < 20 years, AaE < 5 years]. In the elder age group a higher proportion of sporadic tumors is assumed due to a negligible dose response, suggesting different molecular mechanisms in sporadic and radiation-induced cases. This is further supported by the association of elder patients (AaO > 20 years) with positivity for BRAF V600E mutation., (© The Author 2015. Published by Oxford University Press.)

Colon cancer is caused by multiple genomic alterations which lead to genomic instability (GI). GI appears in molecular pathways of microsatellite instability (MSI) and chromosomal instability (CIN) with clinically observed case shares of about 15-20% and 80-85%. Radiation enhances the colon cancer risk by inducing GI, but little is known about different outcomes for MSI and CIN. Computer-based modelling can facilitate the understanding of the phenomena named above. Comprehensive biological models, which combine the two main molecular pathways to colon cancer, are fitted to incidence data of Japanese a-bomb survivors. The preferred model is selected according to statistical criteria and biological plausibility. Imprints of cell-based processes in the succession from adenoma to carcinoma are identified by the model from age dependences and secular trends of the incidence data. Model parameters show remarkable compliance with mutation rates and growth rates for adenoma, which has been reported over the last fifteen years. Model results suggest that CIN begins during fission of intestinal crypts. Chromosomal aberrations are generated at a markedly elevated rate which favors the accelerated growth of premalignant adenoma. Possibly driven by a trend of Westernization in the Japanese diet, incidence rates for the CIN pathway increased notably in subsequent birth cohorts, whereas rates pertaining to MSI remained constant. An imbalance between number of CIN and MSI cases began to emerge in the 1980s, whereas in previous decades the number of cases was almost equal. The CIN pathway exhibits a strong radio-sensitivity, probably more intensive in men. Among young birth cohorts of both sexes the excess absolute radiation risk related to CIN is larger by an order of magnitude compared to the MSI-related risk. Observance of pathway-specific risks improves the determination of the probability of causation for radiation-induced colon cancer in individual patients, if their exposure histories are known.

Thyroid cancer is one of the major health concerns after the accident in the Fukushima Dai-ichi nuclear power station (NPS). Currently, ultrasonography surveys are being performed for persons residing in the Fukushima Prefecture at the time of the accident with an age of up to 18 years. Here, the expected thyroid cancer prevalence in the Fukushima Prefecture is assessed based on an ultrasonography survey of Ukrainians, who were exposed at an age of up to 18 years to (131)I released during the Chernobyl NPS accident, and on differences in equipment and study protocol in the two surveys. Radiation risk of thyroid cancer incidence among survivors of the atomic bombings of Hiroshima and Nagasaki and preliminary estimates of thyroid dose due to the Fukushima accident were used for the prediction of baseline and radiation-related thyroid cancer risks. We estimate a prevalence of thyroid cancer of 0.027 % (95 % CI 0.010 %; 0.050 %) for the first screening campaign in the Fukushima Prefecture. Compared with the incidence rate in Japan in 2007, the ultrasonography survey is predicted to increase baseline thyroid cancer incidence by a factor of 7.4 (95 % CI 0.95; 17.3). Under the condition of continued screening, thyroid cancer during the first fifty years after the accident is predicted to be detected for about 2 % of the screened population. The prediction of radiation-related thyroid cancer in the most exposed fraction (a few ten thousand persons) of the screened population of the Fukushima Prefecture has a large uncertainty with the best estimates of the average risk of 0.1-0.3 %, depending on average dose.

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.

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., (© Springer-Verlag 2010)

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., (Copyright 2010 Elsevier B.V. All rights reserved.)

In this article scenarios have been developed, which simulate screening effects in ecological and cohort studies of thyroid cancer incidence among Ukrainians, whose thyroids have been exposed to (131)I in the aftermath of the Chernobyl accident. If possible, the scenarios were based on directly observed data, such as the population size, dose distributions and thyroid cancer cases. Two scenarios were considered where the screening effect on baseline cases is either equal to or larger than that of radiation-related thyroid cancer cases. For ecological studies in settlements with more than ten measurements of the (131)I activity in the human thyroid in May-June 1986, the screening bias appeared small (<19%) for all risk quantities. In the cohort studies, the excess absolute risk per dose was larger by a factor of 4 than in the general population. For an equal screening effect on baseline and radiation-related cancer (Scenario 1) the excess relative risk was about the same as in the general population. However, a differential screening effect (Scenario 2) produced a risk smaller by a factor of 2.5. A comparison with first results of the Ukrainian-US-American cohort study did not give any indication that a differential screening effect has a marked influence on the risk estimates. The differences in the risk estimates from ecological studies and cohort studies were explained by the different screening patterns in the general population and in the much smaller cohort. The present investigations are characterized by dose estimates for many settlements which are very weakly correlated with screening, the confounding variable. The results show that under these conditions ecological studies may provide risk estimates with an acceptable bias.