RESUMO
OBJECTIVES: Increased risks of central nervous system (CNS) tumors and leukemia associated with computed tomography (CT) exposure during childhood have been reported in recent epidemiological studies. However, no evidence of increased risks was suggested in a previous analysis of the French CT cohort. This study benefits from an updated cohort with a longer follow-up and a larger sample size of patients. METHODS: The patients were followed from the date of their first CT (between 2000 and 2011) until their date of cohort exit defined as the earliest among the following: 31 December 2016, date of death, date of first cancer diagnosis or date of their 18th birthday. Cancer incidence, vital status, cancer predisposing factors (PFs), and additional CT scans were collected via external national databases. Hazard ratios (HRs) associated to cumulative organ doses and sex were estimated from Cox models. RESULTS: At the end of follow-up, mean cumulative doses were 27.7 and 10.3 mGy for the brain and the red bone marrow (RBM), respectively. In patients without PFs, an HR per 10 mGy of 1.05 (95% CI: 1.01-1.09) for CNS tumors, 1.17 (95% CI: 1.09-1.26) for leukemia, and 0.96 (95% CI: 0.63-1.45) for lymphoma was estimated. These estimates were not modified by the inclusion of CT scans performed outside the participating hospitals or after the inclusion period. CONCLUSIONS: This study shows statistically significant dose-response relationships for CNS tumors and leukemia for patients without PFs. KEY POINTS: ⢠Computed tomography is the most important contributor to the collective dose for diagnostic imaging to the French population. ⢠Concerns have been raised about possible cancer risks, particularly after exposure to CT in childhood, due to the greater radiation sensitivity of children and to their longer life expectancy. ⢠Analysis of the updated French CT cohort shows statistically significant dose-response relationships for CNS tumors and leukemia.
Assuntos
Neoplasias do Sistema Nervoso Central , Leucemia , Neoplasias Induzidas por Radiação , Criança , Estudos de Coortes , Humanos , Incidência , Neoplasias Induzidas por Radiação/epidemiologia , Neoplasias Induzidas por Radiação/etiologia , Doses de Radiação , Tomografia Computadorizada por Raios X/efeitos adversos , Tomografia Computadorizada por Raios X/métodosRESUMO
As multifactorial and chronic diseases, cancers are among these pathologies for which the exposome concept is essential to gain more insight into the associated etiology and, ultimately, lead to better primary prevention strategies for public health. Indeed, cancers result from the combined influence of many genetic, environmental and behavioral stressors that may occur simultaneously and interact. It is thus important to properly account for multifactorial exposure patterns when estimating specific cancer risks at individual or population level. Nevertheless, the risk factors, especially environmental, are still too often considered in isolation in epidemiological studies. Moreover, major statistical difficulties occur when exposures to several factors are highly correlated due, for instance, to common sources shared by several pollutants. Suitable statistical methods must then be used to deal with these multicollinearity issues. In this work, we focused on the specific problem of estimating a disease risk from highly correlated environmental exposure covariates and a censored survival outcome. We extended Bayesian profile regression mixture (PRM) models to this context by assuming an instantaneous excess hazard ratio disease sub-model. The proposed hierarchical model incorporates an underlying truncated Dirichlet process mixture as an attribution sub-model. A specific adaptive Metropolis-Within-Gibbs algorithm-including label switching moves-was implemented to infer the model. This allows simultaneously clustering individuals with similar risks and similar exposure characteristics and estimating the associated risk for each group. Our Bayesian PRM model was applied to the estimation of the risk of death by lung cancer in a cohort of French uranium miners who were chronically and occupationally exposed to multiple and correlated sources of ionizing radiation. Several groups of uranium miners with high risk and low risk of death by lung cancer were identified and characterized by specific exposure profiles. Interestingly, our case study illustrates a limit of MCMC algorithms to fit full Bayesian PRM models even if the updating schemes for the cluster labels incorporate label-switching moves. Then, although this paper shows that Bayesian PRM models are promising tools for exposome research, it also opens new avenues for methodological research in this class of probabilistic models.
Assuntos
Exposição Ambiental , Modelos Estatísticos , Teorema de Bayes , Estudos de Coortes , Exposição Ambiental/efeitos adversos , Humanos , Radiação IonizanteRESUMO
Exposure measurement error can be seen as one of the most important sources of uncertainty in studies in epidemiology. When the aim is to assess the effects of measurement error on statistical inference or to compare the performance of several methods for measurement error correction, it is indispensable to be able to generate different types of measurement error. This paper compares two approaches for the generation of Berkson error, which have recently been applied in radiation epidemiology, in their ability to generate exposure data that satisfy the properties of the Berkson model. In particular, it is shown that the use of one of the methods produces results that are not in accordance with two important properties of Berkson error.
Assuntos
Estudos Epidemiológicos , Modelos Estatísticos , Exposição à Radiação/efeitos adversos , Exposição à Radiação/análise , Projetos de Pesquisa , Humanos , Neoplasias Pulmonares/epidemiologia , Neoplasias Pulmonares/etiologia , Radônio/efeitos adversos , IncertezaRESUMO
Exposure measurement error represents one of the most important sources of uncertainty in epidemiology. When exposure uncertainty is not or only poorly accounted for, it can lead to biased risk estimates and a distortion of the shape of the exposure-response relationship. In occupational cohort studies, the time-dependent nature of exposure and changes in the method of exposure assessment may create complex error structures. When a method of group-level exposure assessment is used, individual worker practices and the imprecision of the instrument used to measure the average exposure for a group of workers may give rise to errors that are shared between workers, within workers or both. In contrast to unshared measurement error, the effects of shared errors remain largely unknown. Moreover, exposure uncertainty and magnitude of exposure are typically highest for the earliest years of exposure. We conduct a simulation study based on exposure data of the French cohort of uranium miners to compare the effects of shared and unshared exposure uncertainty on risk estimation and on the shape of the exposure-response curve in proportional hazards models. Our results indicate that uncertainty components shared within workers cause more bias in risk estimation and a more severe attenuation of the exposure-response relationship than unshared exposure uncertainty or exposure uncertainty shared between individuals. These findings underline the importance of careful characterisation and modeling of exposure uncertainty in observational studies.
Assuntos
Exposição Ambiental , Modelos de Riscos Proporcionais , Estudos de Coortes , HumanosRESUMO
Many occupational cohort studies on underground miners have demonstrated that radon exposure is associated with an increased risk of lung cancer mortality. However, despite the deleterious consequences of exposure measurement error on statistical inference, these analyses traditionally do not account for exposure uncertainty. This might be due to the challenging nature of measurement error resulting from imperfect surrogate measures of radon exposure. Indeed, we are typically faced with exposure uncertainty in a time-varying exposure variable where both the type and the magnitude of error may depend on period of exposure. To address the challenge of accounting for multiplicative and heteroscedastic measurement error that may be of Berkson or classical nature, depending on the year of exposure, we opted for a Bayesian structural approach, which is arguably the most flexible method to account for uncertainty in exposure assessment. We assessed the association between occupational radon exposure and lung cancer mortality in the French cohort of uranium miners and found the impact of uncorrelated multiplicative measurement error to be of marginal importance. However, our findings indicate that the retrospective nature of exposure assessment that occurred in the earliest years of mining of this cohort as well as many other cohorts of underground miners might lead to an attenuation of the exposure-risk relationship. More research is needed to address further uncertainties in the calculation of lung dose, since this step will likely introduce important sources of shared uncertainty.
Assuntos
Mineração , Exposição Ocupacional/efeitos adversos , Exposição Ocupacional/análise , Radônio/efeitos adversos , Projetos de Pesquisa , Urânio , Adolescente , Adulto , Idoso , Teorema de Bayes , Estudos de Coortes , Relação Dose-Resposta à Radiação , França , Humanos , Neoplasias Pulmonares/etiologia , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Neoplasias Induzidas por Radiação/etiologia , Incerteza , Adulto JovemRESUMO
The potential health impacts of chronic exposures to uranium, as they occur in occupational settings, are not well characterized. Most epidemiological studies have been limited by small sample sizes, and a lack of harmonization of methods used to quantify radiation doses resulting from uranium exposure. Experimental studies have shown that uranium has biological effects, but their implications for human health are not clear. New studies that would combine the strengths of large, well-designed epidemiological datasets with those of state-of-the-art biological methods would help improve the characterization of the biological and health effects of occupational uranium exposure. The aim of the European Commission concerted action CURE (Concerted Uranium Research in Europe) was to develop protocols for such a future collaborative research project, in which dosimetry, epidemiology and biology would be integrated to better characterize the effects of occupational uranium exposure. These protocols were developed from existing European cohorts of workers exposed to uranium together with expertise in epidemiology, biology and dosimetry of CURE partner institutions. The preparatory work of CURE should allow a large scale collaborative project to be launched, in order to better characterize the effects of uranium exposure and more generally of alpha particles and low doses of ionizing radiation.
Assuntos
Doenças Profissionais/epidemiologia , Doenças Profissionais/etiologia , Exposição Ocupacional/efeitos adversos , Exposição Ocupacional/análise , Lesões por Radiação/epidemiologia , Radiobiologia/métodos , Medição de Risco/métodos , Urânio/toxicidade , Europa (Continente)/epidemiologia , Humanos , Doses de Radiação , Radiometria/métodos , Fatores de RiscoRESUMO
The investigation of potential adverse health effects of occupational exposures to ionizing radiation, on uranium miners, is an important area of research. Radon is a well-known carcinogen for lung, but the link between radiation exposure and other diseases remains controversial, particularly for kidney cancer. The aims of this study were therefore to perform external kidney cancer mortality analyses and to assess the relationship between occupational radiation exposure and kidney cancer mortality, using competing risks methodology, from two uranium miners cohorts. The French (n = 3,377) and German (n = 58,986) cohorts of uranium miners included 11 and 174 deaths from kidney cancer. For each cohort, the excess of kidney cancer mortality has been assessed by standardized mortality ratio (SMR) corrected for the probability of known causes of death. The associations between cumulative occupational radiation exposures (radon, external gamma radiation and long-lived radionuclides) or kidney equivalent doses and both the cause-specific hazard and the probability of occurrence of kidney cancer death have been estimated with Cox and Fine and Gray models adjusted to date of birth and considering the attained age as the timescale. No significant excess of kidney cancer mortality has been observed neither in the French cohort (SMR = 1.49, 95 % confidence interval [0.73; 2.67]) nor in the German cohort (SMR = 0.91 [0.77; 1.06]). Moreover, no significant association between kidney cancer mortality and any type of occupational radiation exposure or kidney equivalent dose has been observed. Future analyses based on further follow-up updates and/or large pooled cohorts should allow us to confirm or not the absence of association.
Assuntos
Neoplasias Renais/etiologia , Neoplasias Renais/mortalidade , Mineração , Neoplasias Induzidas por Radiação/etiologia , Neoplasias Induzidas por Radiação/mortalidade , Exposição Ocupacional/efeitos adversos , Urânio , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , França/epidemiologia , Raios gama/efeitos adversos , Alemanha/epidemiologia , Humanos , Masculino , Pessoa de Meia-Idade , Distribuição de Poisson , Radônio/efeitos adversos , Análise de Regressão , Risco , Adulto JovemRESUMO
The potential adverse effects associated with exposure to ionizing radiation from computed tomography (CT) in pediatrics must be characterized in relation to their expected clinical benefits. Additional epidemiological data are, however, still awaited for providing a lifelong overview of potential cancer risks. This paper gives predictions of potential lifetime risks of cancer incidence that would be induced by CT examinations during childhood in French routine practices in pediatrics. Organ doses were estimated from standard radiological protocols in 15 hospitals. Excess risks of leukemia, brain/central nervous system, breast and thyroid cancers were predicted from dose-response models estimated in the Japanese atomic bomb survivors' dataset and studies of medical exposures. Uncertainty in predictions was quantified using Monte Carlo simulations. This approach predicts that 100,000 skull/brain scans in 5-year-old children would result in eight (90 % uncertainty interval (UI) 1-55) brain/CNS cancers and four (90 % UI 1-14) cases of leukemia and that 100,000 chest scans would lead to 31 (90 % UI 9-101) thyroid cancers, 55 (90 % UI 20-158) breast cancers, and one (90 % UI <0.1-4) leukemia case (all in excess of risks without exposure). Compared to background risks, radiation-induced risks would be low for individuals throughout life, but relative risks would be highest in the first decades of life. Heterogeneity in the radiological protocols across the hospitals implies that 5-10 % of CT examinations would be related to risks 1.4-3.6 times higher than those for the median doses. Overall excess relative risks in exposed populations would be 1-10 % depending on the site of cancer and the duration of follow-up. The results emphasize the potential risks of cancer specifically from standard CT examinations in pediatrics and underline the necessity of optimization of radiological protocols.
Assuntos
Neoplasias Induzidas por Radiação/epidemiologia , Neoplasias Induzidas por Radiação/etiologia , Tomografia Computadorizada por Raios X/efeitos adversos , Adulto , Criança , Exposição Ambiental/efeitos adversos , Feminino , Humanos , Lactente , Recém-Nascido , Masculino , Medição de Risco , IncertezaRESUMO
Previous epidemiological studies and quantitative risk assessments (QRA) have suggested that natural background radiation may be a cause of childhood leukemia. The present work uses a QRA approach to predict the excess risk of childhood leukemia in France related to three components of natural radiation: radon, cosmic rays and terrestrial gamma rays, using excess relative and absolute risk models proposed by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). Both models were developed from the Life Span Study (LSS) of Japanese A-bomb survivors. Previous risk assessments were extended by considering uncertainties in radiation-related leukemia risk model parameters as part of this process, within a Bayesian framework. Estimated red bone marrow doses cumulated during childhood by the average French child due to radon, terrestrial gamma and cosmic rays are 4.4, 7.5 and 4.3 mSv, respectively. The excess fractions of cases (expressed as percentages) associated with these sources of natural radiation are 20 % [95 % credible interval (CI) 0-68 %] and 4 % (95 % CI 0-11 %) under the excess relative and excess absolute risk models, respectively. The large CIs, as well as the different point estimates obtained under these two models, highlight the uncertainties in predictions of radiation-related childhood leukemia risks. These results are only valid provided that models developed from the LSS can be transferred to the population of French children and to chronic natural radiation exposures, and must be considered in view of the currently limited knowledge concerning other potential risk factors for childhood leukemia. Last, they emphasize the need for further epidemiological investigations of the effects of natural radiation on childhood leukemia to reduce uncertainties and help refine radiation protection standards.