Occupational Exposure to Ionizing Radiation: Models for Policy Making

摘要 据估计，每年有150万美国工人在职业上暴露于电离辐射。的 根据这个数字，美国每年大约有120，000名工人受到辐射照射的监测 能源部的设施，而成千上万的其他人在与医疗机构合作时暴露 辐射源、核能发电以及放射线照相术和食品等工业过程 辐照与许多其他已确定的职业致癌物相比， 随着时间的推移，美国工作场所暴露在辐射下的工人数量不仅没有减少，反而有所增加 随着辐射在医学和其他工业环境中的新用途的出现。我们理解 辐射暴露对健康的影响来自各种来源，包括实验室研究、 医学辐射和原子弹幸存者的研究。然而，对工人的流行病学研究表明， 一个特殊的地方，因为这样的研究允许直接评估证据，而不需要外推 从细胞到生物体，在物种之间，或在种群和暴露条件之间。 直到最近，对辐射工作人员的流行病学研究往往导致不精确的风险估计， 置信区间，往往跨越空。因此，日本原子能机构的流行病学分析 原子弹爆炸幸存者是辐射防护标准的主要定量依据。但是，在这方面， 最近的流行病学研究汇集了队列数据，得出了辐射风险估计， 置信区间加强当代放射工作者的防护基础， 过去暴露的工人的赔偿决定，我们提出了最先进的统计分析，使用 参数g公式方法应用于最近已被组装为主要的一部分的数据， 这是一项国际努力，旨在汇集英国、法国和美国雇用的核工作人员的数据。 具体而言，我们建议评估：1）辐射效应的时间修饰符（暴露后时间，年龄， （2）辐射对不同癌症类型的影响;（3）辐射对非癌症患者的影响。 癌症死亡原因此外，我们提出贝叶斯方法来评估4）剂量和剂量率效应; 5）由于结果错误分类而产生的偏倚。因为对流行病学调查结果的因果解释是 通过可重复性和一致性的证据，我们将评估得出的结果的一致性 从这些国际群体中。所提出的方法使我们能够最大限度地减少偏见，包括健康的工人 幸存者偏见，正式联合收割机信息从不同的研究，并利用这些最近汇集的核 工人队列数据。该研究项目的结果预计将对以下方面产生重大影响 了解职业辐射照射的影响。这项工作将解决诺拉的优先事项， 提高对辐射致癌的认识，加强政策基础 建议. 1

ABSTRACT There are an estimated 1.5 million U.S. workers occupationally exposed to ionizing radiation each year. Of this number, approximately 120,000 workers are monitored annually for radiation exposure at United States Department of Energy facilities, while hundreds of thousands of others are exposed while working with medical sources of radiation, nuclear power generation, and industrial processes such as radiography and food irradiation. In contrast to many other established occupational carcinogens, which have been removed from US workplaces over time, the number of radiation-exposed workers has not diminished, but rather has grown with the emergence of new uses of radiation in medicine and other industrial settings. Our understanding of the health effects of radiation exposure comes from a variety of sources, including laboratory research, studies of medical irradiation, and studies of atomic bomb survivors. However, epidemiological studies of workers hold a special place because such studies allow direct evaluation of evidence that does not require extrapolation from cells to organisms, between species, or across populations and exposure conditions. Until recently, epidemiological studies of radiation workers tended to result in imprecise risk estimates with confidence intervals that often spanned the null. Consequently, epidemiological analyses of Japanese atomic bomb survivors have served as the primary quantitative basis for radiation protection standards. However, recent epidemiological studies that pool cohort data have yielded radiation risk estimates with relatively tight confidence intervals. To strengthen the basis for protection of contemporary radiation workers, and to improve compensation decisions for workers exposed in the past, we propose state-of-the-art statistical analysis using parametric g-formula methods applied to data that recently have been assembled as part of a major international effort to pool data for nuclear workers employed in the United Kingdom, France, and USA. Specifically, we propose to assess: 1) temporal modifiers of radiation effects (time-since-exposure, age-at- exposure, and attained age); 2) variation in radiation effects by type of cancer; and, 3) radiation effects on non- cancer causes of death. In addition, we propose Bayesian methods to evaluate 4) dose and dose-rate effects; and, 5) bias due to outcome misclassification. Because a causal interpretation of epidemiological findings is strengthened by evidence of reproducibility and consistency, we will assess the consistency of results derived from these international cohorts. The proposed methods allow us to minimize bias, including healthy worker survivor bias, formally combine information from different studies, and leverage these recently pooled nuclear worker cohort data. The findings of this research project are expected to have substantial impact on understanding of the effects occupational radiation exposures. The work will address NORA priorities by improving understanding of cancer caused by radiation and strengthening the basis for policy recommendations. 1