Occupational Exposure to Ionizing Radiation: Models for Policy Making

电离辐射的职业暴露：政策制定模型

• 批准号: 10176134
• 负责人: DAVID B RICHARDSON
• 金额: $ 27.1万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10176134
• 关键词: Occupational; Exposure; Ionizing; Radiation; Models

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

抽象的 估计每年有150万美国工人职业接触电离辐射。的 这个数字，每年在美国进行大约120,000名工人进行辐射暴露监测 能源部设施部，而在与医疗合作时，成千上万的其他人都在暴露 辐射，核电发电和射线照相等工业过程的来源 辐照。与许多其他已建立的职业致癌物相反，已从 随着时间的流逝，美国的工作场所，暴露于辐射的工人的数量并没有减少，而是成长 随着辐射在医学和其他工业环境中的新用途的出现。我们对 辐射暴露的健康影响来自各种来源，包括实验室研究，研究 医疗辐射和原子弹幸存者的研究。但是，工人的流行病学研究 一个特殊的地方，因为此类研究允许直接评估不需要推断的证据 从细胞到生物，物种之间或种群之间的跨性别和暴露条件。 直到最近，对辐射工人的流行病学研究往往会导致不精确的风险估计 置信区间通常跨越零。因此，日本原子的流行病学分析 炸弹幸存者已成为辐射保护标准的主要定量基础。然而， 最近的流行病学研究表明，池队列数据已经产生了辐射风险的估计值 置信区间。加强保护当代辐射工人的基础，并改善 过去，我们对过去暴露的工人的薪酬决定，我们建议使用最先进的统计分析 应用于最近已经组装的数据的参数G-Gramula方法作为主要的一部分 国际努力为英国，法国和美国雇用的核工人汇集数据。 具体而言，我们建议评估：1）辐射效应的时间修饰剂（时间暴露，年龄at-at- 暴露并达到年龄）； 2）癌症类型的辐射效应变化； 3）辐射对非 - 癌症死亡原因。此外，我们提出了评估4）剂量和剂量效果的贝叶斯方法； 5）由于结果错误分类而引起的偏见。因为流行病学发现的因果解释是 通过可重复性和一致性的证据加强，我们将评估得出的结果的一致性 来自这些国际队列。提出的方法使我们能够最大程度地减少偏见，包括健康的工作者 幸存者偏见，正式结合来自不同研究的信息，并利用这些最近合并的核 工人队列数据。预计该研究项目的发现将对 了解效果职业辐射暴露。这项工作将通过 提高对辐射引起的癌症的理解，并加强政策的基础 建议。 1

项目成果

Reducing Bias Due to Exposure Measurement Error Using Disease Risk Scores.

使用疾病风险评分减少由于暴露测量误差造成的偏差。

• DOI: 10.1093/aje/kwaa208
• 发表时间: 2021
• 期刊: American journal of epidemiology
• 影响因子: 5
• 作者: Richardson,DavidB;Keil,AlexanderP;Cole,StephenR;Edwards,JessieK
• 通讯作者: Edwards,JessieK

Single proxy control.

单一代理控制。

• DOI: 10.1093/biomtc/ujae027
• 发表时间: 2024
• 期刊: Biometrics
• 影响因子: 1.9
• 作者: Park,Chan;Richardson,DavidB;TchetgenTchetgen,EricJ
• 通讯作者: TchetgenTchetgen,EricJ

Amplification of Bias Due to Exposure Measurement Error.

由于曝光测量误差而导致的偏差放大。

• DOI: 10.1093/aje/kwab228
• 发表时间: 2022
• 期刊: American journal of epidemiology
• 影响因子: 5
• 作者: Richardson,DavidB;Keil,AlexanderP;Cole,StephenR
• 通讯作者: Cole,StephenR

Standardizing Discrete-Time Hazard Ratios With a Disease Risk Score.

使用疾病风险评分标准化离散时间风险比。

• DOI: 10.1093/aje/kwaa061
• 发表时间: 2020
• 期刊: American journal of epidemiology
• 影响因子: 5
• 作者: Richardson,DavidB;Keil,AlexanderP;Edwards,JessieK;Kinlaw,AlanC;Cole,StephenR
• 通讯作者: Cole,StephenR

Risk of cancer associated with low-dose radiation exposure: comparison of results between the INWORKS nuclear workers study and the A-bomb survivors study.

• DOI: 10.1007/s00411-020-00890-7
• 发表时间: 2021-03
• 期刊: Radiation and environmental biophysics
• 影响因子: 1.7
• 作者: Leuraud K;Richardson DB;Cardis E;Daniels RD;Gillies M;Haylock R;Moissonnier M;Schubauer-Berigan MK;Thierry-Chef I;Kesminiene A;Laurier D
• 通讯作者: Laurier D