Stochastic models for radiation carcinogenesis: tempora*

辐射致癌的随机模型：tempora*

• 批准号: 6773839
• 负责人: SURESH H MOOLGAVKAR
• 金额: $ 24.41万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-30 至 2005-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6773839
• 关键词: beta radiation; clinical research; colorectal neoplasms; disease /disorder proneness /risk; epidemiology; human data; human mortality; ionizing radiation; lung neoplasms; method development; model design /development; occupational hazard; radiation carcinogenesis; radiation dosage; relative biological effectiveness

DESCRIPTION: Current radiation protection standards are based largely on the experience of the cohort of A-bomb survivors. An important question, however, is whether the risks estimated in a Japanese war-time population exposed to instantaneous radiation can be transported to contemporary western populations exposed typically to protracted radiation in the workplace or elsewhere. Additional complications arise when age- and time-related factors in radiation exposure must be considered. A recent analysis of a large Canadian cohort of workers occupationally exposed to low-LET radiation using conventional epidemiological methods yielded estimates of excess relative risk that were an order of magnitude higher than those estimated from the A-bomb survivor's data. Can such inconsistencies be resolved? This research proposes to continue the development of methods based on the biological principles of multistage carcinogenesis for analyses of epidemiological data on radiation carcinogenesis. These methods, which complement the traditional epidemiological approaches to data analyses, can incorporate age- and time-dependent factors, including protraction of exposure, in a transparent way. These methods have been used by us and others for analyses of occupational cohort data and have yielded insights that would have been difficult to obtain using traditional methods alone. As an example an analysis of lung cancer incidence in the Canadian cohort referred to above using these methods showed that the inconsistency referred to above disappears when protraction is properly accounted for. The developed methods will be applied to substantial available data sets. Specifically, we propose to analyze the association between low-LET radiation and incidence of lung and colorectal cancer in Canadian National Dose Registry (CNDR) cohort with extended follow-up through 1999. We also propose to explore the association between low-LET radiation and mortality from lung cancer in the CNDR cohort and the cohort of nuclear workers in the Comprehensive Epidemiological Data Resource (CEDR) set up by the Department of Energy. The main goals of these analyses are to explore the effects of various age- and time-related factors and of protraction of exposure on the risk of radiation carcinogenesis.

产品说明： 目前的辐射防护标准主要是根据原子弹爆炸幸存者群体的经验制定的。然而，一个重要的问题是，在日本战时暴露于瞬时辐射的人群中估计的风险是否可以转移到当代西方人群中，这些人群通常在工作场所或其他地方长期暴露于辐射。当必须考虑辐射暴露中与年龄和时间有关的因素时，会出现其他并发症。最近使用常规流行病学方法对加拿大一大批因职业而受到低LET辐射的工人进行了分析，得出了超额相对风险的估计数，其数量级高于原子弹爆炸幸存者数据的估计数。这种不一致性能否得到解决？这项研究建议继续根据多阶段致癌作用的生物学原理开发方法，用于分析辐射致癌作用的流行病学数据。这些方法补充了传统的流行病学数据分析方法，能够以透明的方式纳入年龄和时间因素，包括暴露时间的延长。这些方法已经被我们和其他人用于分析职业队列数据，并产生了单独使用传统方法难以获得的见解。例如，使用这些方法对上文提到的加拿大队列中的肺癌发病率进行的分析表明，当适当考虑到延长时，上文提到的不一致性消失了。所开发的方法将应用于大量现有数据集。具体来说，我们建议分析低LET辐射和肺癌和结直肠癌的发病率之间的关系，在加拿大国家剂量登记处（CNDR）队列延长随访至1999年。我们还建议探索CNDR队列和能源部建立的综合流行病学数据资源（CEDR）中的核工人队列中低LET辐射与肺癌死亡率之间的关联。这些分析的主要目标是探索各种年龄和时间相关因素以及暴露时间延长对辐射致癌风险的影响。

项目成果

Decreases in occupational exposure to ionizing radiation among Canadian dental workers.

加拿大牙科工作者职业电离辐射暴露减少。

• 发表时间: 2005
• 期刊: Journal (Canadian Dental Association)
• 作者: Zielinski,JanM;Garner,MichaelJ;Krewski,Daniel;Ashmore,JPatrick;Band,PierreR;Fair,MarthaE;Jiang,Huixa;Letourneau,ErnestG;Semenciw,Robert;Sont,WillemN
• 通讯作者: Sont,WillemN

Effects of exposure uncertainties in the TSCE model and application to the Colorado miners data.

TSCE 模型中暴露不确定性的影响及其在科罗拉多州矿工数据中的应用。

• DOI: 10.1667/rr3089
• 发表时间: 2004
• 期刊: Radiation research
• 影响因子: 3.4
• 作者: Heidenreich,WolfgangF;Luebeck,EGeorg;Moolgavkar,SureshH
• 通讯作者: Moolgavkar,SureshH