Stochastic models for radiation carcinogenesis: tempora*

辐射致癌的随机模型：tempora*

• 批准号: 6592904
• 负责人: SURESH H MOOLGAVKAR
• 金额: $ 24.7万
• 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/6592904
• 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.

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