时间积分辐射风险度量与生存率的人群间变异性。
Time-integrated radiation risk metrics and interpopulation variability of survival.
发表日期:2023 Sep 03
作者:
Alexander Ulanowski, Nobuhiko Ban, Kotaro Ozasa, Werner Rühm, Edward Semones, Mark Shavers, Ludovic Vaillant
来源:
Zeitschrift fur Medizinische Physik
摘要:
国际辐射防护委员会第115工作小组致力于研究与太空辐射相关的任务相关暴露以及太空机组成员的相关健康风险,包括癌症发展的风险。累计辐射风险估计的不确定性来自考虑的健康结果(即癌症)的随机性,统计推断和模型参数的不确定性,用于人口统计预测的未知世俗趋势以及个体或人群之间的存活特性的未知变异性。当处理大的人群时,通常忽略存活率的变异性,这可以假设为在特定国家或全球平均水平上的统计数据对当代普通人口具有很好的代表性。太空机组成员在许多方面与代表普通人口的个体不同,包括他们的生活方式和健康状况、营养、医疗保健、训练和教育。本模型研究探讨了辐射和寿命对个体响应的个性化。115工作小组目前正在评估各种风险度量标准在量化太空机组成员辐射相关癌症风险方面的适用性和鲁棒性。本文展示了存活曲线的人口间变异性对于癌症辐射风险的时间积分估计值和不确定性的影响。版权所有©2023作者。由Elsevier GmbH出版。保留所有权利。
Task Group 115 of the International Commission on Radiological Protection is focusing on mission-related exposures to space radiation and concomitant health risks for space crew members including, among others, risk of cancer development. Uncertainties in cumulative radiation risk estimates come from the stochastic nature of the considered health outcome (i.e., cancer), uncertainties of statistical inference and model parameters, unknown secular trends used for projections of population statistics and unknown variability of survival properties between individuals or population groups. The variability of survival is usually ignored when dealing with large groups, which can be assumed well represented by the statistical data for the contemporary general population, either in a specific country or world averaged. Space crew members differ in many aspects from individuals represented by the general population, including, for example, their lifestyle and health status, nutrition, medical care, training and education. The individuality of response to radiation and lifespan is explored in this modelling study. Task Group 115 is currently evaluating applicability and robustness of various risk metrics for quantification of radiation-attributed risks of cancer for space crew members. This paper demonstrates the impact of interpopulation variability of survival curves on values and uncertainty of the estimates of the time-integrated radiation risk of cancer.Copyright © 2023 The Author(s). Published by Elsevier GmbH.. All rights reserved.