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基于1958 - 1998年发病数据的多模型推断得出的原子弹爆炸幸存者患乳腺癌的风险

Breast cancer risk in atomic bomb survivors from multi-model inference with incidence data 1958-1998.

作者信息

Kaiser J C, Jacob P, Meckbach R, Cullings H M

机构信息

Helmholtz-Zentrum München, German Research Centre for Environmental Health, Institute of Radiation Protection, 85764, Neuherberg, Germany.

出版信息

Radiat Environ Biophys. 2012 Mar;51(1):1-14. doi: 10.1007/s00411-011-0387-4. Epub 2011 Sep 23.

Abstract

Breast cancer risk from radiation exposure has been analyzed in the cohort of Japanese a-bomb survivors using empirical models and mechanistic two-step clonal expansion (TSCE) models with incidence data from 1958 to 1998. TSCE models rely on a phenomenological representation of cell transition processes on the path to cancer. They describe the data as good as empirical models and this fact has been exploited for risk assessment. Adequate models of both types have been selected with a statistical protocol based on parsimonious parameter deployment and their risk estimates have been combined using multi-model inference techniques. TSCE models relate the radiation risk to cell processes which are controlled by age-increasing rates of initiating mutations and by changes in hormone levels due to menopause. For exposure at young age, they predict an enhanced excess relative risk (ERR) whereas the preferred empirical model shows no dependence on age at exposure. At attained age 70, the multi-model median of the ERR at 1 Gy decreases moderately from 1.2 Gy(-1) (90% CI 0.72; 2.1) for exposure at age 25 to a 30% lower value for exposure at age 55. For cohort strata with few cases, where model predictions diverge, uncertainty intervals from multi-model inference are enhanced by up to a factor of 1.6 compared to the preferred empirical model. Multi-model inference provides a joint risk estimate from several plausible models rather than relying on a single model of choice. It produces more reliable point estimates and improves the characterization of uncertainties. The method is recommended for risk assessment in practical radiation protection.

摘要

利用经验模型和机制性两步克隆扩增(TSCE)模型,并结合1958年至1998年的发病率数据,对日本原子弹爆炸幸存者队列中辐射暴露导致的乳腺癌风险进行了分析。TSCE模型依赖于癌症发生过程中细胞转变过程的唯象学表示。它们对数据的描述与经验模型一样好,这一事实已被用于风险评估。已根据简约参数部署的统计方案选择了两种类型的适当模型,并使用多模型推断技术对其风险估计值进行了合并。TSCE模型将辐射风险与细胞过程相关联,这些细胞过程由起始突变率随年龄增加以及绝经导致的激素水平变化所控制。对于年轻时的暴露,它们预测超额相对危险度(ERR)会增加,而首选的经验模型显示对暴露年龄没有依赖性。在达到70岁时,1 Gy剂量下ERR的多模型中位数从25岁时暴露的1.2 Gy⁻¹(90%可信区间0.72;2.1)适度下降至55岁时暴露的低30%的值。对于病例数较少的队列分层,当模型预测出现分歧时,与首选的经验模型相比,多模型推断的不确定性区间最多会扩大1.6倍。多模型推断提供了来自几个合理模型的联合风险估计,而不是依赖于单一的选择模型。它产生更可靠的点估计,并改善了不确定性的表征。该方法推荐用于实际辐射防护中的风险评估。

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