The risk assessment quantities called lifetime attributable risk (LAR) and risk of exposure-induced cancer (REIC) are used to calculate the cumulative cancer incidence risks for astronauts, attributable to radiation exposure accumulated during long term lunar and Mars missions. These risk quantities are based on the most recently published epidemiological data on the Life Span Study (LSS) of Japanese A-bomb survivors, who were exposed to γ-rays and neutrons. In order to analyse the impact of a different neutron RBE on the risk quantities, a model for the neutron relative biological effectiveness (RBE) relative to gammas in the LSS is developed based on an older dataset with less follow-up time. Since both risk quantities are based on uncertain quantities, such as survival curves, and REIC includes deterministic radiation induced non-cancer mortality risks, modelled with data based on the general population, the risks for astronauts may not be optimally estimated. The suitability of these risk assessment measures for the use of cancer risk calculation for astronauts is discussed. The work presented here shows that the use of a higher neutron RBE than the value of 10, traditionally used in the LSS risk models, can reduce the risks up to almost 50%. Additionally, including an excess absolute risk (EAR) baseline scaling also increases the risks by between 0.4% and 8.1% for the space missions considered in this study. Using just an EAR model instead of an equally weighted EAR and excess relative risk (ERR) model can decrease the cumulative risks for the considered missions by between 0.4% and 4.1% if no EAR baseline scaling is applied. If EAR baseline scaling is included, the calculated risks with the EAR- and the mixed model, as well as the risks calculated with just the ERR model are almost identical and only small differences in the uncertainties are visible.

称为终生归因风险 (LAR) 和暴露诱发癌症风险 (REIC) 的风险评估量用于计算宇航员的累积癌症发病风险，归因于长期月球和火星任务期间累积的辐射暴露。这些风险量是基于最近公布的关于日本原子弹幸存者寿命研究 (LSS) 的流行病学数据，他们暴露于 γ 射线和中子。为了分析不同中子 RBE 对风险量的影响，基于较旧的数据集开发了一个中子相对生物有效性 (RBE) 相对于 LSS 中伽马的模型，其后续时间较短。由于两个风险量都基于不确定的量，例如生存曲线，REIC 包括确定性辐射引起的非癌症死亡风险，以基于一般人群的数据为模型，宇航员的风险可能无法得到最佳估计。讨论了这些风险评估措施对宇航员癌症风险计算的适用性。这里介绍的工作表明，使用比 10 值更高的中子 RBE（传统上用于 LSS 风险模型）可以将风险降低近 50%。此外，包括超额绝对风险 (EAR) 基线缩放也会使本研究中考虑的太空任务的风险增加 0.4% 至 8.1%。仅使用 EAR 模型而不是同等加权的 EAR 和超额相对风险 (ERR) 模型可以将所考虑任务的累积风险降低 0.4% 到 4%。如果未应用 EAR 基线缩放，则为 1%。如果包含 EAR 基线缩放，则使用 E​​AR 模型和混合模型计算的风险以及仅使用 ERR 模型计算的风险几乎相同，并且在不确定性中只有很小的差异是可见的。