Grigoriev Institute for Medical Radiology of the Academy of Medical Science of Ukraine, Kharkiv, 61024, Ukraine.
Radiat Res. 2010 Oct;174(4):403-14. doi: 10.1667/RR2228.1.
The scientific literature concerning cytogenetic biodosimetry has been reviewed to identify the range of scenarios of radiation exposure where biodosimetry has been carried out. Limitations in the existing standardized statistical methodology have been identified and categorized, and the reasons for these limitations have been explored. Statistical problems generally occur due to either low numbers of aberrations leading to large uncertainties or deviations in aberration-per-cell distributions leading to over- or under-dispersion with respect to the Poisson model. A number of difficulties also stem from limitations of the classical statistical methodology, which requires that chromosome aberration yields be considered as something "fixed" and thus provides a deterministic estimate of radiation dose and associated confidence limits (because an assignment of a probability to an event is based solely on the observed frequency of occurrence of the event). Therefore, it is suggested that solutions to the listed problems should be based in the Bayesian framework. This will allow the investigator to take a probabilistic approach to analysis of cytogenetic data, which can be considered highly appropriate for biological dose estimation.
已经对有关细胞遗传学生物剂量学的科学文献进行了回顾，以确定已经进行生物剂量学的辐射暴露情况的范围。已经确定并分类了现有标准化统计方法学的局限性，并探讨了这些局限性的原因。统计问题通常是由于染色体畸变数量较少导致不确定性较大，或者由于每个细胞的畸变分布偏差导致泊松模型的过度或不足分散。许多困难还源于经典统计方法学的局限性，该方法要求将染色体畸变产量视为“固定”的，从而提供辐射剂量及其相关置信限的确定性估计（因为对事件的概率分配仅基于事件的观察到的发生频率）。因此，建议列出的问题的解决方案应基于贝叶斯框架。这将允许研究人员对细胞遗传学数据进行概率分析，这被认为非常适合生物剂量估计。
