Assessment methods for inter-laboratory comparisons of the dicentric assay

To test the performance of different algorithms that can be used in inter-laboratory comparisons based on dicentric chromosome analysis, and to evaluate the impact of considering <i>a priori</i> values different to calculate individual laboratory performance based on the ionizing radiation dose estimation. Mean and standard deviation estimations in inter-laboratory comparisons are tested on simulated data and data from previously published inter-laboratory comparisons using three robust algorithms, Algorithm A, Algorithm B and Q/Hampel, all programmed in R-project language and implemented in a Shiny application. The simulated data were generated assuming three different probabilities to contaminate inter-laboratory comparisons samples with atypical dose values. Comparison between different algorithms was also done using published exercises where blood samples were irradiated at 0 and 0.7 Gy that represent a challenge for the assessment of an inter-laboratory comparison. The best performance was obtained with the Q/Hampel algorithm for the estimation of the dose mean and with the Algorithm B for the estimation of the dose standard deviation under the conditions tested in the simulations. The Q/Hampel algorithm showed the best performance when non-irradiated samples were evaluated and there was a high proportion of identical values. The presence identical values cause the Algorithm B to fail. Real examples illustrating the need to consider standard deviation priors, and the need to use algorithms resistant to a high proportion of identical values are presented. Q/Hampel algorithm is a serious candidate to estimate the dose mean in the inter-laboratory comparisons, and to estimate both parameters when the proportion of identical values equals or higher than the half of the results. When the proportion of identical values is less than the half of the results, the Algorithm B should be considered as a candidate to estimate the standard deviation in the inter-laboratory comparisons with small number of laboratories. We remark that special attention is needed to establish prior definitions of standard deviation in the assessment of inter-laboratory dicentric assay comparisons.

本数据集旨在测试可应用于基于双着丝粒染色体分析（dicentric chromosome analysis）的实验室间比对的各类算法性能，并评估采用不同先验（a priori）值、基于电离辐射剂量估算来评估单个实验室性能时所产生的影响。本研究针对三种稳健算法——算法A、算法B与Q/Hampel——，基于模拟数据及此前已发表的实验室间比对数据集，测试了实验室间比对场景下的均值与标准差估算效果；上述算法均以R语言（R-project language）编写，并已在Shiny应用程序（Shiny application）中实现部署。模拟数据的生成设定了三种不同的异常剂量值污染实验室间比对样本的概率。此外，本研究还借助已公开的比对实验开展算法对比：这些实验将血液样本分别辐照至0 Gy与0.7 Gy，该实验设置对实验室间比对的评估构成了一定挑战。在本次模拟测试的条件下，Q/Hampel算法在剂量均值估算方面表现最优，而算法B则在剂量标准差估算方面性能最佳。当评估未辐照样本且存在高比例相同值时，Q/Hampel算法展现出最优性能，而相同值的存在会导致算法B失效。本研究还提供了实际案例，用以说明在实验室间比对评估中需考虑标准差先验值，以及需使用可抵抗高比例相同值的算法的必要性。Q/Hampel算法可作为实验室间比对中剂量均值估算的有力候选方案，同时在相同值占比大于等于结果总数一半的场景下，也可用于两项参数的估算。当相同值占比低于结果总数一半时，针对实验室数量较少的实验室间比对，算法B可作为标准差估算的候选方案。本研究强调，在实验室间双着丝粒染色体分析比对的评估中，需特别关注标准差先验定义的建立。