Cui Ming, Xu Lili, Wang Huimin, Ju Shaoqing, Xu Shuizhu, Jing Rongrong
Center of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong, China.
Center of Laboratory Medicine, Affiliated Maternal and Child Health Hospital of Nantong University, Nantong, China.
Clin Biochem. 2017 Dec;50(18):1067-1072. doi: 10.1016/j.clinbiochem.2017.09.008. Epub 2017 Sep 18.
Measurement uncertainty (MU) is a metrological concept, which can be used for objectively estimating the quality of test results in medical laboratories. The Nordtest guide recommends an approach that uses both internal quality control (IQC) and external quality assessment (EQA) data to evaluate the MU. Bootstrap resampling is employed to simulate the unknown distribution based on the mathematical statistics method using an existing small sample of data, where the aim is to transform the small sample into a large sample. However, there have been no reports of the utilization of this method in medical laboratories. Thus, this study applied the Nordtest guide approach based on bootstrap resampling for estimating the MU.
We estimated the MU for the white blood cell (WBC) count, red blood cell (RBC) count, hemoglobin (Hb), and platelets (Plt). First, we used 6months of IQC data and 12months of EQA data to calculate the MU according to the Nordtest method. Second, we combined the Nordtest method and bootstrap resampling with the quality control data and calculated the MU using MATLAB software. We then compared the MU results obtained using the two approaches.
The expanded uncertainty results determined for WBC, RBC, Hb, and Plt using the bootstrap resampling method were 4.39%, 2.43%, 3.04%, and 5.92%, respectively, and 4.38%, 2.42%, 3.02%, and 6.00% with the existing quality control data (U [k=2]). For WBC, RBC, Hb, and Plt, the differences between the results obtained using the two methods were lower than 1.33%. The expanded uncertainty values were all less than the target uncertainties.
The bootstrap resampling method allows the statistical analysis of the MU. Combining the Nordtest method and bootstrap resampling is considered a suitable alternative method for estimating the MU.
测量不确定度（MU）是一个计量学概念，可用于客观评估医学实验室检测结果的质量。Nordtest指南推荐了一种利用内部质量控制（IQC）和外部质量评估（EQA）数据来评估测量不确定度的方法。自举重采样基于数理统计方法，利用现有的小样本数据模拟未知分布，目的是将小样本转化为大样本。然而，尚无该方法在医学实验室应用的报道。因此，本研究应用基于自举重采样的Nordtest指南方法来估计测量不确定度。
我们估计了白细胞（WBC）计数、红细胞（RBC）计数、血红蛋白（Hb）和血小板（Plt）的测量不确定度。首先，我们使用6个月的内部质量控制数据和12个月的外部质量评估数据，根据Nordtest方法计算测量不确定度。其次，我们将Nordtest方法和自举重采样与质量控制数据相结合，并使用MATLAB软件计算测量不确定度。然后，我们比较了两种方法获得的测量不确定度结果。
使用自举重采样方法确定的白细胞、红细胞、血红蛋白和血小板的扩展不确定度结果分别为4.39%、2.43%、3.04%和5.92%，使用现有质量控制数据（U [k=2]）时分别为4.38%、2.42%、3.02%和6.00%。对于白细胞、红细胞、血红蛋白和血小板，两种方法获得的结果差异低于1.33%。扩展不确定度值均小于目标不确定度。
自举重采样方法可对测量不确定度进行统计分析。将Nordtest方法和自举重采样相结合被认为是估计测量不确定度的一种合适的替代方法。
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