Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC, USA.
Statistical Analysis and Data Center, Boston, MA, USA.
J Immunol Methods. 2014 Jul;409:82-90. doi: 10.1016/j.jim.2014.05.017. Epub 2014 Jun 7.
Since 1999, the National Institute of Allergy and Infectious Diseases Division of AIDS (NIAID DAIDS) has funded the Immunology Quality Assessment (IQA) Program with the goal of assessing proficiency in basic lymphocyte subset immunophenotyping for each North American laboratory supporting the NIAID DAIDS HIV clinical trial networks. Further, the purpose of this program is to facilitate an increase in the consistency of interlaboratory T-cell subset measurement (CD3(+)4(+)/CD3(+)8(+) percentages and absolute counts) and likewise, a decrease in intralaboratory variability. IQA T-cell subset measurement proficiency testing was performed over a ten-year period (January 2003-July 2012), and the results were analyzed via longitudinal analysis using mixed effects models. The goal of this analysis was to describe how a typical laboratory (a statistical modeling construct) participating in the IQA Program performed over time. Specifically, these models were utilized to examine trends in interlaboratory agreement, as well as successful passing of proficiency testing. Intralaboratory variability (i.e., precision) was determined by the repeated measures variance, while fixed and random effects were taken into account for changes in interlaboratory agreement (i.e., accuracy) over time. A flow cytometer (single-platform technology, SPT) or a flow cytometer/hematology analyzer (dual-platform technology, DPT) was also examined as a factor for accuracy and precision. The principal finding of this analysis was a significant (p<0.001) increase in accuracy of T-cell subset measurements over time, regardless of technology type (SPT or DPT). Greater precision was found in SPT measurements of all T-cell subset measurements (p<0.001), as well as greater accuracy of SPT on CD3(+)4(+)% and CD3(+)8(+)% assessments (p<0.05 and p<0.001, respectively). However, the interlaboratory random effects variance in DPT results indicates that for some cases DPT can have increased accuracy compared to SPT. Overall, these findings demonstrate that proficiency in and among IQA laboratories have, in general, improved over time and that platform type differences in performance do exist.
自 1999 年以来,美国国立过敏和传染病研究所艾滋病司(NIAID DAIDS)一直资助免疫质量评估(IQA)计划,旨在评估每个支持 NIAID DAIDS HIV 临床试验网络的北美实验室进行基本淋巴细胞亚群免疫表型分析的能力。此外,该计划的目的是促进实验室间 T 细胞亚群测量(CD3(+)4(+)/CD3(+)8(+)百分比和绝对值)的一致性提高,同时减少实验室内部的变异性。IQA T 细胞亚群测量能力测试在十年期间进行(2003 年 1 月至 2012 年 7 月),并通过使用混合效应模型进行纵向分析来分析结果。该分析的目的是描述参与 IQA 计划的典型实验室(统计建模结构)随时间的表现。具体来说,这些模型用于检查实验室间一致性的趋势,以及能力测试的成功通过。实验室内部变异性(即精密度)由重复测量方差确定,同时考虑了固定和随机效应,以说明随时间变化的实验室间一致性(即准确性)的变化。还检查了流式细胞仪(单平台技术,SPT)或流式细胞仪/血液学分析仪(双平台技术,DPT)作为准确性和精密度的一个因素。该分析的主要发现是,无论技术类型(SPT 或 DPT)如何,T 细胞亚群测量的准确性随着时间的推移都有显著(p<0.001)提高。在所有 T 细胞亚群测量的 SPT 测量中发现了更高的精密度(p<0.001),以及 SPT 对 CD3(+)4(+)%和 CD3(+)8(+)%评估的更高准确性(p<0.05 和 p<0.001)。然而,DPT 结果的实验室间随机效应方差表明,在某些情况下,DPT 可以比 SPT 具有更高的准确性。总体而言,这些发现表明,IQA 实验室的能力和实验室间的能力总体上随着时间的推移而提高,并且性能的平台类型差异确实存在。