Austrian Association for Quality Assurance and Standardization of Medical and Diagnostic Tests (ÖQUASTA), Vienna, Austria.
Center for Virology, Medical University of Vienna, Vienna, Austria.
Lancet Microbe. 2023 Dec;4(12):e1015-e1023. doi: 10.1016/S2666-5247(23)00286-0. Epub 2023 Nov 15.
The aim of external quality assessment (EQA) schemes is to evaluate the analytical performance of laboratories and test systems in a near-to-real-life setting. This monitoring service provides feedback to participant laboratories and serves as a control measure for the epidemiological assessment of the regional incidence of a pathogen, particularly during epidemics. Using data from EQA schemes implemented as a result of the intensive effort to monitor SARS-CoV-2 infections in Austria, we aimed to identify factors that explained the variation in laboratory performance for SARS-CoV-2 detection over the course of the COVID-19 pandemic.
For this observational study, we retrospectively analysed 6308 reverse transcriptase quantitative PCR (RT-qPCR) test results reported by 191 laboratories on 71 samples during 14 rounds of three SARS-CoV-2 pathogen detection EQA schemes in Austria between May 18, 2020, and Feb 20, 2023. We calculated the overall rates of false and true-negative, false and true-positive, and inconclusive results. We then assessed laboratory performance by estimating the sensitivity by testing whether significant variation in the odds of obtaining a true-positive result could be explained by virus concentration, laboratory type, or assay format. We also assessed whether laboratory performance changed over time.
4371 (93·7%) of 4663 qPCR test results were true-positive, 241 (5·2%) were false-negative, and 51 (1·1%) were inconclusive. The mean per-sample sensitivity was 99·7% in samples with high virus concentrations (1383 [99·4%] true-positive, three [0·2%] false-negative, and five [0·4%] inconclusive results for 1391 tests in which the sample cycle threshold was ≤32), whereas detection rates were lower in samples with low virus concentrations (mean per-sample sensitivity 92·5%; 2988 [91·3%] true-positive, 238 [7·3%] false-negative, and 46 [1·4%] inconclusive results for 3272 tests in which the cycle threshold was >32). Of the 1645 results expected to be negative, 1561 (94·9%) were correctly reported as negative, 10 (0·6%) were incorrectly reported as positive, and 74 (4·5%) were reported as inconclusive. Notably, the overall performance of the tests did not change significantly over time. The odds of reporting a correct result were 2·94 (95% CI 1·75-4·96) times higher for a medical laboratory than for a non-medical laboratory, and 4·60 (2·91-7·41) times greater for automated test systems than for manual test systems. Automated test systems within medical laboratories had the highest sensitivity when compared with systems requiring manual intervention in both medical and non-medical laboratories.
High rates of false-negativity in all PCR analyses evaluated in comprehensive, multiple, and repeated EQA schemes outline a clear path for improvement in the future. The performance of some laboratories (eg, non-medical laboratories or those using non-automated test systems) should receive additional scrutiny-for example, by requiring additional EQA schemes for certification or accreditation-if the aggregated data from EQA rounds suggest lower sensitivity than that recorded by others. This strategy will provide assurances that epidemiological data as a whole are reliable when testing on such a large scale. Although performance did not improve over time, we cannot exclude extenuating circumstances-such as shortages and weakened supply chains-that could have prevented laboratories from seeking alternative methods to improve performance.
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外部质量评估 (EQA) 计划的目的是在接近真实生活的环境中评估实验室和测试系统的分析性能。该监测服务为参与实验室提供反馈,并作为对区域病原体发病率进行流行病学评估的控制措施,特别是在疫情期间。利用在奥地利密集监测 SARS-CoV-2 感染过程中实施 EQA 计划所产生的数据,我们旨在确定在 COVID-19 大流行期间解释 SARS-CoV-2 检测实验室性能变化的因素。
在这项观察性研究中,我们回顾性分析了 2020 年 5 月 18 日至 2023 年 2 月 20 日期间奥地利三个 SARS-CoV-2 病原体检测 EQA 计划的 14 轮中,191 个实验室对 71 个样本进行的 6308 次逆转录定量 PCR (RT-qPCR) 测试结果。我们计算了假阴性和真阴性、假阳性和真阳性以及不确定结果的总体率。然后,我们通过估计灵敏度来评估实验室性能,方法是检验病毒浓度、实验室类型或检测方法是否可以显著解释获得真阳性结果的可能性。我们还评估了实验室性能是否随时间变化。
在 4663 次 qPCR 测试结果中,4371 次(93.7%)为真阳性,241 次(5.2%)为假阴性,51 次(1.1%)为不确定。在高病毒浓度样本中(1391 次检测中,样本循环阈值≤32,1383 次为真阳性,3 次为假阴性,5 次为不确定),样本的平均灵敏度为 99.7%,而在病毒浓度较低的样本中,检测率较低(2372 次检测中,样本循环阈值>32,2988 次为真阳性,238 次为假阴性,46 次为不确定),平均灵敏度为 92.5%。在预期为阴性的 1645 个结果中,1561 个(94.9%)正确报告为阴性,10 个(0.6%)错误报告为阳性,74 个(4.5%)报告为不确定。值得注意的是,检测的整体性能随时间没有明显变化。与非医疗实验室相比,医疗实验室报告正确结果的几率高 2.94 倍(95%CI 1.75-4.96),与手动检测系统相比,自动检测系统的几率高 4.60 倍(2.91-7.41)。与需要手动干预的系统相比,医疗实验室中的自动检测系统具有最高的灵敏度。
在全面、多次和重复的 EQA 计划中评估的所有 PCR 分析中,高假阴性率为未来的改进提供了明确的方向。一些实验室(例如非医疗实验室或使用非自动化检测系统的实验室)的性能应受到额外审查-例如,要求额外的 EQA 计划进行认证或认可-如果从 EQA 轮次汇总的数据表明敏感性低于其他实验室记录的敏感性。这一策略将确保在如此大规模的检测中,整体流行病学数据是可靠的。尽管性能没有随时间提高,但我们不能排除可能会阻止实验室寻求改进性能的其他方法的特殊情况,例如短缺和供应链减弱。
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