菲律宾FDA授权的新冠肺炎抗体检测的诊断准确性:系统评价和Meta-Analysis

Carmel Reina R. Chua, Esther Delle E. De los Santos, Karla Veronica H. Escasa, Richmond Louis G. Estolas, Junnealyn Feliciano, Sabrina Audrey E. Ortega, Carlo Ledesma, Jan Ebrian D. Leonin, S. Tesalona
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引用次数: 3

摘要

简介:冠状病毒病(COVID-19)是由严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)引起的一种高度传染性疾病,已在世界各地感染了许多人。减少其传播的最佳方法之一是通过早期检测和诊断。目前,各种血清学检测被用作检测对严重急性呼吸系统综合征冠状病毒2型反应的抗体的监测工具。本研究的目的是评估菲律宾食品药品监督管理局(FDA)授权的新冠肺炎抗体测试的诊断准确性和性能,这些测试使用酶联免疫吸附剂测定(ELISA)、化学发光免疫测定(CLIA)和侧流免疫测定(LFIA)。方法:使用可信的医学期刊搜索引擎收集与三种抗体测试的诊断准确性相关的完整已发表期刊文章。使用QUADAS-2评估期刊的质量,以确定偏倚的风险,并评估诊断准确性研究的适用性判断。根据LFIA、ELISA和CLIA在检测各种抗体方面的特异性和敏感性,使用森林图来总结它们的性能。还使用双变量随机效应模型及其对数似然性、相应的平方检验统计量和受试者操作特征曲线下面积进行了敏感性和特异性汇总,以了解数据的潜在异质性并评估新冠肺炎抗体检测的诊断准确性。结果:采用双变量随机效应模型和sROC曲线下面积评价新冠肺炎抗体检测的诊断准确性。基于CLIA、ELISA和LFIA检测IgG的合并灵敏度分别为81.7%、58.7%和74.3%,总体为72.0%。对于IgM检测,LFIA的合并灵敏度为69.6%,高于CLIA的61.0%。总体而言,合并灵敏度为68.5%。在IgA检测中,仅包括基于ELISA的检测,合并灵敏度达84.8%。最后,基于ELISA和LFIA的联合抗体的合并敏感性分别为89.0%和81.6%,总体为82.5%。另一方面,除ELISA IgA外的所有测试都显示出高合并特异性,范围为94.0%至100.0%,基于sROC下的计算面积,发现组合抗体几乎是完美的,其值分别为0.973、0.953和0.966。结论:在这项系统综述和荟萃分析中,发现新冠肺炎抗体检测诊断准确性的现有证据具有高偏倚风险、敏感性异质性的一致性和高特异性同质性的一致性,但使用ELISA检测IgA除外。双变量随机效应模型显示,在95%置信区间下,CLIA、ELISA和LFIA在检测IgG、IgM和联合抗体方面的敏感性没有显著差异。尽管如此,CLIA、ELISA和LFIA在检测IgG、IgM和联合抗体方面被发现具有极好的诊断准确性,如其AUC值所反映的。Doi:10.28991/SciMedJ-2021-0304-1全文:PDF
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Diagnostic Accuracy of COVID-19 Antibody Tests Authorized by FDA Philippines: A Systematic Review and Meta-Analysis
Introduction: Coronavirus Disease (COVID-19) is a highly infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) which has infected many people all over the world. One of the best ways to lessen its spread is through early detection and diagnosis. Various serological tests are now being used as a surveillance tool in the detection of antibodies as a response to SARS-CoV-2. The aim of this study is to evaluate the diagnostic accuracy and performance of the available COVID-19 antibody tests authorized by the Food and Drug Administration (FDA) Philippines that make use of Enzyme-Linked Immunosorbent Assay (ELISA), Chemiluminescence Immunoassay (CLIA) and Lateral Flow Immunoassay (LFIA). Method: Complete published journal articles relevant to the diagnostic accuracy of the three antibody tests were collected using trusted medical journal search engines. The quality of journals was assessed using QUADAS-2 to determine the risk of bias and assess the applicability judgments of diagnostic accuracy studies. Forest plots were used to summarize the performance of LFIA, ELISA and CLIA according to their specificity and sensitivity in detecting various antibodies. Pooled sensitivity and specificity were also done using bivariate random-effects models with its log-likelihood, a corresponding chi-square test statistic, and area under the summary Receiver-Operating Characteristic curve to see the potential heterogeneity in the data and to assess the diagnostic accuracy of the COVID-19 antibody tests. Results: Bivariate random-effects model and areas under the sROC curve were used to evaluate the diagnostic accuracy of COVID-19 antibody tests. The pooled sensitivity in detecting IgG based on CLIA, ELISA, and LFIA were 81.7%, 58.7%, and 74.3% respectively, with an overall of 72.0%. For IgM detection, LFIA has a higher pooled sensitivity of 69.6% than CLIA with 61.0%. Overall, the pooled sensitivity is 68.5%. In IgA detection, only ELISA based test was included with a pooled sensitivity of 84.8%. Lastly, pooled sensitivities for combined antibodies based on ELISA and LFIA were 89.0% and 81.6% respectively, with an overall of 82.5%. On the other hand, all tests excluding ELISA-IgA displayed high pooled specificities with a range of 94.0% to 100.0%. Diagnostic accuracies of the test in detecting IgG, IgM, and combined antibodies were found out to be almost perfect based on the computed area under the sROC with values of 0.973, 0.953, and 0.966, respectively. Conclusion: In this systematic review and meta-analysis, existing evidence on the diagnostic accuracy of antibody tests for COVID-19 were found to be characterized by high risks of bias, consistency in the heterogeneity of sensitivities, and consistency in the homogeneity of high specificities except in IgA detection using ELISA. The bivariate random-effects models showed that there are no significant differences in terms of sensitivity among CLIA, ELISA and LFIA in detecting IgG, IgM, and combined antibodies at a 95% confidence interval. Nonetheless, CLIA, ELISA and LFIA were found to have excellent diagnostic accuracies in the detection of IgG, IgM and combined antibodies as reflected by their AUC values. Doi: 10.28991/SciMedJ-2021-0304-1 Full Text: PDF
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