Differentiating Latent Tuberculosis from Active Tuberculosis Through Activation Phenotypes and Chemokine Markers HLA-DR, CD38, MCP-1, and RANTES: A Systematic Review and Meta-Analysis.

IF 3.4 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Biomarker Insights Pub Date : 2025-01-08 eCollection Date: 2025-01-01 DOI:10.1177/11772719241312776
Chaimae Kadi, Narjisse Ahmadi, Anass Houdou, Imad El Badisy, Oumnia Bouaddi, Zakaria Mennane, Nouhaila Najimi, Maryam Benlamari, Saber Boutayeb, Mohamed Khalis, Noureddine El Mtili, Fouad Seghrouchni
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引用次数: 0

Abstract

Background: Latent TB infection (LTBI) affects one fourth of the global population. Currently, there is an absence of an optimal strategy for distinguishing between active tuberculosis (aTB) and LTBI. While some researchers have explored cytokines other than interferon-gamma (IFN-γ) as biomarkers, results have shown significant variability in their ability to differentiate between these conditions. This meta-analysis aims to evaluate the performance of activation phenotype and chemokine markers in distinguishing between aTB and LTBI.

Objectives: To assess the diagnostic accuracy of specific biomarkers (HLA-DR+ IFNγ+, CD38+ IFNγ+, MCP-1, and RANTES) in differentiating aTB from LTBI.

Design: This study was conducted in accordance with the PRISMA guidelines for systematic reviews and meta-analyses of diagnostic studies.

Data sources and methods: We conducted a comprehensive search of PubMed, Scopus, Sciences Direct, and Web of Science for primary studies published in English up to 2023. Studies were included if they reported sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) for the biomarkers in question. We calculated pooled diagnostic sensitivity, specificity, DOR, and AUC, and used the summary receiver operating characteristic curve (SROC) to summarize the diagnostic performance of each biomarker.

Results: Sixteen studies involving 1696 participants were included in the analysis. Among them, 925 individuals were diagnosed with aTB, while 771 were classified as having LTBI. The specificity, sensitivity, DOR, and AUC for CD38+ IFNγ+, HLA-DR+ IFNγ+, RANTES, and MCP-1 were (0.97 [95% CI: 0.72-1.00], 0.90 [95% CI: 0.75-0.96], 291.863, and 0.9432), (0.90 [95% CI: 0.70-0.97], 0.83 [95% CI: 0.63-0.94], 41.819, and 0.8598), (0.68 [95% CI: 0.55-0.79], 0.72 [95% CI: 0.56-0.84], 5.733, and 0.7979), and (0.63 [95% CI: 0.54-0.72], 0.63 [95% CI: 0.50-0.75], 2.892, and 0.7290) respectively.

Conclusion: The findings indicate that CD38+ IFNγ+ and HLA-DR+ IFNγ+ demonstrated the highest diagnostic accuracy. Additional prospective research is necessary to identify the optimal combination of biomarkers to enhance diagnostic accuracy in clinical settings.

Registration: This review has been registered on PROSPERO: (CRD42023472091). Available from: https://www.crd.york.ac.uk/prospero/#recordDetails.

通过激活表型和趋化因子标记HLA-DR、CD38、MCP-1和RANTES区分潜伏性结核病和活动性结核病:一项系统综述和荟萃分析
背景:潜伏性结核感染(LTBI)影响着全球四分之一的人口。目前,尚无区分活动性肺结核(aTB)和LTBI的最佳策略。虽然一些研究人员已经探索了干扰素-γ (IFN-γ)以外的细胞因子作为生物标志物,但结果表明,它们区分这些疾病的能力存在显著差异。本荟萃分析旨在评估激活表型和趋化因子标记在区分aTB和LTBI中的表现。目的:评估特异性生物标志物(HLA-DR+ IFNγ+、CD38+ IFNγ+、MCP-1和RANTES)在鉴别aTB和LTBI中的诊断准确性。设计:本研究按照PRISMA诊断研究系统评价和荟萃分析指南进行。数据来源和方法:我们对PubMed、Scopus、Sciences Direct和Web of Science进行了全面的检索,以获取截至2023年的英文发表的主要研究。如果研究报告了相关生物标志物的敏感性、特异性、诊断优势比(DOR)和曲线下面积(AUC),则纳入研究。我们计算了诊断敏感性、特异性、DOR和AUC,并使用总结受试者工作特征曲线(SROC)来总结每个生物标志物的诊断性能。结果:16项研究共纳入1696名受试者。其中,925人被诊断为aTB, 771人被归类为LTBI。CD38+ IFNγ+、HLA-DR+ IFNγ+、RANTES和MCP-1的特异性、敏感性、DOR和AUC分别为(0.97 [95% CI: 0.72-1.00]、0.90 [95% CI: 0.75-0.96]、291.863和0.9432)、(0.90 [95% CI: 0.70-0.97]、0.83 [95% CI: 0.63-0.94]、41.819和0.8598)、(0.68 [95% CI: 0.55-0.79]、0.72 [95% CI: 0.56-0.84]、5.733和0.7979)和(0.63 [95% CI: 0.54-0.72]、0.63 [95% CI: 0.50-0.75]、2.892和0.7290)。结论:CD38+ IFNγ+和HLA-DR+ IFNγ+具有最高的诊断准确性。需要进一步的前瞻性研究来确定生物标志物的最佳组合,以提高临床诊断的准确性。注册:本综述已在PROSPERO注册:(CRD42023472091)。可从:https://www.crd.york.ac.uk/prospero/#recordDetails。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biomarker Insights
Biomarker Insights MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
6.00
自引率
0.00%
发文量
26
审稿时长
8 weeks
期刊介绍: An open access, peer reviewed electronic journal that covers all aspects of biomarker research and clinical applications.
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