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2
Validation of Calprotectin As a Novel Biomarker For The Diagnosis of Pleural Effusion: a Multicentre Trial.血清钙卫蛋白对胸腔积液诊断的新型生物标志物的验证:一项多中心试验。
Sci Rep. 2020 Mar 30;10(1):5679. doi: 10.1038/s41598-020-62388-y.
3
The value of apolipoprotein E in distinguishing benign and malignant unilateral pleural effusions.载脂蛋白E在鉴别单侧良恶性胸腔积液中的价值。
Medicine (Baltimore). 2020 Mar;99(10):e19320. doi: 10.1097/MD.0000000000019320.
4
Suggestions for designing studies investigating diagnostic accuracy of biomarkers.关于设计研究以调查生物标志物诊断准确性的建议。
Ann Transl Med. 2019 Dec;7(23):788. doi: 10.21037/atm.2019.11.133.
5
Diagnostic accuracy of cancer ratio for malignant pleural effusion: a systematic review and meta-analysis.恶性胸腔积液癌症比例的诊断准确性:一项系统评价和荟萃分析。
Ann Transl Med. 2019 Oct;7(20):554. doi: 10.21037/atm.2019.09.85.
6
MicroRNAs - novel biomarkers for malignant pleural effusions.微小RNA——恶性胸腔积液的新型生物标志物
Contemp Oncol (Pozn). 2019;23(3):133-140. doi: 10.5114/wo.2019.89241. Epub 2019 Oct 30.
7
Clinical value of combined detection of reactive oxygen species modulator 1 and adenosine deaminase in pleural effusion in the identification of NSCLC associated malignant pleural effusion.活性氧调节因子 1 与腺苷脱氨酶联合检测在鉴别 NSCLC 相关恶性胸腔积液中的临床价值。
J Clin Lab Anal. 2020 Mar;34(3):e23091. doi: 10.1002/jcla.23091. Epub 2019 Nov 10.
8
Diagnostic value of human epididymis protein 4 in malignant pleural effusion in lung cancer.人附睾蛋白 4 在肺癌恶性胸腔积液中的诊断价值。
Cancer Biomark. 2019;26(4):523-528. doi: 10.3233/CBM-190840.
9
Identifying tuberculous pleural effusion using artificial intelligence machine learning algorithms.利用人工智能机器学习算法识别结核性胸腔积液。
Respir Res. 2019 Oct 16;20(1):220. doi: 10.1186/s12931-019-1197-5.
10
The diagnostic value of pleural fluid homocysteine in malignant pleural effusion.胸腔积液同型半胱氨酸对恶性胸腔积液的诊断价值。
PLoS One. 2019 Sep 24;14(9):e0222616. doi: 10.1371/journal.pone.0222616. eCollection 2019.

恶性胸腔积液诊断中的胸膜生物标志物:一项叙述性综述

Pleural biomarkers in diagnostics of malignant pleural effusion: a narrative review.

作者信息

Zhang Man, Yan Li, Lippi Giuseppe, Hu Zhi-De

机构信息

Department of Thoracic Surgery, the Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China.

Department of Respiratory and Critical Care Medicine, the Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China.

出版信息

Transl Lung Cancer Res. 2021 Mar;10(3):1557-1570. doi: 10.21037/tlcr-20-1111.

DOI:10.21037/tlcr-20-1111
PMID:33889529
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8044497/
Abstract

Although cytology and pleural biopsy of pleural effusion (PE) are the gold standards for diagnosing malignant pleural effusion (MPE), these tools' diagnostic accuracy is plagued by some limitations such as low sensitivity, considerable inter-observer variation and invasiveness. The assessment of PE biomarkers may hence be seen as an objective and non-invasive diagnostic alternative in MPE diagnostics. In this review, we summarize the characteristics and diagnostic accuracy of available PE biomarkers, including carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), carbohydrate antigens 125 (CA125), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 15-3 (CA15-3), a fragment of cytokeratin 19 (CYFRA 21-1), chitinase-like proteins (CLPs), vascular endothelial growth factor (VEGF) and its soluble receptor, endostatin, calprotectin, cancer ratio, homocysteine, apolipoprotein E (Apo-E), B7 family members, matrix metalloproteinase (MMPs) and tissue-specific inhibitors of metalloproteinases (TIMPs), reactive oxygen species modulator 1 (Romo1), tumor-associated macrophages (TAMs) and monocytes, epigenetic markers (e.g., cell-free microRNA and mRNA). We summarized the evidence from systematic review and meta-analysis for traditional tumor markers' diagnostic accuracy. According to the currently available evidence, we conclude that the traditional tumor markers have high specificity (around 0.90) but low sensitivity (around 0.50). The diagnostic accuracy of novel tumor markers needs to be validated by further studies. None of these tumor biomarkers would have sufficient diagnostic accuracy to confirm or exclude MPE when used alone. A multi-biomarker strategy, also encompassing the use of artificial intelligence algorithms, may be a valuable perspective for improving the diagnostic accuracy of MPE.

摘要

尽管胸腔积液(PE)的细胞学检查和胸膜活检是诊断恶性胸腔积液(MPE)的金标准,但这些方法的诊断准确性受到一些限制,如敏感性低、观察者间差异大以及具有侵入性。因此,评估PE生物标志物可能被视为MPE诊断中一种客观且非侵入性的诊断替代方法。在本综述中,我们总结了现有PE生物标志物的特征和诊断准确性,包括癌胚抗原(CEA)、神经元特异性烯醇化酶(NSE)、糖类抗原125(CA125)、糖类抗原19-9(CA19-9)、糖类抗原15-3(CA15-3)、细胞角蛋白19片段(CYFRA 21-1)、几丁质酶样蛋白(CLPs)、血管内皮生长因子(VEGF)及其可溶性受体内皮抑素、钙卫蛋白、癌症比例、同型半胱氨酸、载脂蛋白E(Apo-E)、B7家族成员、基质金属蛋白酶(MMPs)和金属蛋白酶组织特异性抑制剂(TIMPs)、活性氧调节剂1(Romo1)、肿瘤相关巨噬细胞(TAMs)和单核细胞、表观遗传标志物(如游离微小RNA和信使核糖核酸)。我们总结了系统评价和荟萃分析中关于传统肿瘤标志物诊断准确性的证据。根据目前可得的证据,我们得出结论,传统肿瘤标志物具有较高的特异性(约0.90)但敏感性较低(约0.50)。新型肿瘤标志物的诊断准确性需要进一步研究验证。这些肿瘤生物标志物单独使用时,均没有足够的诊断准确性来确诊或排除MPE。一种多生物标志物策略,包括使用人工智能算法,可能是提高MPE诊断准确性的一个有价值的方向。