Department of Clinical Laboratory, Linyi People's Hospital, Shandong University, Linyi, Shandong Province, China.
Department of Immunology, School of Basic Medical Sciences, Shandong University, Jinan, Shandong Province, China.
Int J Biol Markers. 2020 Jun;35(2):40-48. doi: 10.1177/1724600820926685. Epub 2020 May 28.
Owing to inconsistency between reports, a meta-analysis was designed to appraise the clinical implications of long non-coding RNAs (lncRNAs) in urine and blood for the diagnosis of bladder cancer.
Studies that met the criteria were acquired by bibliographic retrieval through PubMed, Embase, and the Cochrane Library. The pooled diagnostic performance was evaluated by calculating the area under the summary receiver operator characteristic (SROC) curve. The potential sources of heterogeneity were approached through meta-regression and subgroup analyses. All statistical analyses and plots were performed by RevMan 5.3, Meta-DiSc 1.4, and STATA 12.0.
A total of 43 studies from 15 articles consisting of 3370 bladder cancer patients and 3212 controls were incorporated in our meta-analysis. lncRNAs in urine and blood performed relatively well in diagnosing bladder cancer, with a pooled sensitivity of 0.78, a specificity of 0.79, and an area under the SROC curve (AUC) of 0.86. H19 displayed the best diagnostic accuracy with a pooled AUC of 0.90, followed by UCA1 and MALAT1. The heterogeneity among studies was partly conducted by sample size, lncRNA existence form (cell-free or intracellular lncRNA), lncRNA origin (exosome- or non-exosome-based lncRNA), lncRNA profiling (single- or multiple-lncRNA), specimen types, and ethnicity.
lncRNAs in urine and blood may serve as noninvasive diagnostic biomarkers with great promise for bladder cancer, while their clinical values need to be examined through further synthetic forward-looking studies.
由于报告之间存在不一致，因此设计了一项荟萃分析，以评估尿液和血液中的长链非编码 RNA（lncRNA）在膀胱癌诊断中的临床意义。
通过文献检索获取符合标准的研究，检索数据库包括 PubMed、Embase 和 Cochrane Library。通过计算汇总受试者工作特征（SROC）曲线下面积来评估汇总诊断性能。通过荟萃回归和亚组分析探讨潜在的异质性来源。所有统计分析和绘图均由 RevMan 5.3、Meta-DiSc 1.4 和 STATA 12.0 完成。
共有来自 15 篇文章的 43 项研究纳入了我们的荟萃分析，这些研究共纳入了 3370 例膀胱癌患者和 3212 例对照。尿液和血液中的 lncRNA 对膀胱癌的诊断具有较好的性能，其合并敏感度为 0.78，特异度为 0.79，SROC 曲线下面积（AUC）为 0.86。H19 的诊断准确性最高，合并 AUC 为 0.90，其次是 UCA1 和 MALAT1。研究间的异质性部分通过样本量、lncRNA 存在形式（游离或细胞内 lncRNA）、lncRNA 来源（外泌体或非外泌体 lncRNA）、lncRNA 分析（单 lncRNA 或多 lncRNA）、标本类型和种族得到解释。
尿液和血液中的 lncRNA 可能成为膀胱癌有前途的非侵入性诊断生物标志物，但它们的临床价值需要通过进一步的综合前瞻性研究来检验。
