Wang Shunda, You Lei, Dai Menghua, Zhao Yupei
Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ann Transl Med. 2021 Feb;9(3):192. doi: 10.21037/atm-20-5606.
The use of mucins (MUC) as specific biomarkers for various malignancies has recently emerged. MUC1, MUC4, MUC5AC, and MUC16 can be detected at different stages of pancreatic cancer (PC), and can be valuable for indicating the initiation and progression of this disease. However, the diagnostic significance of the mucin family in patients with PC remains disputed. Herein, we assessed the diagnostic accuracy of mucins in PC using a meta-analysis.
We searched the PubMed, Cochrane Library, Institute for Scientific Information (ISI) Web of Science, Embase, and Chinese databases from their date of inception to June 1, 2020 to identify studies assessing the diagnostic performance of mucins in PC. The estimations of diagnostic indicators in selected studies were extracted for further analysis by Meta-DiSc software. Publication bias was assessed using Deeks' funnel plot asymmetry test.
Our meta-analysis included 34 studies. The pooled accuracy indicators of MUC1 in PC including the sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) (with 95% confidence intervals) were 0.84 (0.82-0.86), 0.60 (0.56-0.64), 18.37 (9.18-36.78), 2.62 (1.79-3.86), and 0.22 (0.15-0.33), respectively. The area under the summary receiver operating characteristic (SROC) curve was 0.8875 and the Q index was 0.8181. Quantitative random-effects meta-analysis of MUC4 in PC using the summary (ROC) curve model revealed a pooled sensitivity of 0.86 (95% confidence interval, 0.82-0.89) and specificity of 0.88 (95% confidence interval, 0.85-0.91). In addition, the meta-analysis of MUC5AC in PC diagnosis also showed a high sensitivity and specificity of 0.71 (95% confidence interval, 0.65-0.76) and 0.60 (95% confidence interval, 0.53-0.66), respectively. Regarding MUC16, the area under the summary ROC curve and Q index were 0.9185 and 0.8516, respectively.
In summary, our results suggested a good diagnostic accuracy of several crucial mucins in PC. Mucins may serve as optional indicators in PC examination, and further research is warranted to investigate the role of mucins as potential clinical biomarkers.
近年来，黏蛋白（MUC）作为多种恶性肿瘤的特异性生物标志物开始受到关注。MUC1、MUC4、MUC5AC和MUC16可在胰腺癌（PC）的不同阶段被检测到，对提示该疾病的发生和进展具有重要价值。然而，黏蛋白家族在PC患者中的诊断意义仍存在争议。在此，我们通过荟萃分析评估了黏蛋白在PC中的诊断准确性。
我们检索了PubMed、Cochrane图书馆、科学信息研究所（ISI）的科学网、Embase以及中文数据库，检索时间从建库至2020年6月1日，以确定评估黏蛋白在PC中诊断性能的研究。通过Meta-DiSc软件提取所选研究中诊断指标的估计值，进行进一步分析。采用Deeks漏斗图不对称性检验评估发表偏倚。
我们的荟萃分析纳入了34项研究。PC中MUC1的合并准确性指标，包括敏感性、特异性、诊断比值比（DOR）、阳性似然比（PLR）和阴性似然比（NLR）（95%置信区间）分别为0.84（0.82 - 0.86）、0.60（0.56 - 0.64）、18.37（9.18 - 36.78）、2.62（1.79 - 3.86）和0.22（0.15 - 0.33）。汇总受试者工作特征（SROC）曲线下面积为0.8875，Q指数为0.8181。使用汇总（ROC）曲线模型对PC中MUC4进行定量随机效应荟萃分析，结果显示合并敏感性为0.86（95%置信区间，0.82 - 0.89），特异性为0.88（95%置信区间，0.85 - 0.91）。此外，PC诊断中MUC5AC的荟萃分析也显示出较高的敏感性和特异性，分别为0.71（95%置信区间，0.65 - 0.76）和0.60（95%置信区间，0.53 - 0.66）。对于MUC16而言，汇总ROC曲线下面积和Q指数分别为0.9185和0.8516。
总之，我们的结果表明几种关键黏蛋白在PC中具有良好的诊断准确性。黏蛋白可作为PC检查中的可选指标，有必要进一步研究黏蛋白作为潜在临床生物标志物的作用。
