18 November 2015 : Meta-Analysis
Diagnostic Accuracy of Serum CA19-9 in Patients with Cholangiocarcinoma: A Systematic Review and Meta-AnalysisBin LiangB, Liansheng ZhongBC, Qun HeCF, Shaocheng WangC, Zhongcheng PanC, Tianjiao WangD, Yujie ZhaoA
Med Sci Monit 2015; 21:3555-3563
BACKGROUND: Cholangiocarcinoma (CCA) is a relatively rare cancer worldwide; however, its incidence is extremely high in Asia. Numerous studies reported that serum carbohydrate antigen 19-9 (CA19-9) plays a role in the diagnosis of CCA patients. However, published data are inconclusive. The aim of this meta-analysis was to provide a systematic review of the diagnostic performance of CA19-9 for CCA.
MATERIAL AND METHODS: We searched the public databases including PubMed, Web of Science, Embase, Chinese National Knowledge Infrastructure (CNKI), and WANFANG databases for articles evaluating the diagnostic accuracy of serum CA19-9 to predict CCA. The diagnostic sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic curve (SROC) were pooled by Meta-DiSc 1.4 software.
RESULTS: A total of 31 articles met the inclusion criteria, including 1,264 patients and 2,039 controls. The pooled SEN, SPE, PLR, NLR, and DOR were 0.72 (95% CI: 0.70–0.75), 0.84 (95% CI: 0.82–0.85), 4.93 (95% CI, 3.67–6.64), 0.35 (95%CI, 0.30–0.41), and 15.10 (95% CI, 10.70–21.32), respectively. The area under SROC curve was 0.8300. The subgroup analyses based on different control type, geographical location, and sample size revealed that the diagnostic accuracy of CA19-9 tends to be same in different control type, but showed low sensitivity in European patients and small size group.
CONCLUSIONS: Serum CA19-9 is a useful non-invasive biomarker for CCA detection and may become a clinically useful tool to identify high-risk patients.
Keywords: Biomarkers, Tumor - blood, Bile Duct Neoplasms - diagnosis, CA-19-9 Antigen - blood, Cholangiocarcinoma - diagnosis, Odds Ratio, Publication Bias, ROC Curve, Sensitivity and Specificity
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