Research Papers:
Clinically relevant circulating microRNA profiling studies in pancreatic cancer using meta-analysis
PDF | HTML | Supplementary Files | How to cite
Metrics: PDF 2524 views | HTML 2502 views | ?
Abstract
Zenglin Pei1, Song-Mei Liu2, Jing-Tao Huang2, Xuan Zhang1, Dong Yan3, Qianlin Xia1, Chunxia Ji1, Weiping Chen4, Xiaoyan Zhang1, Jianqing Xu1, Jin Wang1
1Scientific Research Center, Shanghai Public Health Clinical Center, Fudan University, Jinshan District, Shanghai 201508, P.R. China
2Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China
3Department of Medical Oncology, Beijing Chaoyang Hospital affiliated to Capital Medical University, Beijing, China
4Genomics Core, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
Correspondence to:
Jin Wang, email: [email protected]
Keywords: pancreatic cancer, meta-analysis, diagnostics, multiple miRNA, SROC
Received: October 24, 2016 Accepted: January 25, 2017 Published: February 07, 2017
ABSTRACT
Background: Pancreatic cancer (PaCa) is the most lethal gastrointestinal (GI) tumor. Although many studies on differentially expressed miRNAs as candidate biomarkers of pancreatic cancer have been published, reliability of these findings generated from investigations performed in single laboratory settings remain unclear.
Results: There were 29 articles with a total of 2,225 patients and 1,618 controls included in this meta-analysis. The pooled sensitivity was 82% (95% CI, 79–85%); the specificity was 85% (95% CI, 79–89%); and area under the curve (AUC) was 0.89 (95% CI, 0.86–0.92). Subgroup analyses indicated that there were significant divergences between Caucasian and Asian subgroups for circulating miRNA analysis.
Materials And Methods: To comprehensively investigate the potential utility of miRNAs as biomarkers of the disease, we searched publications diagnosing PaCa using miRNAs from PubMed, Medline, Embase, Google Scholar and Chinese National Knowledge Infrastructure (CNKI) databases. The sensitivity (SEN), specificity (SPE), and summary receiver operating characteristic (SROC) curve were used to examine the overall test performance, and heterogeneity was analyzed with the I2 test.
Conclusions: Our analysis demonstrated that multiple miRNAs (SEN: 85%; SPE: 89%; AUC: 0.93) were more accurate for diagnosing PaCa than a single miRNA (SEN: 78%; SPE: 79%; AUC: 0.84), and future studies are still needed to confirm the diagnostic value of these pooled miRNAs for PaCa.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 License.
PII: 15148