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Meta-Analysis
. 2014:2014:573783.
doi: 10.1155/2014/573783. Epub 2014 Jul 16.

K-ras mutational status in cytohistological tissue as a molecular marker for the diagnosis of pancreatic cancer: a systematic review and meta-analysis

Affiliations
Meta-Analysis

K-ras mutational status in cytohistological tissue as a molecular marker for the diagnosis of pancreatic cancer: a systematic review and meta-analysis

Jing Yang et al. Dis Markers. 2014.

Abstract

Background: More clinically meaningful diagnostic tests are needed in pancreatic cancer (PC). K-ras mutations are the most frequently acquired genetic alteration.

Methods: Original research articles involving the diagnostic accuracy of K-ras mutation detection in PC were selected. Data were presented as forest plots and summary receiver operating characteristic (SROC) curve analysis was used to summarize the overall test performance.

Results: We assessed 19 studies from 16 published articles. The reports were divided into three groups according to the process used to obtain the test material. The summary estimates for detecting K-ras status using an invasive method (fine needle aspiration (FNA), endoscopic retrograde cholangiopancreatography (ERCP), or surgery) were better than cytology: the pooled sensitivity was 77% (95% confidence interval (CI): 74-80%) versus 54% (95% CI: 47-61%); specificity was 88% (95% CI: 85-91%) versus 91% (95% CI: 83-96%); and diagnostic odds ratio (DOR) was 20.26 (11.40-36.03) versus 7.52 (95% CI: 2.80-20.18), respectively. When two procedures were combined, the diagnostic accuracy was markedly improved.

Conclusions: The analysis of K-ras mutations in pancreatic tissue has a promising diagnostic significance in PC. Further valuable studies are needed.

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Figures

Figure 1
Figure 1
Flow diagram showing the process of article selection for the meta-analysis.
Figure 2
Figure 2
Summary of the methodological quality of included studies on the basis of review authors' judgments on the four domains of the QUADAS-2 checklist for each study.
Figure 3
Figure 3
Forest plot of the meta-analysis of each index.
Figure 4
Figure 4
Summary receiver-operating characteristic curves for detecting K-ras mutation using FNA/ERCP/surgical methods from the hierarchical summary receiver operating characteristic model.
Figure 5
Figure 5
Forest plot of the meta-analysis of seven studies which included the diagnostic value of cytology for detecting PC.
Figure 6
Figure 6
Deeks funnel plot output using the “metafunnel” command for Stata (version 12.0).

References

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