Can EGFR mutations in plasma or serum be predictive markers of non-small-cell lung cancer? A meta-analysis.

Abstract

BACKGROUND:

The detection of epidermal growth factor receptor (EGFR) mutations in plasma or serum has previously been reported to be feasible for non-small-cell lung cancer (NSCLC). However, not all results indicate a consistency between EGFR mutation status in the plasma or serum and that in tissues.

METHODS:

A meta-analysis was performed to evaluate the overall accuracy of EGFR mutation detection in plasma or serum. Publications up to December 2014 were searched for using the PubMed, Embase and Web of Science databases. Sensitivity, specificity and other accuracy measures were pooled using the bivariate mixed-effects regression model.

RESULTS:

Twenty-six studies were included in this meta-analysis. The pooled specificity, sensitivity, positive and negative likelihood ratios, and diagnostic odds ratios were 0.97 (95% confidence interval (CI): 0.93-0.99), 0.65 (95% CI: 0.54-0.74), 24.9 (95% CI: 9.2-67.2), 0.36 (95% CI: 0.27-0.48), and 69 (95% CI: 24-202), respectively. The summary receiver operating characteristic curve was 0.89 (95% CI: 0.86-0.91).

CONCLUSIONS:

The detection of EGFR mutations in plasma or serum is a noninvasive method to confirm EGFR mutation status in patients with NSCLC. However, more work is necessary to identify which method can raise the sensitivity of EGFR mutation detection.

• Authors: Ying Wu, Hongbing Liu, Xuefei Shi, Yong Song
• Journal: Lung cancer (Amsterdam, Netherlands) (Lung Cancer) Vol. 88 Issue 3 Pg. 246-53 (Jun 2015) ISSN: 1872-8332 [Electronic] Ireland
• PMID: 25837799 (Publication Type: Journal Article, Meta-Analysis, Research Support, Non-U.S. Gov't)
• Copyright: Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Chemical References

• Biomarkers, Tumor
• ErbB Receptors

Topics

• Biomarkers, Tumor
• Carcinoma, Non-Small-Cell Lung (blood, diagnosis, genetics)
• ErbB Receptors (blood, genetics)
• Humans
• Lung Neoplasms (blood, diagnosis, genetics)
• Mutation
• Prognosis
• Publication Bias
• ROC Curve