EUS elastography for the differentiation of benign and malignant lymph nodes: a meta-analysis

Gastrointest Endosc. 2011 Nov;74(5):1001-9; quiz 1115.e1-4. doi: 10.1016/j.gie.2011.07.026.

Abstract

Background: EUS elastography is a new technique for differentiating benign and malignant lymph nodes (LNs) by describing the mechanical property of the target tissue.

Objective: To assess the accuracy of EUS elastography by pooling data of existing trials.

Design: Seven studies involving 368 patients with 431 LNs were included. Meta-analysis was performed. Pooling was conducted in a fixed-effect model or a random-effect model.

Patients: This study involved 368 patients.

Intervention: EUS elastography.

Main outcome measurements: Meta-analysis and meta-regression analysis.

Results: The pooled sensitivity of EUS elastography for the differential diagnosis of benign and malignant LNs was 88% (95% confidence interval [CI] 0.83-0.92), and the specificity was 85% (95% CI, 0.79-0.89). The area under the curve under summary receiver operating characteristic (SROC) was 0.9456. The pooled positive likelihood ratio was 5.68 (95% CI, 2.86-11.28), and the negative likelihood ratio was 0.15 (95% CI, 0.10-0.21). The subgroup analysis by excluding the outliers provided a sensitivity of 85% (95% CI, 0.79-0.90) and a specificity of 91% (95% CI, 0.85-0.95) for the differential diagnosis of benign and malignant LNs. The area under the curve under SROC was 0.9421.

Limitations: A small number of studies met inclusion criteria.

Conclusion: EUS elastography is a promising, noninvasive method for differential diagnosis of malignant LNs and may prove to be a valuable supplemental method to EUS-guided FNA.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Area Under Curve
  • Diagnosis, Differential
  • Elasticity Imaging Techniques*
  • Endosonography*
  • Female
  • Humans
  • Lymph Nodes / diagnostic imaging*
  • Lymph Nodes / pathology*
  • Lymphatic Metastasis
  • Male
  • Middle Aged
  • ROC Curve
  • Regression Analysis