Korean J Intern Med.  2016 Sep;31(5):860-871. 10.3904/kjim.2015.093.

Endoscopic submucosal dissection of gastric subepithelial tumors: a systematic review and meta-analysis

Affiliations
  • 1Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, Korea. baikgh@hallym.or.kr
  • 2Jeonju University College of Education, Jeonju, Korea.

Abstract

BACKGROUND/AIMS
To evaluate the therapeutic outcomes of the endoscopic submucosal dissection (ESD) technique for the treatment of gastric subepithelial tumors (SETs).
METHODS
A systematic literature review was conducted using the core databases. Data on the complete resection rates and the procedure-related perforation rates were extracted and analyzed. A random effects model was then applied for this meta-analysis.
RESULTS
In all, 288 patients with 290 SETs were enrolled from nine studies (44 SETs originated from the submucosal layer; 246 SETs originated from the muscularis propria layer). The mean diameter of the lesions ranged from 17.99 to 38 mm. Overall, the pooled complete resection rate was estimated to be 86.2% (95% confidence interval [CI], 78.9 to 91.3). If the analysis was limited to the lesions that originated from the submucosal layer, the pooled complete resection rate was 91.4% (95% CI, 77.9 to 97). If the analysis was limited to the lesions that originated from the muscularis propria, the pooled complete resection rate was 84.4% (95% CI, 78.7 to 88.8). The pooled procedure-related gastric perforation rate was 13% (95% CI, 9.4 to 17.6). Sensitivity analyses showed consistent results. Finally, publication bias was not detected.
CONCLUSIONS
ESD, including endoscopic muscularis dissection, is a technically feasible procedure for the treatment of SETs. However, selection bias is suspected from the enrolled studies. For the development of a proper indication of ESD for SETs, further studies are needed.

Keyword

Endoscopic submucosal dissection; Gastrointestinal stromal tumors; Subepithelial tumors

MeSH Terms

Gastrointestinal Stromal Tumors
Humans
Publication Bias
Selection Bias
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