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Comparative Performance of Endoscopic Ultrasound-based Techniques in Patients with Pancreatic Cystic Lesions: A Network Meta-analysis

Am J Gastroenterol. 2022 Dec 23. doi: 10.14309/ajg.0000000000002088. Online ahead of print.

ABSTRACT

BACKGROUND: Evidence on the comparative diagnostic performance of endoscopic ultrasound (EUS)-based techniques for pancreatic cyst lesions (PCLs) is limited. This network meta-analysis comprehensively compared EUS-based techniques for PCLs diagnosis.

METHODS: A comprehensive literature search was performed for all comparative studies assessing the accuracy of 2 or more modalities for PCLs diagnosis. The primary outcome was the diagnostic efficacy for mucinous PCLs. Secondary outcomes were the diagnostic efficacy for malignant PCLs, diagnostic success rate, and adverse event rate. A network meta-analysis was conducted using the ANOVA model to assess the diagnostic accuracy of each index.

RESULTS: Forty studies comprising 3641 patients were identified. The network ranking of the superiority index for EUS-guided needle-based confocal laser endomicroscopy (EUS-nCLE) and EUS-guided through-the-needle biopsy (EUS-TTNB) were significantly higher than other techniques for differentiating mucinous PCLs; besides, EUS-TTNB was also the optimal technique in identifying malignant PCLs. The evidence was inadequate for EUS-nCLE diagnosing malignant PCLs and CH-EUS for diagnosing both mucinous and malignant PCLs. Glucose showed a high sensitivity but low specificity, and molecular analysis (KRAS, GNAS and KRAS+GNAS mutations) showed a high specificity but low sensitivity for diagnosing mucinous PCLs. Satisfactory results were not obtained during the evaluation of the efficiency of pancreatic cyst fluid (PCF) biomarkers in detecting malignant PCLs.

CONCLUSIONS: For centers with relevant expertise and facilities, EUS-TTNB and EUS-nCLE were better choices for the diagnosis of PCLs. Further studies are urgently required for further improving PCF biomarkers and validating diagnostic performance of the index techniques.

PMID:36563321 | DOI:10.14309/ajg.0000000000002088

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