Comparison of Biliary Drainage Techniques for Malignant Biliary Obstruction: A Systematic Review and Network Meta-analysis

J Clin Gastroenterol. 2022 Jan 1;56(1):88-97. doi: 10.1097/MCG.0000000000001512.

Abstract

Background and aims: Endoscopic retrograde cholangiopancreatography (ERCP), percutaneous transhepatic biliary drainage, and endoscopic ultrasound (EUS)-guided biliary drainage are all established techniques for drainage of malignant biliary obstruction. This network meta-analysis (NMA) was aimed at comparing all 3 modalities to each other.

Materials and methods: Multiple databases were searched from inception to October 2019 to identify relevant studies. All the patients were eligible to receive any one of the 3 interventions. Data extraction and risk of bias assessment was performed using standardized tools. Outcomes of interest were technical success, clinical success, adverse events, and reintervention. Direct meta-analyses were performed using the random-effects model. NMA was conducted using a multivariate, consistency model with random-effects meta-regression. The GRADE approach was followed to rate the certainty of evidence.

Results: The final analysis included 17 studies with 1566 patients. Direct meta-analysis suggested that EUS-guided biliary drainage had a lower reintervention rate than ERCP. NMA did not show statistically significant differences to favor any one intervention with certainty across all the outcomes. The overall certainty of evidence was found to be low to very low for all the outcomes.

Conclusions: The available evidence did not favor any intervention for drainage of malignant biliary obstruction across all the outcomes assessed. ERCP with or without EUS should be considered first to allow simultaneous tissue acquisition and biliary drainage.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Cholangiopancreatography, Endoscopic Retrograde / adverse effects
  • Cholestasis* / etiology
  • Cholestasis* / therapy
  • Drainage
  • Endosonography
  • Humans
  • Network Meta-Analysis