Cost-effectiveness of endoscopic ultrasound-directed transgastric ERCP compared with device-assisted and laparoscopic-assisted ERCP in patients with Roux-en-Y anatomy

2019 
Background  Roux-en-Y gastric bypass (RYGB) surgery is the second most common weight loss surgery in the United States. Treatment of pancreaticobiliary disease in this patient population is challenging due to the altered anatomy, which limits the use of standard instruments and techniques. Both nonoperative and operative modalities are available to overcome these limitations, including device-assisted (DAE) endoscopic retrograde cholangiopancreatography (ERCP), laparoscopic-assisted (LA) ERCP, and endoscopic ultrasound-directed transgastric ERCP (EDGE). The aim of this study was to compare the cost-effectiveness of ERCP-based modalities for treatment of pancreaticobiliary diseases in post-RYGB patients. Methods  A decision tree model with a 1-year time horizon was used to analyze the cost-effectiveness of EDGE, DAE-ERCP, and LA-ERCP in post-RYGB patients. Monte Carlo simulation was used to assess a plausible range of incremental cost-effectiveness ratios, net monetary benefit calculations, and a cost-effectiveness acceptability curve. One-way sensitivity analyses and probabilistic sensitivity analyses were also performed to assess how changes in key parameters affected model conclusions. Results  EDGE resulted in the lowest total costs and highest total quality-adjusted life-years (QALY) for a total of $5188/QALY, making it the dominant alternative compared with DAE-ERCP and LA-ERCP. In probabilistic analyses, EDGE was the most cost-effective modality compared with LA-ERCP and DAE-ERCP in 94.4 % and 97.1 % of simulations, respectively. Conclusion  EDGE was the most cost-effective modality in post-RYGB anatomy for treatment of pancreaticobiliary diseases compared with DAE-ERCP and LA-ERCP. Sensitivity analysis demonstrated that this conclusion was robust to changes in important model parameters.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    33
    References
    17
    Citations
    NaN
    KQI
    []