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Taking Back The Common Bile Duct - A Decision Tree Analysis for The Management Of Choledocholithiasis
*Rachel Morris, *Marc de Moya, *Todd Neideen, *Dan Holena, *Patrick B Murphy
Medical College of Wisconsin, Wauwatosa, WI

OBJECTIVE: The management of suspected choledocholithiasis typically consists of pre-operative magnetic resonance cholangiopancreatography (MRCP), endoscopic ultrasound (EUS) or endoscopic retrograde cholangiopancreatography (ERCP) followed by laparoscopic cholecystectomy (LC). Direct to LC and intra-operative cholangiogram (IOC) followed by transcystic common bile duct exploration (LCBDE) provides an alternative approach. The objectives of this study were to evaluate the cost-effectiveness of single-stage vs multistage clearance of the CBD in patients with a clinical suspicion for choledocholithiasis based on pre-test probability of choledocholithiasis and to develop a real-time tool for cost-estimation.
METHODS: We modeled a decision tree to compare the costs associated with the different treatment strategies for patients with suspected choledocholithiasis. The model parameters included pre-test probability of CBD stones and the associated costs of each of 4 decision strategies: (1) MRCP; (2) ERPC; (3) EUS; and, (4) LC and IOC. Decision nodes were assigned and expected cost was calculated based on the pre-test probability of choledocholithiasis, probability of treatment success, and cost. The primary outcome was overall expected cost from each strategy. Costs were from Medicare charges and sensitivity analyses were performed on all model parameters.
RESULTS: Direct to surgery via LC with IOC and a transcystic LCBDE if CBD stones were discovered had the lowest expected costs at all probabilities of choledocholithiasis, Figure 1. MRCP is the next favored strategy from a cost standpoint until the pre-test probability of choledocholithiasis reaches up to 80%. Pre-test probability of choledocholithiasis, probability of LCBDE success and cost of IOC have the greatest impact on expected costs in our model. An online tool was created to allow users to vary models inputs: (images/g37_2.png" target="_blank">


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