Development of a Predictive Model for Common Bile Duct Stones in Patients With Clinical Suspicion of Choledocholithiasis: A Cohort Study

Abstract

Background: Current choledocholithiasis guidelines heavily focus on patients with low or no risk, they may be inappropriate for populations with high rates of choledocholithiasis. We aimed to develop a predictive scoring model for choledocholithiasis in patients with relevant clinical manifestations.

Methods: A multivariable predictive model development study based on a retrospective cohort of patients with clinical suspicion of choledocholithiasis was used in this study. The setting was a 700-bed public tertiary hospital. Participants were patients who had completed three reference tests (endoscopic retrograde cholangiography, magnetic resonance cholangiopancreatography, and intraoperative cholangiography) from January 2019 to June 2021. The model was developed using logistic regression analysis. Predictor selection was conducted using a backward stepwise approach. Three risk groups were considered. Model performance was evaluated by area under the receiver operating characteristic curve, calibration, classification measures, and decision curve analyses.

Results: Six hundred twenty-one patients were included; the choledocholithiasis prevalence was 59.9%. The predictors were age > 55 years, pancreatitis, cholangitis, cirrhosis, alkaline phosphatase level of 125 - 250 or > 250 U/L, total bilirubin level > 4 mg/dL, common bile duct size > 6 mm, and common bile duct stone detection. Pancreatitis and cirrhosis each had a negative score. The sum of scores was -4.5 to 28.5. Patients were categorized into three risk groups: low-intermediate (score ≤ 5), intermediate (score 5.5 - 14.5), and high (score ≥ 15). Positive likelihood ratios were 0.16 and 3.47 in the low-intermediate and high-risk groups, respectively. The model had an area under the receiver operating characteristic curve of 0.80 (95% confidence interval: 0.76, 0.83) and was well-calibrated; it exhibited better statistical suitability to the high-prevalence population, compared to current guidelines.

Conclusions: Our scoring model had good predictive ability for choledocholithiasis in patients with relevant clinical manifestations. Consideration of other factors is necessary for clinical application, particularly regarding the availability of expert physicians and specialized equipment.

Keywords: Choledocholithiasis; Clinical decision rules; Risk assessment.

Figure 1

Study participant flow diagram. ^aPre-reference LFTs mean LFTs within 7 days before reference tests. CBD: common bile duct; ERC: endoscopic retrograde cholangiography; IOC: intraoperative cholangiography; LFTs: liver function tests; MRCP: magnetic resonance cholangiopancreatography.

Figure 2

Parametric ROC with 95% confidence band for CBD stone prediction using the scoring model. AUC: area under the receiver operating characteristic curve; CBD: common bile duct; CI: confidence interval; ROC: receiver operating characteristic curve.

Figure 3

Calibration plot comparing the score-predicted and observed risks of common bile duct stone. AUC: area under the receiver operating characteristic curve; CIs: confidence intervals; CITL: calibration-in-the-large; LOWESS: locally weighted scatterplot smoothing.

Figure 4

Risk curve. Risk curve illustrating the score-predicted CBD stone risk (solid line) and the observed stone risk (hollow circles) according to risk group (vertical dash line). The relative number of patients corresponds to the circle’s size. CBD: common bile duct.

Figure 5

Comparing validation of CBD stone score performance to CBD stone guidelines. Discriminative ability with ROC is shown in (a) and clinical utility with decision curve analysis is shown in (b). ASGE: American Society of Gastrointestinal Endoscopy; CBD: common bile duct; ESGE: European Society of Gastrointestinal Endoscopy; ROC: receiver operating characteristic curve.