Establishment and validation of a prediction model for the first recurrence of Budd–Chiari syndrome after endovascular treatment: a large sample size, single-center retrospective study

Abstract

Abstract Objective To investigate the independent risk factors for the first recurrence after endovascular management in patients with Budd–Chiari syndrome (BCS), and to establish a prediction model for predicting recurrence in target patients. Methods BCS patients who underwent endovascular treatment in the Affiliated Hospital of Xuzhou Medical University from January 2010 to December 2015 were retrospectively examined, with their clinical, laboratory test, and imaging data collected and analyzed. Independent risk factors for recurrence were identified, and a prediction model was established and validated. Results A total of 450 patients met the filtering criteria, and 102 recurred during the follow-up. The median follow-up time was 87 months, ranging from 1 to 137 months. The 1-, 3-, 5- and 10-year cumulative recurrence rate was 9.11% (6.41–11.73%), 17.35% (13.77–20.78%), 20.10% (16.30–23.72%), and 23.06% (18.86–27.04%), respectively. Liver cirrhosis, ascites, thrombosis, and all the main intrahepatic drainage veins obstructed (obstructed HV + AHV) are independent risk factors, while age is an independent protective factor. The prediction model was named MRBET. Based on the model, the risk score of each patient equals (−0.385981 * Age/10) + (0.0404184 * PT) + (0.0943423 * CRE/10) + (0.0157053 * LDH/10) + (0.592179 * LC) + (0.896034 * Ascites) + (0.691346 * Thrombosis) + (0.886741 * obstructed HV + AHV), and those in the high-risk group (risk score ≥ 1.57) were more likely to recur than those in the low-risk group (HR = 6.911, p < 0.001). The MRBET model is also available as a web tool at https://mrbet.shinyapps.io/dynnomapp. Conclusion Liver cirrhosis, ascites, thrombosis, and obstructed HV + AHV are independent risk factors for the first recurrence; age is an independent protective factor. The prediction model can effectively and conveniently predict the risk of recurrence and screen out patients at a high recurrence risk.