Bayesian Network-based Survival Prediction Model for Patients Having Undergone Post-transjugular Intrahepatic Portosystemic Shunt for Portal Hypertension

Overview

Journal World J Gastroenterol

Publisher Baishideng Publishing Group

Specialty Gastroenterology

Date 2024 Apr 25

PMID 38659484

Authors

Rong Chen

Ling Luo

Yun-Zhi Zhang

Zhen Liu

An-Lin Liu

Yi-Wen Zhang

Affiliations

Soon will be listed here.

Abstract

Background: Portal hypertension (PHT), primarily induced by cirrhosis, manifests severe symptoms impacting patient survival. Although transjugular intrahepatic portosystemic shunt (TIPS) is a critical intervention for managing PHT, it carries risks like hepatic encephalopathy, thus affecting patient survival prognosis. To our knowledge, existing prognostic models for post-TIPS survival in patients with PHT fail to account for the interplay among and collective impact of various prognostic factors on outcomes. Consequently, the development of an innovative modeling approach is essential to address this limitation.

Aim: To develop and validate a Bayesian network (BN)-based survival prediction model for patients with cirrhosis-induced PHT having undergone TIPS.

Methods: The clinical data of 393 patients with cirrhosis-induced PHT who underwent TIPS surgery at the Second Affiliated Hospital of Chongqing Medical University between January 2015 and May 2022 were retrospectively analyzed. Variables were selected using Cox and least absolute shrinkage and selection operator regression methods, and a BN-based model was established and evaluated to predict survival in patients having undergone TIPS surgery for PHT.

Results: Variable selection revealed the following as key factors impacting survival: age, ascites, hypertension, indications for TIPS, postoperative portal vein pressure (post-PVP), aspartate aminotransferase, alkaline phosphatase, total bilirubin, prealbumin, the Child-Pugh grade, and the model for end-stage liver disease (MELD) score. Based on the above-mentioned variables, a BN-based 2-year survival prognostic prediction model was constructed, which identified the following factors to be directly linked to the survival time: age, ascites, indications for TIPS, concurrent hypertension, post-PVP, the Child-Pugh grade, and the MELD score. The Bayesian information criterion was 3589.04, and 10-fold cross-validation indicated an average log-likelihood loss of 5.55 with a standard deviation of 0.16. The model's accuracy, precision, recall, and F1 score were 0.90, 0.92, 0.97, and 0.95 respectively, with the area under the receiver operating characteristic curve being 0.72.

Conclusion: This study successfully developed a BN-based survival prediction model with good predictive capabilities. It offers valuable insights for treatment strategies and prognostic evaluations in patients having undergone TIPS surgery for PHT.

References

Park E, Chang H, Nam H . A Bayesian Network Model for Predicting Post-stroke Outcomes With Available Risk Factors. Front Neurol. 2018; 9:699. PMC: 6137617. DOI: 10.3389/fneur.2018.00699. View

Turco L, Villanueva C, La Mura V, Garcia-Pagan J, Reiberger T, Genesca J . Lowering Portal Pressure Improves Outcomes of Patients With Cirrhosis, With or Without Ascites: A Meta-Analysis. Clin Gastroenterol Hepatol. 2019; 18(2):313-327.e6. DOI: 10.1016/j.cgh.2019.05.050. View

Bureau C, Metivier S, DAmico M, Peron J, Otal P, Carlos Garcia Pagan J . Serum bilirubin and platelet count: a simple predictive model for survival in patients with refractory ascites treated by TIPS. J Hepatol. 2010; 54(5):901-7. DOI: 10.1016/j.jhep.2010.08.025. View

Hung M, Lee E . Role of Transjugular Intrahepatic Portosystemic Shunt in the Management of Portal Hypertension: Review and Update of the Literature. Clin Liver Dis. 2019; 23(4):737-754. DOI: 10.1016/j.cld.2019.07.004. View

Bhatia Kapoor P, Benjamin J, Tripathi H, Patidar Y, Maiwall R, Kumar G . Post-transjugular Intrahepatic Portosystemic Shunt Hepatic Encephalopathy: Sarcopenia Adds Insult to Injury. Turk J Gastroenterol. 2023; 34(4):406-412. PMC: 10210830. DOI: 10.5152/tjg.2023.21964. View

Carrier P, Debette-Gratien M, Jacques J, Loustaud-Ratti V . Cirrhotic patients and older people. World J Hepatol. 2019; 11(9):663-677. PMC: 6783402. DOI: 10.4254/wjh.v11.i9.663. View

Iluz-Freundlich D, Grubert Van Iderstine M, Uhanova J, Zhang M, Knowles C, Minuk G . Low serum alkaline phosphatase levels in patients with chronic liver diseases: Possible contributions to disease pathogenesis. Clin Res Hepatol Gastroenterol. 2021; 45(4):101694. DOI: 10.1016/j.clinre.2021.101694. View

Wu Y, Li Q, Cai Z, Zhang Y, Qiu Y, Yang N . Survival prediction for gallbladder carcinoma after curative resection: Comparison of nomogram and Bayesian network models. Eur J Surg Oncol. 2020; 46(11):2106-2113. DOI: 10.1016/j.ejso.2020.07.009. View

Xu X, Ding H, Li W, Xu J, Han Y, Jia J . Chinese guidelines on the management of liver cirrhosis (abbreviated version). World J Gastroenterol. 2020; 26(45):7088-7103. PMC: 7723671. DOI: 10.3748/wjg.v26.i45.7088. View

10.

Li K, Cheng Y, Zhao R, Jiang H, Zhang L, Tong Y . Prediction of mortality and overt hepatic encephalopathy undergoing transjugular intrahepatic portosystemic shunt: a retrospective cohort study. Abdom Radiol (NY). 2023; 49(3):908-918. DOI: 10.1007/s00261-023-04086-7. View

11.

Ranasinghe R, Biswas M, Vincent R . Prealbumin: The clinical utility and analytical methodologies. Ann Clin Biochem. 2020; 59(1):7-14. DOI: 10.1177/0004563220931885. View

12.

Li R, Zhang C, Du K, Dan H, Ding R, Cai Z . Analysis of Prognostic Factors of Rectal Cancer and Construction of a Prognostic Prediction Model Based on Bayesian Network. Front Public Health. 2022; 10:842970. PMC: 9247333. DOI: 10.3389/fpubh.2022.842970. View

13.

Khabbaz R, Lokken R, Chen Y, Lipnik A, Bui J, Ray Jr C . Albumin-Bilirubin and Platelet-Albumin-Bilirubin Grades Do Not Predict Survival After Transjugular Intrahepatic Portosystemic Shunt Creation. Cardiovasc Intervent Radiol. 2018; 41(7):1029-1034. DOI: 10.1007/s00270-018-1923-2. View

14.

Sun S, Eche T, Dorczynski C, Otal P, Revel-Mouroz P, Zadro C . Predicting death or recurrence of portal hypertension symptoms after TIPS procedures. Eur Radiol. 2022; 32(5):3346-3357. DOI: 10.1007/s00330-021-08437-0. View

15.

Simonetto D, Liu M, Kamath P . Portal Hypertension and Related Complications: Diagnosis and Management. Mayo Clin Proc. 2019; 94(4):714-726. DOI: 10.1016/j.mayocp.2018.12.020. View

16.

Mandato C, Vajro P . Isolated aspartate aminotransferase elevation: Is it liver disease or what else?. Acta Paediatr. 2021; 111(3):459-461. DOI: 10.1111/apa.16213. View

17.

Adebayo D, Neong S, Wong F . Refractory Ascites in Liver Cirrhosis. Am J Gastroenterol. 2018; 114(1):40-47. DOI: 10.1038/s41395-018-0185-6. View

18.

Queck A, Schwierz L, Gu W, Ferstl P, Jansen C, Uschner F . Targeted decrease of portal hepatic pressure gradient improves ascites control after TIPS. Hepatology. 2022; 77(2):466-475. DOI: 10.1002/hep.32676. View

19.

Liang Z, Li L, Cao L, Liu J, Liu J . Analyses on Clinical Efficacy of TIPS in the Treatment of Cirrhotic Portal Hypertension and Relevant Influencing Factors. Cell Mol Biol (Noisy-le-grand). 2022; 68(7):129-134. DOI: 10.14715/cmb/2022.68.7.21. View

20.

Fan Z, Wang C, Fang L, Ma L, Niu T, Wang Z . Risk factors and a Bayesian network model to predict ischemic stroke in patients with dilated cardiomyopathy. Front Neurosci. 2022; 16:1043922. PMC: 9683474. DOI: 10.3389/fnins.2022.1043922. View