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JP Journal of Biostatistics

JP Journal of Biostatistics
Volume 24, Issue 3, Pages 449 - 472 (November 2024)
http://dx.doi.org/10.17654/0973514324025

STOCHASTIC ANALYSIS OF A MODEL ON LIVER DISEASE CONSIDERING LIVER TRANSPLANTATION

Shikha Bhardwaj and Rajeev Kumar

Abstract:

Liver is a vital organ in human being. Liver disease has basically four different stages of its progression namely hepatitis or steatosis or hepatosteatosis (Stage 1), fibrosis (Stage 2), cirrhosis (Stage 3), and hepatocellular carcinoma (Stage 4). The diagnosis of a specific stage of liver disease can be made by clinical laboratory imaging or liver stiffness finding. The goal of the present paper is to analyze the performance of human liver to enhance survivability. For the purpose, a stochastic model has been developed for the human liver considering liver disease at different stages of its progression and liver transplantation at cirrhosis stage. Using Markov process and regenerative point technique, survivability measures are obtained and analyzed. Sensitivity and relative sensitivity analyses are also carried out to judge the impact of various parameters.

Keywords and phrases:

liver disease progression, liver transplantation, mean survival time, sensitivity analysis, Markov process and regenerative point technique

Received: April 30, 2024; Revised: August 3, 2024; Accepted: August 16, 2024; Published: August 23, 2024

How to cite this article: Shikha Bhardwaj and Rajeev Kumar, Stochastic analysis of a model on liver disease considering liver transplantation, JP Journal of Biostatistics 24(3) (2024), 449-472. https://doi.org/10.17654/0973514324025

This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License

References:

[1] A. S. Abdalrada, O. H. Yahya, A. H. M. Alaidi, N. A. Hussein, H. TH. S. Alrikabi and T. Al-Quraishi, A predictive model for liver disease progression based on logistic regression algorithm, Periodicals of Engineering and Natural Sciences 7(3) (2019), 1255-1264.

[2] A. Cardenas and P. Gines, Management of complications of cirrhosis in patients awaiting liver transplantation, Journal of Hepatology 42(1) (2005), 124-133.

https://doi.org/10.1016/j.jhep.2004.12.007.

[3] T. H. H. Chen, H. S. Kuo, M. F. Yen, M. S. Lai, L. Tabar and S. W. Duffy, Estimation of sojourn time in chronic disease screening without data on interval cases, Biometrics 56(1) (2000), 167-172.

DOI: 10.1111/j.0006-341x.2000.00167.x.

[4] M. Cohen, D. Katz and Y. Baruch, Stress among the family caregivers of liver transplant recipients, Prog Transplant 17(1) (2007), 48-53.

DOI: 10.1177/152692480701700107.

[5] A. Din and Y. Li, Mathematical analysis of a new nonlinear stochastic hepatitis B epidemic model with vaccination effect and a case study, The European Physical Journal Plus 137(558) (2022), 1-24.

https://doi.org/10.1140/epjp/s13360-022-02748-x.

[6] G. Grover, D. Seth, V. Ravi and P. K. Swain, A multistate Markov model for the progression of liver cirrhosis in the presence of various prognostic factors, Chilean Journal of Statistics 5(2) (2014), 15-27.

[7] I. Ivanova, Liver cirrhosis: new concepts, Scripta Scientifica Medica 48(2) (2016), 18-25. DOI: 10.14748/ssm.v48i2.1481.

[8] A. Khan, G. Hussain, A. Yusuf, A. H. Usman and U. W. Humphries, A hepatitis stochastic epidemic model with acute and chronic stages, Adv. Difference Equ. (2021), Paper No. 181, 10 pp. https://doi.org/10.1186/s13662-021-03335-7.

[9] M. Koch and P. Banys, Liver transplantation and opioid dependence, JAMA, 285(8) (2001), 1056-1058. DOI: 10.1001/jama.285.8.1056.

[10] J. Potosek, M. Curry, M. Buss and E. Chittenden, Integration of palliative care in end-stage liver disease and liver transplantation, Journal of Palliative Medicine 17(11) (2014), 1271-1277. DOI: 10.1089/jpm.2013.0167.

[11] F. N. U. Savanti, S. D. Jagani, K. Kumari Aradhna and A. Andani, Role and frequency of non-viral causes in chronic liver disease and cirrhosis, Journal of Population Therapeutics and Clinical Pharmacology 30(17) (2023), 277-286.

[12] A. Sharma and S. Nagalli, Chronic liver disease, Statpearls (Internet) Treasure Island (FL), StatPearls Publishing, 2024.

https://www.ncbi.nlm.nih.gov/books/NBK554597/.

[13] J. K. Suh, J. Lee, J. H. Lee, S. Shin, H. J. Tchoe and J.W. Kwon, Risk factors for developing liver cancer in people with and without liver disease, PLoS ONE 13(10) (2018), 1-13. https://doi.org/10.1371/journal.pone.0206374.

[14] J. Wiegand and T. Berg, The etiology, diagnosis and prevention of liver cirrhosis, Deutsches Ärzteblatt International 110(6) (2013), 85-91. DOI: 10.3238/arztebl.2013.0085.

[15] S. K. Yeom, C. H. Lee, S. H. Cha and C. M. Park, Prediction of liver cirrhosis, using diagnostic imaging tools, World Journal of Hepatology 7(17) (2015), 2069-2079. DOI: 10.4254/wjh.v7.i17.2069.

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