Dataset Information

The Matching Status Between Donor and Recipient Hepatitis B Seroepidemiology Makes a Difference in Liver Transplantation for Hepatocellular Carcinoma.

ABSTRACT:

Introduction

Antibody to hepatitis B core antigen (HBcAb) is known to be related with the prognosis for patients with hepatocellular carcinoma (HCC). This study aims to evaluate the prognostic capacity of HbcAb and other donor/recipient hepatitis B seroepidemiological indexes in transplantation for HCC.

Methods

Based on the national liver transplant registry, we analyzed the prognostic capacity of HBcAb in liver transplantation for patients with HCC of different etiological backgrounds. The hepatitis B virus (HBV)-related HCC cohort was further studied regarding donor/recipient hepatitis B seroepidemiology, and then divided into a training cohort (n = 1,222) and a validation cohort (n = 611) to develop a pretransplant recurrence-risk predicting nomogram.

Results

Positive HbcAb in recipients was related to an increased risk of post-transplant tumor recurrence in HBV-related (n = 1,833, P = 0.007), HCV-related (n = 79, P = 0.037), and non-B non-C HCC (n = 313, P = 0.017). In HBV-related HCC (n = 1,833), donor hepatitis B surface antigen (HbsAg) was also associated with post-transplant tumor recurrence (P = 0.020). Multivariate analysis showed that the matching status of recipient HbcAb and donor HbsAg (MSHB) was an independent prognostic factor (P = 0.017). HbcAb-positive recipients matched with HbsAg-positive donors displayed the worst post-transplant outcomes (P < 0.001). In the training cohort (n = 1,222), a risk-predicting nomogram was established based on ?-fetoprotein, Milan criteria, and MSHB. The model showed excellent prognostic capacity and safely expanded Milan criteria in both training and validation cohorts (P < 0.001).

Discussion

Positive HbcAb in recipients increases the risk of post-transplant tumor recurrence in HCC with different etiological backgrounds. The nomogram based on MSHB is effective in predicting tumor recurrence after transplantation for HBV-related HCC.

SUBMITTER: Lu D

PROVIDER: S-EPMC7263649 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

The Matching Status Between Donor and Recipient Hepatitis B Seroepidemiology Makes a Difference in Liver Transplantation for Hepatocellular Carcinoma.

Lu Di D Yang Fan F Zhuo Jianyong J Yang Modan M Lin Zuyuan Z Jin Pingbo P Cai Xuechun X Cen Beini B Wang Jianguo J Wei Xuyong X Zheng Shusen S Xu Xiao X

Clinical and translational gastroenterology 20200501 5

<h4>Introduction</h4>Antibody to hepatitis B core antigen (HBcAb) is known to be related with the prognosis for patients with hepatocellular carcinoma (HCC). This study aims to evaluate the prognostic capacity of HbcAb and other donor/recipient hepatitis B seroepidemiological indexes in transplantation for HCC.<h4>Methods</h4>Based on the national liver transplant registry, we analyzed the prognostic capacity of HBcAb in liver transplantation for patients with HCC of different etiological backgr ...[more]

PMID: 32358239

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Project description:ObjectiveOne of the main problems of lung transplantation is the shortage of organs as well as reduced survival rates. In the absence of an international standardized model for lung donor-recipient allocation, we set out to develop such a model based on the characteristics of past experiences with lung donors and recipients with the aim of improving the outcomes of the entire transplantation process.MethodsThis was a retrospective analysis of 404 lung transplants carried out at the Reina Sofía University Hospital (Córdoba, Spain) over 23 years. We analyzed various clinical variables obtained via our experience of clinical practice in the donation and transplantation process. These were used to create various classification models, including classical statistical methods and also incorporating newer machine-learning approaches.ResultsThe proposed model represents a powerful tool for donor-recipient matching, which in this current work, exceeded the capacity of classical statistical methods. The variables that predicted an increase in the probability of survival were: higher pre-transplant and post-transplant functional vital capacity (FVC), lower pre-transplant carbon dioxide (PCO2) pressure, lower donor mechanical ventilation, and shorter ischemia time. The variables that negatively influenced transplant survival were low forced expiratory volume in the first second (FEV1) pre-transplant, lower arterial oxygen pressure (PaO2)/fraction of inspired oxygen (FiO2) ratio, bilobar transplant, elderly recipient and donor, donor-recipient graft disproportion requiring a surgical reduction (Tailor), type of combined transplant, need for cardiopulmonary bypass during the surgery, death of the donor due to head trauma, hospitalization status before surgery, and female and male recipient donor sex.ConclusionsThese results show the difficulty of the problem which required the introduction of other variables into the analysis. The combination of classical statistical methods and machine learning can support decision-making about the compatibility between donors and recipients. This helps to facilitate reliable prediction and to optimize the grafts for transplantation, thereby improving the transplanted patient survival rate.

Dataset Information

The Matching Status Between Donor and Recipient Hepatitis B Seroepidemiology Makes a Difference in Liver Transplantation for Hepatocellular Carcinoma.

Introduction

Methods

Results

Discussion

Publications

The Matching Status Between Donor and Recipient Hepatitis B Seroepidemiology Makes a Difference in Liver Transplantation for Hepatocellular Carcinoma.

Similar Datasets

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