A novel nomogram for prognosis stratification in salvage liver transplantation: a national-wide study with propensity score matching analysis in China.

Background: Salvage liver transplantation (SLT) has been reported to be an efficient treatment option for patients with recurrent hepatocellular carcinoma (HCC) after liver resection (LR). However, for recipients who underwent liver transplantation (LT) due to recurrent HCC after LR in China, the selection criteria are not well established. Methods: In this study, data from the China Liver Transplant Registry (CLTR) of 4,244 LT performed from January 2015 to December 2019 were examined, including 3,498 primary liver transplantation (PLT) and 746 SLT recipients. Propensity score matching (PSM) analysis was used to minimize between-group imbalances. The overall survival (OS) and disease-free survival (DFS) between PLT and SLT in recipients fulfilling the Milan or Hangzhou criteria were compared based on the multivariate analysis, nomograms were plotted to further classify the SLT group into low- and high-risk groups. Results: In this study, the 1-, 3- and 5-year OS and DFS of SLT recipients fulfilling Milan criteria (OS, P=0.01; DFS, P<0.001) or Hangzhou criteria (OS, P=0.03; DFS, P=0.003) were significantly reduced when compared to that of PLT group after PSM analysis. Independent risk factors, including preoperative transarterial chemoembolization (TACE), alpha fetoprotein (AFP) level, tumor maximum size and tumor total diameter were selected to draw a prognostic nomogram. The low-risk SLT recipients (1-year, 95.34%; 3-year, 84.26%; 5-year, 77.20%) showed a comparable OS with PLT recipients fulfilling Hangzhou criteria (P=0.107). Conclusions: An optimal nomogram model for prognosis stratification and clinical decision guidance of SLT was established. The low-risk SLT recipients based on the nomograms showed comparable survival with those fulfilling Hangzhou criteria in PLT group.

Development and validation of a nomogram model for predicting chronic kidney disease after liver transplantation: a multi-center retrospective study.

Chronic kidney disease (CKD) is a frequent complication after liver transplantation (LT) and associated with poor prognosis. In this study, we retrospectively analyzed 515 adult patients who underwent LT in our center. They were randomly divided into a training set (n = 360) and an internal test set (n = 155). Another 118 recipients in other centers served as external validation set. Univariate and multivariate COX regression analysis were used to determine risk factors. A nomogram model was developed to predict post-LT CKD. The incidence of post-LT CKD in our center was 16.9% (87/515) during a median follow-up time of 22.73 months. The overall survival of recipients with severe CKD (stage IV and V) were significantly lower than those with non or mild CKD (stage III) (p = 0.0015). A nomogram model was established based on recipient's age, anhepatic phase, estimated glomerular filtration rate and triglyceride levels at 30 days after LT. The calibration curves for post-LT CKD prediction in the nomogram were consistent with the actual observation in both the internal and external validation set. In conclusion, severe post-LT CKD resulted in a significantly reduced survival in liver recipient. The newly established nomogram model had good predictive ability for post-LT CKD.

TNFR2 is a potent prognostic biomarker for post-transplant lung metastasis in patients with hepatocellular carcinoma.

Objective: Lung metastasis is a common and fatal complication of liver transplantation for hepatocellular carcinoma (HCC). The precise prediction of post-transplant lung metastasis in the early phase is of great value. Methods: The mRNA profiles of primary and paired lung metastatic lesions were analyzed to determine key signaling pathways. We enrolled 241 HCC patients who underwent liver transplantation from three centers. Tissue microarrays were used to evaluate the prognostic capacity of tumor necrosis factor (TNF), tumor necrosis factor receptor 1 (TNFR1), and TNFR2, particularly for post-transplant lung metastasis. Results: Comparison of primary and lung metastatic lesions revealed that the TNF-dependent signaling pathway was related to lung metastasis of HCC. The expression of TNF was degraded in comparison to that in para-tumor tissues (P<0.001). The expression of key receptors in the TNF-dependent signaling pathway, TNFR1 and TNFR2, was higher in HCC tissues than in para-tumor tissues (P<0.001). TNF and TNFR1 showed no relationship with patients' outcomes, whereas elevated TNFR2 in tumor tissue was significantly associated with worse overall survival (OS) and increased recurrence risk (5-year OS rate: 31.9% vs. 62.5%, P<0.001). Notably, elevated TNFR2 levels were also associated with an increased risk of post-transplant lung metastasis (hazard ratio: 1.146; P<0.001). Cox regression analysis revealed that TNFR2, Hangzhou criteria, age, and hepatitis B surface antigen were independent risk factors for post-transplant lung metastasis, and a novel nomogram was established accordingly. The nomogram achieved excellent prognostic efficiency (area under time-dependent receiver operating characteristic =0.755, concordance-index =0.779) and was superior to conventional models, such as the Milan criteria. Conclusions: TNFR2 is a potent prognostic biomarker for predicting post-transplant lung metastasis in patients with HCC. A nomogram incorporating TNFR2 deserves to be a helpful prognostic tool in liver transplantation for HCC.

Prognostic implication of early posttransplant hypercholesterolemia in liver transplantation for patients with hepatocellular carcinoma.

BACKGROUND: Hyperlipidemia is a common complication after liver transplantation (LT) and develops mostly in the early posttransplant period. Recently, some studies have reported a positive correlation between hyperlipidemia and favorable prognosis in patients with hepatocellular carcinoma (HCC) undergoing hepatectomy. This study aimed to evaluate the possibility of predicting prognosis in HCC patients receiving LT by early posttransplant dyslipidemia. METHODS: From January 2015 to December 2017, a total of 806 HCC patients from China Liver Transplant Registry database were retrospectively enrolled. The prognostic relevance of early posttransplant hypertriglyceridemia or hypercholesterolemia was examined using survival analysis, and subgroup analysis was implemented based on LT criteria. RESULTS: Early posttransplant hypercholesterolemia (EPHC) was independently inversely associated with the risk of recurrence [hazard ratio (HR) = 0.630; P = 0.022], but was not significantly correlated with the mortality. However, early posttransplant hypertriglyceridemia was not related to prognosis. Intriguingly, with further classification, we found that borderline EPHC (B-EPHC), instead of significant EPHC, was a predictor of lower risk for both recurrence (HR = 0.504; P = 0.006) and mortality (HR = 0.511; P = 0.023). Compared with non-EPHC patients, B-EPHC patients achieved significantly superior 1-year and 3-year tumor-free survival (89.6% and 83.7% vs. 83.8% and 72.7% respectively; P = 0.023), and 1-year and 3-year overall survival (95.8% and 84.8% vs. 94.6% and 77.6% respectively; P = 0.039). In the subgroup analysis, B-EPHC remained an independent predictor of better prognosis in patients beyond Milan criteria and those within Hangzhou criteria; whereas there was no significant relationship between B-EPHC and prognosis in patients within Milan criteria and those beyond Hangzhou criteria. More interestingly, patients beyond Milan criteria but within Hangzhou criteria were identified as the crucial subpopulation who benefited from B-EPHC (recurrence HR = 0.306, P = 0.011; mortality HR = 0.325, P = 0.031). CONCLUSIONS: B-EPHC could assist transplant teams in dynamically evaluating prognosis after LT for HCC as a postoperative non-oncological biomarker, especially in patients beyond Milan criteria but within Hangzhou criteria.

Utilization of elderly donors in liver transplantation for patients with hepatocellular carcinoma: A national retrospective cohort study of China.

BACKGROUND: Profound organ shortages worldwide have led to the increased utilization of marginal organs from older individuals. However, the effectiveness of liver transplantation (LT) with organs from elderly donors for patients with hepatocellular carcinoma (HCC) remains controversial. The objective of the current study was to assess the overall survival (OS) and disease-free survival (DFS) of patients with HCC following LT using grafts from deceased donors over 60 years old. MATERIAL AND METHODS: Patients with HCC who underwent LT between 2015 and 2018 were identified in the China Liver Transplant Registry database. The overall survival and disease-free survival of older liver donors (OLDs) were compared with those of younger liver donors (YLDs) after propensity score matching. RESULTS: From January 2015 to December 2018, a total of 4971 HCC patients were enrolled in the study according to the screening criteria. The absolute and relative utilization of liver grafts from elderly patients over 60 years for HCC patients increased every year, from 65 (9.3%) in 2015 to 268 (14.5%) in 2018. Disease-free survival (DFS) was significantly lower in HCC patients with elderly donors (both P < 0.05) after propensity score matching. The OLD group had worse DFS than YLD group if patients had tumors beyond the Milan criteria (P < 0.05). CONCLUSIONS: The use of older donors for LT has been growing quickly in the last few years in China. Grafts from older donors can be safely used in HCC recipients with similar OS and comparable perioperative complications. However, further investigation into whether older donor has an impact on recurrence is warranted, especially among those with tumors beyond the Milan criteria.

Impact of hepatitis B surface antigen positive grafts on liver transplantation in patients with benign and malignant liver disease.

Hepatitis B surface antigen (HBsAg) persists after liver transplantation in almost all patients receiving HBsAg-positive grafts. Chronic hepatitis B virus (HBV) infection is one of the main causes of hepatocellular carcinoma (HCC). We aimed to investigate possible interactions between HBsAg-positive donors, HCC, HBV-related transplant indication, and long-term outcomes. This retrospective study enrolled 1176 patients from two centers between January 2015 and May 2019, of which 135 (11.5%) were HBsAg-positive and 1041 (88.5%) were HBsAg-negative donors. Cox regression models were fitted to study the association between variables and patient and graft survival. In univariate and multivariate analyses, the donor HBsAg status was not significantly associated with patient and graft survival in the entire cohort, but there was a significant interaction between HBsAg-positive donors and HCC, independent of HBV-related transplant indication. The cumulative incidence of patient and graft survival was significantly lower in the subgroup of HCC recipients receiving HBsAg-positive grafts, but no significant difference was found in recipients with benign liver disease. In a subgroup analysis of HCC recipients, HBsAg-positive donors were significantly associated with an increased risk of HCC recurrence (hazard ratio: 1.73; 95% confidence interval: 1.20-2.48; p = 0.003) and similar results were obtained after propensity score matching analysis. We showed excellent outcomes of using HBsAg-positive grafts in patients with benign liver disease, regardless of HBV-related transplant indications. However, positive grafts should be used with caution in recipients with HCC, which are associated with an increased risk of HCC recurrence.

A model integrated fibrinogen and D-dimer for prediction of hepatocellular carcinoma recurrence following liver transplantation: a multicentre study.

BACKGROUND: We aimed to investigate whether D-dimer and fibrinogen levels could predict prognosis of patients with hepatocellular carcinoma (HCC) following liver transplantation. METHODS: From January 2015 to January 2020, we conducted a study on patients with hepatitis B-related liver cancer. Two hundred seventy (270) liver transplant recipients were recruited. Considering D-dimer and plasma fibrinogen levels, a model was established to predict liver cancer recurrence following liver transplantation. Subsequent verification was performed on a validation cohort of 295 recipients from two other hospitals. RESULTS: Elevated D-dimer and plasma fibrinogen levels demonstrated independent correlation between overall survival and tumour-free survival among patients with HCC who underwent liver transplantation. Those who had preoperative fibrinogen ≥2.27 g/L had significantly reduced overall survival and tumour-free survival than those who had preoperative fibrinogen <2.27 g/L, in the discovery cohort. Recipients with increased risk had preoperative plasma D-dimer ≥2400 µg/L. The model was: Y= logit (P) =0.91* fibrinogen concentration +0.967* D-dimer +0.585* alpha-fetoprotein +1.623* Milan criteria +0.68* microvascular invasion -3.159. At a cut-off score of -1.524, the validation cohort had area under curve values of 0.764 and 0.828 respectively; analysis of this data optimised predictive performance for overall and tumour-free survival. CONCLUSIONS: For patients who have undergone liver transplantation for HCC, preoperative D-dimer and fibrinogen levels independently predicted key outcomes such as overall survival and tumour-free survival.

The distinct responsiveness of cytokeratin 19-positive hepatocellular carcinoma to regorafenib.

Cytokeratin 19-positive (CK19+) hepatocellular carcinoma (HCC) is an aggressive subtype characterized by early recurrence and chemotherapy tolerance. However, there is no specific therapeutic option for CK19+ HCC. The correlation between tumor recurrence and expression status of CK19 were studied in 206 patients undergoing liver transplantation for HCC. CK19-/+ HCC cells were isolated to screen effective antitumor drugs. The therapeutic effects of regorafenib were evaluated in patient-derived xenograft (PDX) models from 10 HCC patients. The mechanism of regorafenib on CK19+ HCC was investigated. CK19 positiveness indicated aggressiveness of tumor and higher recurrence risk of HCC after liver transplantation. The isolated CK19+ HCC cells had more aggressive behaviors than CK19- cells. Regorafenib preferentially increased the growth inhibition and apoptosis of CK19+ cells in vitro, whereas sorafenib, apatinib, and 5-fluorouracil did not. In PDX models from CK19-/+ HCC patients, the tumor control rate of regorafenib achieved 80% for CK19+ HCCs, whereas 0% for CK19- HCCs. RNA-sequencing revealed that CK19+ cells had elevated expression of mitochondrial ribosomal proteins, which are essential for mitochondrial function. Further experiments confirmed that regorafenib attenuated the mitochondrial respiratory capacity in CK19+ cells. However, the mitochondrial respiration in CK19- cells were faint and hardly repressed by regorafenib. The mitochondrial respiration was regulated by the phosphorylation of signal transducer and activator of transcription 3 (STAT3), which was inhibited by regorafenib in CK19+ cells. Hence, CK19 could be a potential marker of the therapeutic benefit of regorafenib, which facilitates the individualized therapy for HCC. STAT3/mitochondria axis determines the distinct response of CK19+ cells to regorafenib treatment.

A preoperative model for predicting microvascular invasion and assisting in prognostic stratification in liver transplantation for HCC regarding empirical criteria.

PURPOSE: The prediction of microvascular invasion (MVI) has increasingly been recognized to reflect prognosis involving local invasion and distant metastasis of hepatocellular carcinoma (HCC). The aim of this study was to assess a predictive model using preoperatively accessible clinical parameters and radiographic features developed and validated to predict MVI. This predictive model can distinguish clinical outcomes after liver transplantation (LT) for HCC patients. METHODS: In total, 455 HCC patients who underwent LT between January 1, 2015, and December 31, 2019, were retrospectively enrolled in two centers in China as a training cohort (ZFA center; n = 244) and a test cohort (SLA center; n = 211). Univariate and multivariate backward logistic regression analysis were used to select the significant clinical variables which were incorporated into the predictive nomogram associated with MVI. Receiver operating characteristic (ROC) curves based on clinical parameters were plotted to predict MVI in the training and test sets. RESULTS: Univariate and multivariate backward logistic regression analysis identified four independent preoperative risk factors for MVI: α-fetoprotein (AFP) level (p < 0.001), tumor size ((p < 0.001), peritumoral star node (p = 0.003), and tumor margin (p = 0.016). The predictive nomogram using these predictors achieved an area under curve (AUC) of 0.85 and 0.80 in the training and test sets. Furthermore, MVI could discriminate different clinical outcomes within the Milan criteria (MC) and beyond the MC. CONCLUSIONS: The nomogram based on preoperatively clinical variables demonstrated good performance for predicting MVI. MVI may serve as a supplement to the MC.

C-Reactive Protein Is an Independent Predictor of 30-Day Bacterial Infection Post-Liver Transplantation.

The relationship between aseptic systemic inflammation and postoperative bacterial infection is unclear. We investigated the correlation of systemic inflammation biomarkers with 30-day clinically significant bacterial infections (CSI) after liver transplantation (LT). This retrospective study enrolled 940 patients who received LT and were followed for 30 days. The primary end point was 30-day CSI events. The cohort was divided into exploratory (n = 508) and validation (n = 432) sets according to different centers. Area under the receiver operated characteristic (AUROC) and Cox regression models were fitted to study the association between baseline systemic inflammation levels and CSI after LT. A total of 255 bacterial infectious events in 209 recipients occurred. Among systemic inflammation parameters, baseline C-reactive protein (CRP) was independently associated with 30-day CSI in the exploratory group. The combination of CRP and organ failure number showed a good discrimination for 30-day CSI (AUROC = 0.80, 95% CI, 0.76-0.84) and the results were confirmed in an external verification group. Additionally, CRP levels were correlated with bacterial product lipopolysaccharide. In conclusion, our study suggests that pre-transplantation CRP is independent of other prognostic factors for 30-day CSI post-LT, and can be integrated into tools for assessing the risk of bacterial infection post-LT or as a component of prognostic models.

A double-layer hydrogel based on alginate-carboxymethyl cellulose and synthetic polymer as sustained drug delivery system.

A new double-layer, pH-sensitive, composite hydrogel sustained-release system based on polysaccharides and synthetic polymers with combined functions of different inner/outer hydrogels was prepared. The polysaccharides inner core based on sodium alginate (SA) and carboxymethyl cellulose (CMC), was formed by physical crosslinking with pH-sensitive property. The synthetic polymer out-layer with enhanced stability was introduced by chemical crosslinking to eliminate the expansion of inner core and the diffusion of inner content. The physicochemical structure of the double-layer hydrogels was characterized. The drug-release results demonstrated that the sustained-release effect of the hydrogels for different model drugs could be regulated by changing the composition or thickness of the hydrogel layer. The significant sustained-release effect for BSA and indomethacin indicated that the bilayer hydrogel can be developed into a novel sustained delivery system for bioactive substance or drugs with potential applications in drugs and functional foods.

Application of machine learning models for predicting acute kidney injury following donation after cardiac death liver transplantation.

BACKGROUND: Acute kidney injury (AKI) is a common complication after liver transplantation (LT) and is an indicator of poor prognosis. The establishment of a more accurate preoperative prediction model of AKI could help to improve the prognosis of LT. Machine learning algorithms provide a potentially effective approach. METHODS: A total of 493 patients with donation after cardiac death LT (DCDLT) were enrolled. AKI was defined according to the clinical practice guidelines of kidney disease: improving global outcomes (KDIGO). The clinical data of patients with AKI (AKI group) and without AKI (non-AKI group) were compared. With logistic regression analysis as a conventional model, four predictive machine learning models were developed using the following algorithms: random forest, support vector machine, classical decision tree, and conditional inference tree. The predictive power of these models was then evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: The incidence of AKI was 35.7% (176/493) during the follow-up period. Compared with the non-AKI group, the AKI group showed a remarkably lower survival rate (P < 0.001). The random forest model demonstrated the highest prediction accuracy of 0.79 with AUC of 0.850 [95% confidence interval (CI): 0.794-0.905], which was significantly higher than the AUCs of the other machine learning algorithms and logistic regression models (P < 0.001). CONCLUSIONS: The random forest model based on machine learning algorithms for predicting AKI occurring after DCDLT demonstrated stronger predictive power than other models in our study. This suggests that machine learning methods may provide feasible tools for forecasting AKI after DCDLT.

TNT: An Interpretable Tree-Network-Tree Learning Framework using Knowledge Distillation.

Deep Neural Networks (DNNs) usually work in an end-to-end manner. This makes the trained DNNs easy to use, but they remain an ambiguous decision process for every test case. Unfortunately, the interpretability of decisions is crucial in some scenarios, such as medical or financial data mining and decision-making. In this paper, we propose a Tree-Network-Tree (TNT) learning framework for explainable decision-making, where the knowledge is alternately transferred between the tree model and DNNs. Specifically, the proposed TNT learning framework exerts the advantages of different models at different stages: (1) a novel James-Stein Decision Tree (JSDT) is proposed to generate better knowledge representations for DNNs, especially when the input data are in low-frequency or low-quality; (2) the DNNs output high-performing prediction result from the knowledge embedding inputs and behave as a teacher model for the following tree model; and (3) a novel distillable Gradient Boosted Decision Tree (dGBDT) is proposed to learn interpretable trees from the soft labels and make a comparable prediction as DNNs do. Extensive experiments on various machine learning tasks demonstrated the effectiveness of the proposed method.

New-onset hyperglycemia immediately after liver transplantation: A national survey from China Liver Transplant Registry.

BACKGROUND: New-onset hyperglycemia (NOH) is a common phenomenon after liver transplantation (LT), but its impact on clinical outcomes has not yet been fully assessed. We aimed to evaluate the etiology and prognosis of NOH within 1 month after LT. METHODS: The data of 3339 adult patients who underwent primary LT from donation after citizen death between January 2010 and June 2016 were extracted from China Liver Transplant Registry database and analyzed. NOH was defined as fasting blood glucose ≥7.0 mmol/L confirmed on at least two occasions within the first post-transplant month with or without hypoglycemic agent. RESULTS: Of 3339 liver recipients, 1416 (42.4%) developed NOH. Recipients with NOH had higher incidence of post-transplant complications such as graft and kidney failure, infection, biliary stricture, cholangitis, and tumor recurrence in a glucose concentration-dependent manner as compared to non-NOH recipients (P < 0.05). The independent risk factors of NOH were donor warm ischemic time >10 min, cold ischemic time >10 h, anhepatic time >60 min, recipient model for end-stage liver disease score >30, moderate ascites and corticosteroid usage (P < 0.05). Liver enzymes (alanine aminotransferase and gamma-glutamyltranspeptidase) on post-transplant day 7 significantly correlated with NOH (P < 0.001). CONCLUSIONS: NOH leads to increased morbidity and mortality in liver recipients. Close surveillance and tight control of blood glucose are desiderated immediately following LT particularly in those with delayed graft function and receiving corticosteroid. Strategic targeting graft ischemic injury may help maintain glucose homeostasis.