Cillo, Umberto

Normothermic Regional Perfusion (NRP) is emerging as a game-changer in enhancing outcomes for Donation after Circulatory Determination of Death (DCDD). NRP maintains physiological conditions through perfusion with oxygenated blood, outperforming conventional super-rapid recovery techniques significantly improving outcomes and organ utilization. Despite its clinical benefits, widespread adoption of NRP is impeded by heterogeneous organizational, legal, and ethical frameworks. At the ESOT Bucharest Consensus Conference, leading experts in transplantation achieved consensus on 130 relevant NRP-related open issues to facilitate its implementation and guide global practice. Key recommendations include criteria for adoption of NRP, minimal requirements, procedures to be adopted before and during NRP, donor organ evaluation criteria and sequence of organ harvesting. Consensus extends to procedural components (including the configuration of perfusion parameters and strategic team coordination), ethical integrity of NRP in the context of the dead donor rule and key unmet needs for future developments. While significant strides were made in unifying practice, unresolved issues regarding maximum warm ischemic time and variability in legal standards indicate avenues for future research. This consensus underscores the imperative for global standardization in NRP application, promising to elevate the success rates of organ transplants and establish NRP as a foundational element in the evolution of DCDD.

HCC recurrence following liver transplantation (LT) is highly morbid and occurs despite strict patient selection criteria. Individualized prediction of post-LT HCC recurrence risk remains an important need. Clinico-radiologic and pathologic data of 4981 patients with HCC undergoing LT from the US Multicenter HCC Transplant Consortium (UMHTC) were analyzed to develop a REcurrent Liver cAncer Prediction ScorE (RELAPSE). Multivariable Fine and Gray competing risk analysis and machine learning algorithms (Random Survival Forest and Classification and Regression Tree models) identified variables to model HCC recurrence. RELAPSE was externally validated in 1160 HCC LT recipients from the European Hepatocellular Cancer Liver Transplant study group. Of 4981 UMHTC patients with HCC undergoing LT, 71.9% were within Milan criteria, 16.1% were initially beyond Milan criteria with 9.4% downstaged before LT, and 12.0% had incidental HCC on explant pathology. Overall and recurrence-free survival at 1, 3, and 5 years was 89.7%, 78.6%, and 69.8% and 86.8%, 74.9%, and 66.7%, respectively, with a 5-year incidence of HCC recurrence of 12.5% (median 16 months) and non-HCC mortality of 20.8%. A multivariable model identified maximum alpha-fetoprotein (HR = 1.35 per-log SD, 95% CI,1.22–1.50, p < 0.001), neutrophil-lymphocyte ratio (HR = 1.16 per-log SD, 95% CI,1.04–1.28, p < 0.006), pathologic maximum tumor diameter (HR = 1.53 per-log SD, 95% CI, 1.35–1.73, p < 0.001), microvascular (HR = 2.37, 95%–CI, 1.87–2.99, p < 0.001) and macrovascular (HR = 3.38, 95% CI, 2.41–4.75, p < 0.001) invasion, and tumor differentiation (moderate HR = 1.75, 95% CI, 1.29–2.37, p < 0.001; poor HR = 2.62, 95% CI, 1.54–3.32, p < 0.001) as independent variables predicting post-LT HCC recurrence (C-statistic = 0.78). Machine learning algorithms incorporating additional covariates improved prediction of recurrence (Random Survival Forest C-statistic = 0.81). Despite significant differences in European Hepatocellular Cancer Liver Transplant recipient radiologic, treatment, and pathologic characteristics, external validation of RELAPSE demonstrated consistent 2- and 5-year recurrence risk discrimination (AUCs 0.77 and 0.75, respectively). We developed and externally validated a RELAPSE score that accurately discriminates post-LT HCC recurrence risk and may allow for individualized post-LT surveillance, immunosuppression modification, and selection of high-risk patients for adjuvant therapies.

Objective: To compare minimally invasive (MILR) and open liver resections (OLRs) for hepatocellular carcinoma (HCC) in patients with metabolic syndrome (MS). Background: Liver resections for HCC on MS are associated with high perioperative morbidity and mortality. No data on the minimally invasive approach in this setting exist. Material and Methods: A multicenter study involving 24 institutions was conducted. Propensity scores were calculated, and inverse probability weighting was used to weight comparisons. Short-term and long-term outcomes were investigated. Results: A total of 996 patients were included: 580 in OLR and 416 in MILR. After weighing, groups were well matched. Blood loss was similar between groups (OLR 275.9±3.1 vs MILR 226±4.0, P=0.146). There were no significant differences in 90-day morbidity (38.9% vs 31.9% OLRs and MILRs, P=0.08) and mortality (2.4% vs 2.2% OLRs and MILRs, P=0.84). MILRs were associated with lower rates of major complications (9.3% vs 15.3%, P=0.015), posthepatectomy liver failure (0.6% vs 4.3%, P=0.008), and bile leaks (2.2% vs 6.4%, P=0.003); ascites was significantly lower at postoperative day 1 (2.7% vs 8.1%, P=0.002) and day 3 (3.1% vs 11.4%, P<0.001); hospital stay was significantly shorter (5.8±1.9 vs 7.5±1.7, P<0.001). There was no significant difference in overall survival and disease-free survival. Conclusions: MILR for HCC on MS is associated with equivalent perioperative and oncological outcomes to OLRs. Fewer major complications, posthepatectomy liver failures, ascites, and bile leaks can be obtained, with a shorter hospital stay. The combination of lower short-term severe morbidity and equivalent oncologic outcomes favor MILR for MS when feasible.

Background: Metabolic syndrome (MS) is rapidly growing as risk factor for HCC. Liver resection for HCC in patients with MS is associated with increased postoperative risks. There are no data on factors associated with postoperative complications. Aims: The aim was to identify risk factors and develop and validate a model for postoperative major morbidity after liver resection for HCC in patients with MS, using a large multicentric Western cohort. Materials and Methods: The univariable logistic regression analysis was applied to select predictive factors for 90 days major morbidity. The model was built on the multivariable regression and presented as a nomogram. Performance was evaluated by internal validation through the bootstrap method. The predictive discrimination was assessed through the concordance index. Results: A total of 1087 patients were gathered from 24 centers between 2001 and 2021. Four hundred and eighty-four patients (45.2%) were obese. Most liver resections were performed using an open approach (59.1%), and 743 (68.3%) underwent minor hepatectomies. Three hundred and seventy-six patients (34.6%) developed postoperative complications, with 13.8% major morbidity and 2.9% mortality rates. Seven hundred and thirteen patients had complete data and were included in the prediction model. The model identified obesity, diabetes, ischemic heart disease, portal hypertension, open approach, major hepatectomy, and changes in the nontumoral parenchyma as risk factors for major morbidity. The model demonstrated an AUC of 72.8% (95% CI: 67.2%–78.2%) (https://childb.shinyapps.io/NomogramMajorMorbidity90days/). Conclusions: Patients undergoing liver resection for HCC and MS are at high risk of postoperative major complications and death. Careful patient selection, considering baseline characteristics, liver function, and type of surgery, is key to achieving optimal outcomes.