Rompianesi, Gianluca

Objective: To establish benchmark cutoffs for robotic liver resection (R-LR), encompassing both major and minor resections, and to determine the impact of patient selection on outcomes. Background: R-LR is a key advancement in minimally invasive liver surgery but lacks standardized benchmarks, especially for minor resections. While guidelines endorse R-LR, its role in optimizing outcomes remains unclear. This study establishes the first benchmarks for R-LR, enabling comparisons across surgical modalities and refining patient selection. Methods: This retrospective, multicenter study analyzed consecutive adult patients undergoing R-LR at 30 international centers (2020–2023). Benchmark centers had an annual case volume of ≥15 R-LR. Benchmark criteria included ASA ≤2, no major comorbidities, no prior liver resections, and Child-Pugh A status. Benchmark cutoffs for 14 key outcomes were set at the 50th and 75th percentiles of median values across benchmark centers. Multivariable logistic regression identified predictors of textbook outcomes. Results: Eighteen high-volume centers contributed 4028 cases with 2632 (65.3%) meeting benchmark criteria. Malignancy was the indication in 29.6%, most commonly hepatocellular carcinoma followed by colorectal liver metastases. Major liver resection was performed in 42.6%. The distribution of Iwate difficulty scores was low (25.4%), intermediate (53.9%), advanced (15.9%), and expert (4.9%). Benchmark cutoffs were established for minor and major resection, and stratified by Iwate low (0-3), intermediate (4-6) and high (7-12): Open conversion (≤6.5% minor, ≤10.5% major), major complications within 90 days (≤5.2% minor, ≤16.7% major), R1 resection (≤9.2% minor, ≤6.7% major). Benchmark cases performed at low-volume centers were able to achieve outcomes within the corresponding benchmark cutoffs. In fact, patient selection reflected by the proportion of benchmark patients, rather than case volume, was associated with textbook outcomes. Conclusions: This study defines R-LR benchmarks, emphasizing patient selection over center volume for optimal outcomes. Benchmark cutoffs guide training and support the expansion of R-LR.

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.