López‐López, Víctor

Objective: To evaluate the institutional learning curve of robotic liver resection (RLR), its association with surgical complexity and outcomes in an international multicenter cohort. Summary of Background Data: RLR is increasingly adopted worldwide, but the dynamics of the learning process and its impact on surgical outcomes remain poorly defined. Methods: This international, multicenter, retrospective cohort study included consecutive patients who underwent RLR between 06/2013 and 12/2024 across 22 expert centers. Based on the first 150 cases at each center, three phases were used to define the learning curve: operative time for competency, major complications for proficiency, and textbook outcome for mastery. Risk-adjusted generalized additive models were used to assess the learning process. Benchmark performance was compared to international reference values. Results: Among 2,331 patients, the most common indications were hepatocellular carcinoma (36%), benign lesions (23%) and colorectal liver metastases (21%). Operative time decreased after achieving competency (case #62), from 240 to 220 minutes ( P <0.001). Major morbidity reached a plateau during the proficiency phase (cases #63–138; 9% vs. 11%, P =0.144), while progression to mastery (cases #139–150) was associated with a higher rate of textbook outcome (76% vs. 87%, P =0.021). In contrast, conversion (5.1% vs. 4.9% vs. 2%), bile leak (4.0% vs. 5.3% vs. 3.8%), and 90-day mortality (0.7% vs. 0.9% vs. 0.9%) remained low and stable across all learning phases. Importantly, benchmark criteria for operative time, hospital stay, and textbook outcome were met across all complexity groups, including during the early learning phase. Conclusions: Robotic liver surgery shows progressive outcome improvement with early achievement of benchmark-level results and stable performance across increasing complexity. These findings indicate that, in experienced centers, RLR can be safely implemented and integrated into clinical practice, supporting its key role in modern hepatobiliary surgery.

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.

Background: In patients with neuroendocrine liver metastasis (NELM), liver transplantation (LT) is an alternative to liver resection (LR), although the choice of therapy remains controversial. In this multicenter study, we aim to provide novel insight in this dispute. Methods: Following a systematic literature search, 15 large international centers were contacted to provide comprehensive data on their patients after LR or LT for NELM. Survival analyses were performed with the Kaplan-Meier method, while multivariable Cox regression served to identify factors influencing survival after either transplantation or resection. Inverse probability weighting and propensity score matching was used for analyses with balanced and equalized baseline characteristics. Results: Overall, 455 patients were analyzed, including 230 after LR and 225 after LT, with a median follow-up of 97 months [95% confidence interval (CI): 85–110 months]. Multivariable analysis revealed G3 grading as a negative prognostic factor for LR [hazard ratio (HR)=2.22, 95% CI: 1.04–4.77, P=0.040], while G2 grading (HR=2.52, 95% CI: 1.15–5.52, P=0.021) and LT outside Milan criteria (HR=2.40, 95% CI: 1.16–4.92, P=0.018) were negative prognostic factors in transplanted patients. Inverse probability-weighted multivariate analyses revealed a distinct survival benefit after LT. Matched patients presented a median overall survival (OS) of 197 months (95% CI: 143–not reached) and a 73% 5-year OS after LT, and 119 months (95% CI: 74–133 months) and a 52.8% 5-year OS after LR (HR=0.59, 95% CI: 0.3–0.9, P=0.022). However, the survival benefit after LT was lost if patients were transplanted outside Milan criteria. Conclusions: This multicentric study in patients with NELM demonstrates a survival benefit of LT over LR. This benefit depends on adherence to selection criteria, in particular low-grade tumor biology and Milan criteria, and must be balanced against potential risks of LT.

Objective: To define benchmark values for liver transplantation (LT) in patients with perihilar cholangiocarcinoma (PHC) enabling unbiased comparisons. Background: Transplantation for PHC is used with reluctance in many centers and even contraindicated in several countries. Although benchmark values for LT are available, there is a lack of specific data on LT performed for PHC. Methods: PHC patients considered for LT after Mayo-like protocol were analyzed in 17 reference centers in 2 continents over the recent 5-year period (2014–2018). The minimum follow-up was 1 year. Benchmark patients were defined as operated at high-volume centers (≥50 overall LT/year) after neoadjuvant chemoradiotherapy, with a tumor diameter <3 cm, negative lymph nodes, and with the absence of relevant comorbidities. Benchmark cutoff values were derived from the 75th to 25th percentiles of the median values of all benchmark centers. Results: One hundred thirty-four consecutive patients underwent LT after completion of the neoadjuvant treatment. Of those, 89.6% qualified as benchmark cases. Benchmark cutoffs were 90-day mortality ≤5.2%; comprehensive complication index at 1 year of ≤33.7; grade ≥3 complication rates ≤66.7%. These values were better than benchmark values for other indications of LT. Five-year disease-free survival was largely superior compared with a matched group of nodal negative patients undergoing curative liver resection (n=106) (62% vs 32%, P<0.001). Conclusion: This multicenter benchmark study demonstrates that LT offers excellent outcomes with superior oncological results in early stage PHC patients, even in candidates for surgery. This provocative observation should lead to a change in available therapeutic algorithms for PHC.