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(1) Background: Liver metastases (LM) are the leading cause of death in colorectal cancer (CRC) patients. Despite advancements, relapse rates remain high and current prognostic nomograms lack accuracy. Our objective is to develop an interpretable neoadjuvant algorithm based on mathematical models to accurately predict individual risk, ensuring mathematical transparency and auditability. (2) Methods: We retrospectively evaluated 86 CRC patients with LM treated with neoadjuvant systemic therapy followed by complete surgical resection. A comprehensive analysis of 155 individual patient variables was performed. Logistic regression (LR) was utilized to develop the predictive model for relapse risk through significance testing and ANOVA analysis. Due to data limitations, gradient boosting machine (GBM) and synthetic data were also used. (3) Results: The model was based on data from 74 patients (12 were excluded). After a median follow-up of 58 months, 5-year relapse-free survival (RFS) rate was 33% and 5-year overall survival (OS) rate was 60.7%. Fifteen key variables were used to train the GBM model, which showed promising accuracy (0.82), sensitivity (0.59), and specificity (0.96) in predicting relapse. Similar results were obtained when external validation was performed as well. (4) Conclusions: This model offers an alternative for predicting individual relapse risk, aiding in personalized adjuvant therapy and follow-up strategies.

(1) Background: The liver-first approach may be indicated for colorectal cancer patients with synchronous liver metastases to whom preoperative chemotherapy opens a potential window in which liver resection may be undertaken. This study aims to present the data of feasibility and short-term outcomes in the liver-first approach. (2) Methods: A prospective observational study was performed in Spanish hospitals that had a medium/high-volume of HPB surgeries from 1 June 2019 to 31 August 2020. (3) Results: In total, 40 hospitals participated, including a total of 2288 hepatectomies, 1350 for colorectal liver metastases, 150 of them (11.1%) using the liver-first approach, 63 (42.0%) in hospitals performing p = 0.0213). In 81.1% of the cases, the primary tumor was in the rectum or sigmoid colon. In total, 40% of the patients underwent major hepatectomies. The surgical approach was open surgery in 87 (58.0%) patients. Resection margins were R0 in 78.5% of the patients. In total, 40 (26.7%) patients had complications after the liver resection and 36 (27.3%) had complications after the primary resection. One-hundred and thirty-two (89.3%) patients completed the therapeutic regime. (4) Conclusions: There were no differences in the surgical outcomes between the centers performing

Radioembolization (RE) may help local control and achieve tumor reduction while hypertrophies healthy liver and provides a test of time. For liver transplant (LT) candidates, it may attain downstaging for initially non-candidates and bridging during the waitlist. Methods: Patients diagnosed with HCC and ICC treated by RE with further liver resection (LR) or LT between 2005–2020 were included. All patients selected were discarded for the upfront surgical approach for not accomplishing oncological or surgical safety criteria after a multidisciplinary team assessment. Data for clinicopathological details, postoperative, and survival outcomes were retrospectively reviewed from a prospectively maintained database. Results: A total of 34 patients underwent surgery following RE (21 LR and 13 LT). Clavien–Dindo grade III-IV complications and mortality rates were 19.0% and 9.5% for LR and 7.7% and 0% for LT, respectively. After RE, for HCC and ICC patients in the LR group, 10-year OS rates were 57% and 60%, and 10-year DFS rates were 43.1% and 60%, respectively. For HCC patients in the LT group, 10-year OS and DFS rates from RE were 51.3% and 43.3%, respectively. Conclusion: Liver resection after RE is safe and feasible with optimal short-term outcomes. Patients diagnosed with unresectable or high biological risk HCC or ICC, treated with RE, and rescued by LR may achieve optimal global and DFS rates. On the other hand, bridging or downstaging strategies to LT with RE in HCC patients show adequate recurrence rates as well as long-term survival.

Whether albumin and bilirubin levels, platelet counts, ALBI, and ALPlat scores could be useful for the assessment of permanent liver functional deterioration after repeat liver resection was examined, and the deterioration after laparoscopic procedure was evaluated. For 657 patients with liver resection of segment or less in whom results of plasma albumin and bilirubin levels and platelet counts before and 3 months after surgery could be retrieved, liver functional indicators were compared before and after surgery. There were 268 patients who underwent open repeat after previous open liver resection, and 224 patients who underwent laparoscopic repeat after laparoscopic liver resection. The background factors, liver functional indicators before and after surgery and their changes were compared between both groups. Plasma levels of albumin (p = 0.006) and total bilirubin (p = 0.01) were decreased, and ALBI score (p = 0.001) indicated worse liver function after surgery. Laparoscopic group had poorer preoperative performance status and liver function. Changes of liver functional values before and after surgery and overall survivals were similar between laparoscopic and open groups. Plasma levels of albumin and bilirubin and ALBI score could be the indicators for permanent liver functional deterioration after liver resection. Laparoscopic group with poorer conditions showed the similar deterioration of liver function and overall survivals to open group.

Less morbidity is considered among the advantages of laparoscopic liver resection (LLR) for HCC patients. However, our previous international, multi-institutional, propensity score-based study of emerging laparoscopic repeat liver resection (LRLR) failed to prove this advantage. We hypothesize that these results may be since the study included complex LRLR cases performed during the procedure’s developing stage. To examine it, subgroup analysis based on propensity score were performed, defining the proximity of the tumors to major vessels as the indicator of complex cases. Among 1582 LRLR cases from 42 international high-volume liver surgery centers, 620 cases without the proximity to major vessels (more than 1 cm far from both first–second branches of Glissonian pedicles and major hepatic veins) were selected for this subgroup analysis. A propensity score matching (PSM) analysis was performed based on their patient characteristics, preoperative liver function, tumor characteristics and surgical procedures. One hundred and fifteen of each patient groups of LRLR and open repeat liver resection (ORLR) were earned, and the outcomes were compared. Backgrounds were well-balanced between LRLR and ORLR groups after matching. With comparable operation time and long-term outcome, less blood loss (283.3±823.0 vs. 603.5±664.9 mL, p = 0.001) and less morbidity (8.7 vs. 18.3 %, p = 0.034) were shown in LRLR group than ORLR. Even in its worldwide developing stage, LRLR for HCC patients could be beneficial in blood loss and morbidity for the patients with less complexity in surgery.

Background: Although surgical resection is the only potentially curative treatment for pancreatic cancer (PC), long-term outcomes of this treatment remain poor. The aim of this study is to describe the feasibility of a neoadjuvant treatment with induction polychemotherapy (IPCT) followed by chemoradiation (CRT) in resectable PC, and to develop a machine-learning algorithm to predict risk of relapse. Methods: Forty patients with resectable PC treated in our institution with IPCT (based on mFOLFOXIRI, GEMOX or GEMOXEL) followed by CRT (50 Gy and concurrent Capecitabine) were retrospectively analyzed. Additionally, clinical, pathological and analytical data were collected in order to perform a 2-year relapse-risk predictive population model using machine-learning techniques. Results: A R0 resection was achieved in 90% of the patients. After a median follow-up of 33.5 months, median progression-free survival (PFS) was 18 months and median overall survival (OS) was 39 months. The 3 and 5-year actuarial PFS were 43.8% and 32.3%, respectively. The 3 and 5-year actuarial OS were 51.5% and 34.8%, respectively. Forty-percent of grade 3-4 IPCT toxicity, and 29.7% of grade 3 CRT toxicity were reported. Considering the use of granulocyte colony-stimulating factors, the number of resected lymph nodes, the presence of perineural invasion and the surgical margin status, a logistic regression algorithm predicted the individual 2-year relapse-risk with an accuracy of 0.71 (95% confidence interval [CI] 0.56−0.84, p = 0.005). The model-predicted outcome matched 64% of the observed outcomes in an external dataset. Conclusion: An intensified multimodal neoadjuvant approach (IPCT + CRT) in resectable PC is feasible, with an encouraging long-term outcome. Machine-learning algorithms might be a useful tool to predict individual risk of relapse. A small sample size and therapy heterogeneity remain as potential limitations.

(1) Background: Liver metastases (LM) are the leading cause of death in colorectal cancer (CRC) patients. Despite advancements, relapse rates remain high and current prognostic nomograms lack accuracy. Our objective is to develop an interpretable neoadjuvant algorithm based on mathematical models to accurately predict individual risk, ensuring mathematical transparency and auditability. (2) Methods: We retrospectively evaluated 86 CRC patients with LM treated with neoadjuvant systemic therapy followed by complete surgical resection. A comprehensive analysis of 155 individual patient variables was performed. Logistic regression (LR) was utilized to develop the predictive model for relapse risk through significance testing and ANOVA analysis. Due to data limitations, gradient boosting machine (GBM) and synthetic data were also used. (3) Results: The model was based on data from 74 patients (12 were excluded). After a median follow-up of 58 months, 5-year relapse-free survival (RFS) rate was 33% and 5-year overall survival (OS) rate was 60.7%. Fifteen key variables were used to train the GBM model, which showed promising accuracy (0.82), sensitivity (0.59), and specificity (0.96) in predicting relapse. Similar results were obtained when external validation was performed as well. (4) Conclusions: This model offers an alternative for predicting individual relapse risk, aiding in personalized adjuvant therapy and follow-up strategies.