Crossroads in Liver Transplantation: Is Artificial Intelligence the Key to Donor–Recipient Matching?

Liver transplantation outcomes have improved in recent years. However, with the emergence of expanded donor criteria, tools to better assist donor–recipient matching have become necessary. Most of the currently proposed scores based on conventional biostatistics are not good classifiers of a problem that is considered “unbalanced.” In recent years, the implementation of artificial intelligence in medicine has experienced exponential growth. Deep learning, a branch of artificial intelligence, may be the answer to this classification problem. The ability to handle a large number of variables with speed, objectivity, and multi-objective analysis is one of its advantages. Artificial neural networks and random forests have been the most widely used deep classifiers in this field. This review aims to give a brief overview of D–R matching and its evolution in recent years and how artificial intelligence may be able to provide a solution

Epigenetic prediction of response to anti-PD-1 treatment in non-small-cell lung cancer: a multicenter, retrospective analysis

Background: Anti-programmed death-1 (PD-1) treatment for advanced non-small-cell lung cancer (NSCLC) has improved the survival of patients. However, a substantial percentage of patients do not respond to this treatment. We examined the use of DNA methylation profiles to determine the efficacy of anti-PD-1 treatment in patients recruited with current stage IV NSCLC. Methods: In this multicentre study, we recruited adult patients from 15 hospitals in France, Spain, and Italy who had histologically proven stage IV NSCLC and had been exposed to PD-1 blockade during the course of the disease. The study structure comprised a discovery cohort to assess the correlation between epigenetic features and clinical benefit with PD-1 blockade and two validation cohorts to assess the validity of our assumptions. We first established an epigenomic profile based on a microarray DNA methylation signature (EPIMMUNE) in a discovery set of tumour samples from patients treated with nivolumab or pembrolizumab. The EPIMMUNE signature was validated in an independent set of patients. A derived DNA methylation marker was validated by a single-methylation assay in a validation cohort of patients. The main study outcomes were progression-free survival and overall survival. We used the Kaplan-Meier method to estimate progression-free and overall survival, and calculated the differences between the groups with the log-rank test. We constructed a multivariate Cox model to identify the variables independently associated with progression-free and overall survival. Findings: Between June 23, 2014, and May 18, 2017, we obtained samples from 142 patients: 34 in the discovery cohort, 47 in the EPIMMUNE validation cohort, and 61 in the derived methylation marker cohort (the T-cell differentiation factor forkhead box P1 [FOXP1]). The EPIMMUNE signature in patients with stage IV NSCLC treated with anti-PD-1 agents was associated with improved progression-free survival (hazard ratio [HR] 0·010, 95% CI 3·29 × 10 −4–0·0282; p=0·0067) and overall survival (0·080, 0·017–0·373; p=0·0012). The EPIMMUNE-positive signature was not associated with PD-L1 expression, the presence of CD8+ cells, or mutational load. EPIMMUNE-negative tumours were enriched in tumour-associated macrophages and neutrophils, cancer-associated fibroblasts, and senescent endothelial cells. The EPIMMUNE-positive signature was associated with improved progression-free survival in the EPIMMUNE validation cohort (0·330, 0·149–0·727; p=0·0064). The unmethylated status of FOXP1 was associated with improved progression-free survival (0·415, 0·209–0·802; p=0·0063) and overall survival (0·409, 0·220–0·780; p=0·0094) in the FOXP1 validation cohort. The EPIMMUNE signature and unmethylated FOXP1 were not associated with clinical benefit in lung tumours that did not receive immunotherapy. Interpretation: Our study shows that the epigenetic milieu of NSCLC tumours indicates which patients are most likely to benefit from nivolumab or pembrolizumab treatments. The methylation status of FOXP1 could be associated with validated predictive biomarkers such as PD-L1 staining and mutational load to better select patients who will experience clinical benefit with PD-1 blockade, and its predictive value should be evaluated in prospective studies

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

Anorectal melanoma as an unexpected diagnosis for a pigmented mass resembling a thrombosed hemorrhoid

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Short-term outcomes of robotic liver resection: An initial single-institution experience.

Liver surgery has traditionally been characterized by the complexity of its procedures and potentially high rates of morbidity and mortality in inexperienced hands. The robotic approach has gradually been introduced in liver surgery and has increased notably in recent years. However, few centers currently perform robotic liver surgery and experiences in robot-assisted surgical procedures continue to be limited compared to the laparoscopic approach. To analyze the outcomes and feasibility of an initial robotic liver program implemented in an experienced laparoscopic hepatobiliary center. A total of forty consecutive patients underwent robotic liver resection (da Vinci Xi, intuitive.com, United States) between June 2019 and January 2021. Patients were prospectively followed and retrospectively reviewed. Clinicopathological characteristics and perioperative and short-term outcomes were analyzed. Data are expressed as mean and standard deviation. The study was approved by the Institutional Review Board. The mean age of patients was 59.55 years, of which 18 (45%) were female. The mean body mass index was 29.41 kg/m². Nine patients (22.5%) were cirrhotic. Patients were divided by type of resection as follows: Ten segmentectomies, three wedge resections, ten left lateral sectionectomies, six bisegmentectomies (two V-VI bisegmentectomies and four IVb-V bisegmentectomies), two right anterior sectionectomies, five left hepatectomies and two right hepatectomies. Malignant lesions occurred in twenty-nine (72.5%) of the patients. The mean operative time was 258.11 min and two patients were transfused intraoperatively (5%). Inflow occlusion was used in thirty cases (75%) and the mean total clamping time was 32.62 min. There was a single conversion due to uncontrollable hemorrhage. Major postoperative complications (Clavien-Dindo > IIIb) occurred in three patients (7.5%) and mortality in one (2.5%). No patient required readmission to the hospital. The mean hospital stay was 5.6 d. Although robotic hepatectomy is a safe and feasible procedure with favorable short-term outcomes, it involves a demanding learning curve that requires a high level of training, skill and dexterity

Metabolomics as a tool to predict the risk of decompensation or liver related death in patients with compensated cirrhosis.

BACKGROUND AIMS Patients with compensated cirrhosis with clinically significant portal hypertension (CSPH: HVPG >10 mmHg) have a high risk of decompensation. HVPG is, however, an invasive procedure not available in all centers. The present study aims to assess whether metabolomics can improve the capacity of clinical models in predicting clinical outcome in these compensated patients. APPROACH RESULTS This is a nested study from the PREDESCI cohort (a RCT of non-selective beta blockers (NSBB) versus placebo in 201 patients with compensated cirrhosis and CSPH) including 167 patients for whom a blood sample was collected. A targeted metabolomic serum analysis, using UHPLC-MS, was performed. Metabolites underwent univariate time-to event cox regression analysis. Top ranked metabolites were selected using LogRank P-value to generate a stepwise cox model. Comparison between models was done using DeLong's test. Eighty-two patients with CSPH were randomized to NSBB and 85 to placebo. Thirty-three patients developed the main endpoint (decompensation/liver-related death). The model including HVPG, Child-Pugh and treatment received (HVPG/Clinical model) had a C-index of 0.748 [CI95% 0.664-0.827]. Addition of two metabolites, Ceramide (d18:1/22:0) and Methionine (HVPG/Clinical/Metabolite model) significantly improved model's performance (C-index of 0.808 [CI95% 0.735-0.882]; P=0.032). The combination of these two metabolites together with Child-Pugh and type of treatment received (Clinical/Metabolite model) had a C-Index of 0.785 [CI95% 0.710-0.860] not significantly different from the HVPG based models including or not metabolites. CONCLUSIONS In patients with compensated cirrhosis and CSPH, metabolomics improves the capacity of clinical models and achieves similar predictive capacity than models including HVPG

The NUTRAOLEOUM Study, a randomized controlled trial, for achieving nutritional added value for olive oils

Background: Virgin olive oil, a recognized healthy food, cannot be consumed in great quantities. We aim to assess in humans whether an optimized virgin olive oil with high phenolic content (OVOO, 429 mg/Kg) and a functional one (FOO), both rich in phenolic compounds (429 mg/Kg) and triterpenic acids (389 mg/kg), could provide health benefits additional to those supplied a by a standard virgin olive oil (VOO). Methods/design: A randomized, double-blind, crossover, controlled study will be conducted. Healthy volunteers (aged 20 to 50) will be randomized into one of three groups of daily raw olive oil consumption: VOO, OVOO, and FOO (30 mL/d). Olive oils will be administered over 3-week periods preceded by 2-week washout ones. The main outcomes will be markers of lipid and DNA oxidation, inflammation, and vascular damage. A bioavailability and dose-response study will be nested within this sustained- consumption one. It will be made up of 18 volunteers and be performed at two stages after a single dose of each olive oil. Endothelial function and nitric oxide will be assessed at baseline and at 4 h and 6 h after olive oil single dose ingestion. Discussion: For the first time the NUTRAOLEUM Study will provide first level evidence on the health benefits in vivo in humans of olive oil triterpenes (oleanolic and maslinic acid) in addition to their bioavailability and disposition

Switching TNF antagonists in patients with chronic arthritis: An observational study of 488 patients over a four-year period

The objective of this work is to analyze the survival of infliximab, etanercept and adalimumab in patients who have switched among tumor necrosis factor (TNF) antagonists for the treatment of chronic arthritis. BIOBADASER is a national registry of patients with different forms of chronic arthritis who are treated with biologics. Using this registry, we have analyzed patient switching of TNF antagonists. The cumulative discontinuation rate was calculated using the actuarial method. The log-rank test was used to compare survival curves, and Cox regression models were used to assess independent factors associated with discontinuing medication. Between February 2000 and September 2004, 4,706 patients were registered in BIOBADASER, of whom 68% had rheumatoid arthritis, 11% ankylosing spondylitis, 10% psoriatic arthritis, and 11% other forms of chronic arthritis. One- and two-year drug survival rates of the TNF antagonist were 0.83 and 0.75, respectively. There were 488 patients treated with more than one TNF antagonist. In this situation, survival of the second TNF antagonist decreased to 0.68 and 0.60 at 1 and 2 years, respectively. Survival was better in patients replacing the first TNF antagonist because of adverse events (hazard ratio (HR) for discontinuation 0.55 (95% confidence interval (CI), 0.34-0.84)), and worse in patients older than 60 years (HR 1.10 (95% CI 0.97-2.49)) or who were treated with infliximab (HR 3.22 (95% CI 2.13-4.87)). In summary, in patients who require continuous therapy and have failed to respond to a TNF antagonist, replacement with a different TNF antagonist may be of use under certain situations. This issue will deserve continuous reassessment with the arrival of new medications. © 2006 Gomez-Reino and Loreto Carmona; licensee BioMed Central Ltd