Comparison of FIB-4 Index and Child-Pugh Score in Predicting the Outcome of Hepatic Resection for Hepatocellular Carcinoma

Significance of Prediction Models for Post-Hepatectomy Liver Failure Based on Type IV Collagen 7s Domain in Patients with Hepatocellular Carcinoma

Background: Previous studies have attempted to establish predictive models for post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC) undergoing liver resection. However, a versatile and useful predictive model for PHLF remains to be developed. Therefore, we aimed to develop predictive models for PHLF based on type IV collagen 7s domain (7s collagen) in patients with HCC. Methods: We retrospectively collected data from 972 patients with HCC who had undergone initial curative liver resection between February 2000 and December 2020 at our hospital. Multivariate logistic regression analysis using a restricted cubic spline was performed to evaluate the effect of 7s collagen on the incidence of PHLF. A nomogram was developed based on 7s collagen. Results: PHLF grades B or C were identified in 104 patients (11%): 98 (10%) and 6 (1%) PHLF grades B and C, respectively. Multivariate logistic regression analysis revealed that the preoperative serum level of 7s collagen was significantly associated with a proportional increase in the risk of PHLF, which was confirmed in both laparoscopic and open liver resections. A nomogram was developed based on 7s collagen, with a concordance index of 0.768. The inclusion of 7s collagen values in the predictive model increased the predictive accuracy. Conclusion: The findings highlight the efficacy of the serum level of 7s collagen as a predictive factor for PHLF. Our novel nomogram using 7s collagen may be useful for predicting the risk of PHLF.

Artificial Intelligence in Perioperative Planning and Management of Liver Resection

Artificial intelligence (AI) is a speciality within computer science that deals with creating systems that can replicate the intelligence of a human mind and has problem-solving abilities. AI includes a diverse array of techniques and approaches such as machine learning, neural networks, natural language processing, robotics, and expert systems. An electronic literature search was conducted using the databases of "PubMed" and "Google Scholar". The period for the search was from 2000 to June 2023. The search terms included "artificial intelligence", "machine learning", "liver cancers", "liver tumors", "hepatectomy", "perioperative" and their synonyms in various combinations. The search also included all MeSH terms. The extracted articles were further reviewed in a step-wise manner for identification of relevant studies. A total of 148 articles were identified after the initial literature search. Initial review included screening of article titles for relevance and identifying duplicates. Finally, 65 articles were reviewed for this review article. The future of AI in liver cancer planning and management holds immense promise. AI-driven advancements will increasingly enable precise tumour detection, location, and characterisation through enhanced image analysis. ML algorithms will predict patient-specific treatment responses and complications, allowing for tailored therapies. Surgical robots and AI-guided procedures will enhance the precision of liver resections, reducing risks and improving outcomes. AI will also streamline patient monitoring, better hemodynamic management, enabling early detection of recurrence or complications. Moreover, AI will facilitate data-driven research, accelerating the development of novel treatments and therapies. Ultimately, AI's integration will revolutionise liver cancer care, offering personalised, efficient and effective solutions, improving patients' quality of life and survival rates.

A novel nomogram for predicting microvascular invasion in hepatocellular carcinoma

INTRODUCTION AND OBJECTIVES

In hepatocellular carcinoma (HCC), the prognosis of patients with microvascular invasion (MVI) is poor. Therefore, in this study, we established and evaluated the performance of a novel nomogram to predict MVI in patients with HCC.

MATERIALS AND METHODS

We retrospectively obtained clinical data of 497 patients with HCC who underwent hepatectomy at Liaoning Cancer Hospital from November 1, 2018, to November 4, 2021. The patients (n = 497) were randomized in a 7:3 ratio into the training cohort (TC, n = 349) and the validation cohort (VC, n = 148). We performed Least Absolute Shrinkage and Selection Operator (LASSO) and univariate as well as multivariate logistic regression analyses (ULRA, MRLA) on patients in the TC to identify factors independently predicting MVI.

RESULTS

Preoperative FIB-4, AFU, AFP levels, liver cirrhosis, and non-smooth tumor margin were independent risk factors for preoperative MVI prediction. The C-index of the TC, VC, and the entire cohort was 0.846, 0.786, and 0.829, respectively. The calibration curves demonstrated the outstanding agreement between predicted MVI incidences by our model and the actual MVI risk. Decision curve analysis (DCA) confirmed the significance of our predictive model in clinical settings. The Kaplan-Meier (KM) survival curve showed that the recurrence-free survival (RFS) and overall survival (OS) of patients in the high-MVI risk group were poor compared to those in the low-MVI risk group.

CONCLUSIONS

We constructed and evaluated the performance of the novel nomogram for predicting MVI risk. Our predictive model could adequately predict MVI risk and aid clinicians in selecting appropriate therapeutic strategies for patients.

Current status of preoperative risk assessment for posthepatectomy liver failure in patients with hepatocellular carcinoma

Liver resection is an effective therapeutic option for patients with hepatocellular carcinoma. However, posthepatectomy liver failure (PHLF) remains a major cause of hepatectomy-related mortality, and the accurate prediction of PHLF based on preoperative assessment of liver functional reserve is a critical issue. The definition of PHLF proposed by the International Study Group for Liver Surgery has gained acceptance as a standard grading criterion. Liver function can be estimated using a variety of parameters, including routine blood biochemical examinations, clinical scoring systems, dynamic liver function tests, liver stiffness and fibrosis markers, and imaging studies. The Child-Pugh score and model for end-stage liver disease scores are conventionally used for estimating liver decompensation, although the alternatively developed albumin-bilirubin score shows superior performance for predicting hepatic dysfunction. Indocyanine green clearance, a dynamic liver function test mostly used in Japan and other Asian countries, serves as a quantitative estimation of liver function reserve and helps determine indications for surgical procedures according to the estimated risk of PHLF. In an attempt to improve predictive accuracy, specific evaluation of liver fibrosis and portal hypertension has gained popularity, including liver stiffness measurements using ultrasonography or magnetic resonance elastography, as well as noninvasive fibrosis markers. Imaging modalities, including Tc-99m-labeled galactosyl serum albumin scintigraphy and gadolinium-enhanced magnetic resonance imaging, are used for preoperative evaluation in combination with liver volume. This review aims to provide an overview of the usefulness of current options for the preoperative assessment of liver function in predicting PHLF.

Tumor burden score-AFP-albumin-bilirubin grade score predicts the survival of patients with hepatocellular carcinoma after liver resection

PURPOSE

There is little information regarding the overall survival (OS) predictive ability of the combination of tumor burden score (TBS), α-fetoprotein (AFP), and albumin-bilirubin (ALBI) grade for patients with hepatocellular carcinoma (HCC). Here, we aimed to develop a model including TBS, AFP, and ALBI grade to predict HCC patient OS following liver resection.

METHODS

Patients (N = 1556) from six centers were randomly divided 1:1 into training and validation sets. The X-Tile software was used to determine the optimal cutoff values. The time-dependent area under the receiver operating characteristic curve (AUROC) was calculated to assess the prognostic ability of the different models.

RESULTS

In the training set, tumor differentiation, TBS, AFP, ALBI grade, and Barcelona Clinic Liver Cancer (BCLC) stage were independently related to OS. According to the coefficient values of TBS, AFP, and ALBI grade, we developed the TBS-AFP-ALBI (TAA) score using a simplified point system (0, 2 for low/high TBS, 0, 1 for low/high AFP and 0,1 for ALBI grade 1/2). Patients were further divided into low TAA (TAA ≤ 1), medium TAA (TAA = 2-3), and high TAA (TAA= 4) groups. TAA scores (low: referent; medium, HR = 1.994, 95% CI = 1.492-2.666; high, HR = 2.413, 95% CI = 1.630-3.573) were independently associated with patient survival in the validation set. The TAA scores showed higher AUROCs than BCLC stage for the prediction of 1-, 3-, and 5-year OS in both the training and validation sets.

CONCLUSION

TAA is a simple score that has better OS prediction performance than the BCLC stage in predicting OS for HCC patients after liver resection.

Predicting Post-Hepatectomy Liver Failure in HCC Patients: A Review of Liver Function Assessment Based on Laboratory Tests Scores

The assessment of liver function is crucial in predicting the risk of post-hepatectomy liver failure (PHLF) in patients undergoing liver resection, especially in cases of hepatocellular carcinoma (HCC) which is often associated with cirrhosis. There are currently no standardized criteria for predicting the risk of PHLF. Blood tests are often the first- and least invasive expensive method for assessing hepatic function. The Child-Pugh score (CP score) and the Model for End Stage Liver Disease (MELD) score are widely used tools for predicting PHLF, but they have some limitations. The CP score does not consider renal function, and the evaluation of ascites and encephalopathy is subjective. The MELD score can accurately predict outcomes in cirrhotic patients, but its predictive capabilities diminish in non-cirrhotic patients. The albumin-bilirubin score (ALBI) is based on serum bilirubin and albumin levels and allows the most accurate prediction of PHLF for HCC patients. However, this score does not consider liver cirrhosis or portal hypertension. To overcome this limitation, researchers suggest combining the ALBI score with platelet count, a surrogate marker of portal hypertension, into the platelet-albumin-bilirubin (PALBI) grade. Non-invasive markers of fibrosis, such as FIB-4 and APRI, are also available for predicting PHLF but they focus only on cirrhosis related aspects and are potentially incomplete in assessing the global liver function. To improve the predictive power of the PHLF of these models, it has been proposed to combine them into a new score, such as the ALBI-APRI score. In conclusion, blood test scores may be combined to achieve a better predictive value of PHLF. However, even if combined, they may not be sufficient to evaluate liver function and to predict PHLF; thus, the inclusion of dynamic and imaging tests such as liver volumetry and ICG r15 may be helpful to potentially improve the predictive capacity of these models.

Prognostic Significance of Hemoglobin, Albumin, Lymphocyte and Platelet (HALP) Score in Hepatocellular Carcinoma

Purpose

HALP score consisting of hemoglobin content, albumin content, lymphocyte count, and platelet count can comprehensively evaluate the inflammatory response and nutritional status. Many researchers have indicated that the HALP score is an effective predictor of the overall prognosis of various tumors. However, there is no relevant research to suggest whether the HALP score can predict the prognosis of patients with hepatocellular carcinoma (HCC).

Patients and Methods

We retrospectively analyzed 273 HCC patients who underwent surgical resection. Hemoglobin content, albumin content, lymphocyte count, and platelet count in peripheral blood were measured for each patient. The relationship between the HALP score and overall survival (OS) was investigated.

Results

With a mean of 56.69 ± 1.25 months follow-up, the 1-, 3-, and 5-year OS was 98.9%, 76.9%, and 55.3% for all patients, respectively. HALP scores (HR=1.708, 95% CI=1.192-2.448, P=0.004) were significant independent risk factors of OS. The 1-, 3-, and 5-year OS were 99.3%, 84.3%, and 63.4% for patients with high HALP scores; and 98.6%, 69.8%, and 47.5% for patients with low HALP scores, respectively (P=0.018). In TNM I-II stage patients, compared with high HALP scores, low HALP scores have worse OS (P=0.039). In AFP positive patients, compared with high HALP scores, low HALP scores have worse OS (P=0.042).

Conclusion

Our research showed the preoperative HALP score is an independent predictive factor of overall prognosis, and a low HALP score indicates a worse prognosis in HCC patients who underwent surgical resection.

The Prognostic Impact of ABO Blood Group in Hepatocellular Carcinoma Following Hepatectomy

BACKGROUND/PURPOSE

The effect of the ABO blood group on the survival of patients with hepatocellular carcinoma (HCC) is unclear. The aim of the present study is to determine the prognostic impact of ABO blood types on the survival of a Japanese population of patients with HCC who underwent surgical resection.

METHODS

Patients with HCC (n = 480) who underwent an R0 resection between 2010 and 2020 were retrospectively analyzed. Survival outcomes were investigated according to ABO blood type (A, B, O, or AB). Outcomes for type A (n = 173) and non-type A (n = 173) groups after surgery were compared using 1-to-1 propensity score matching to control for variables.

RESULTS

In the study cohort, 173 (36.0%), 133 (27.7%), 131 (27.3%), and 43 (9.0%) of participants had Type A, O, B, and AB, respectively. Type A and non-type A patients were successfully matched based on liver function and tumor characteristics. Recurrence-free survival (RFS; hazard ratio [HR] 0.75, 95% confidence interval [Cl] 0.58-0.98, p = 0.038) and overall survival (OS; HR: 0.67, 95% Cl: 0.48-0.95, p = 0.023) for patients with blood type A were both significantly decreased relative to non-type A patients. Cox proportional hazard analysis demonstrated that patients with HCC who have blood type A had a worse prognosis than those with non-type A blood.

CONCLUSION

ABO blood type may have a prognostic impact on patients with HCC after hepatectomy. Blood type A is an independent unfavorable prognostic factor for recurrence-free and overall survival (RFS and OS) after hepatectomy.

Predicting Post-hepatectomy Liver Failure Preoperatively for Child-Pugh A5 Hepatocellular Carcinoma Patients by Liver Stiffness

BACKGROUND

Post-hepatectomy liver failure (PHLF) represents the major source of mortality after liver resection (LR) in hepatocellular carcinoma (HCC) patients. Child-Pugh (CP) score 5 is always considered to indicate a normal liver function but represents a heterogeneous population with a considerable number suffering from PHLF. The present study aimed to access the ability of liver stiffness (LS) measured by two-dimensional shear wave elastography (2D-SWE) to predict PHLF in HCC patients with a CP score of 5.

METHODS

From August 2018 to May 2021, 146 HCC patients with a CP score of 5 who underwent LR were reviewed. The patients were randomly divided into training (n = 97) and validation (n = 49) groups. Logistic analyses were conducted for the risk factors and a linear model was built to predict the development of PHLF. The discrimination and calibration were assessed in the training and validation cohorts by the areas under the receiver operating characteristic curve (AUC).

RESULTS

Analyses revealed that the minimum of LS (Emin) higher than 8.05 (p = 0.006, OR = 4.59) and future liver remnant / estimated total liver volume (FLR/eTLV) (p < 0.001, OR < 0.01) were independent predictors of PHLF in HCC patients with CP score 5, and the AUC calculated by the model based on them for differentiation of PHLF in the training and validation group was 0.78 and 0.76, respectively.

CONCLUSION

LS was associated with the development of PHLF. A model combining Emin and FLR/eTLV showed proper ability in predicting PHLF in HCC patients with a CP score of 5.

The preoperative M2BPGi score predicts operative difficulty and the incidence of postoperative complications in laparoscopic liver resection

BACKGROUND

Liver fibrosis or cirrhosis frequently makes parenchymal transection more difficult, but the difficulty score of laparoscopic liver resection (LLR), including the IWATE criteria, does not include a factor related to liver fibrosis. Therefore, this study aimed to evaluate M2BPGi as a predictor of the difficulty of parenchymal transection and the incidence of postoperative complications in LLR.

METHODS

Data from 54 patients who underwent laparoscopic partial liver resection (LLR-P) and 24 patients who underwent laparoscopic anatomical liver resection between 2017 and 2019 in our institution were retrospectively analyzed. All cases were classified according to M2BPGi scores, and reserve liver function, intraoperative blood loss, and postoperative complications were compared among these groups.

RESULTS

Sixteen cases (29.6%) were M2BPGi negative (cut-off index < 1.0), 25 cases (46.3%) were 1+ (1.0 ≤ cut-off index < 3.0), and 13 cases (24.1%) were 2+ (cut-off index ≥ 3.0). M2BPGi-positive cases had significantly worse hepatic reserve function (K-ICG: 0.16 vs 0.14 vs 0.08, p < 0.0001). Intraoperative bleeding was significantly greater in M2BPGi-positive cases [50 ml vs 150 ml vs 200 ml, M2BPGi (-) or (1+) vs M2BPGi (2+), p = 0.045]. Postoperative complications (Clavien-Dindo ≥ II) were significantly more frequent in M2BPGi-positive cases [0% vs 4% vs 33%, M2BPGi (-) or (1+) vs M2BPGi (2+), p = 0.001].

CONCLUSION

M2BPGi could predict surgical difficulty and complications in LLR-P. In particular, it might be better not to select M2BPGi (2+) cases as teaching cases because of the massive bleeding during parenchymal transection.

Machine learning prediction model for post- hepatectomy liver failure in hepatocellular carcinoma: A multicenter study

Introduction

Post-hepatectomy liver failure (PHLF) is one of the most serious complications and causes of death in patients with hepatocellular carcinoma (HCC) after hepatectomy. This study aimed to develop a novel machine learning (ML) model based on the light gradient boosting machines (LightGBM) algorithm for predicting PHLF.

Methods

A total of 875 patients with HCC who underwent hepatectomy were randomized into a training cohort (n=612), a validation cohort (n=88), and a testing cohort (n=175). Shapley additive explanation (SHAP) was performed to determine the importance of individual variables. By combining these independent risk factors, an ML model for predicting PHLF was established. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, and decision curve analyses (DCA) were used to evaluate the accuracy of the ML model and compare it to that of other noninvasive models.

Results

The AUCs of the ML model for predicting PHLF in the training cohort, validation cohort, and testing cohort were 0.944, 0.870, and 0.822, respectively. The ML model had a higher AUC for predicting PHLF than did other non-invasive models. The ML model for predicting PHLF was found to be more valuable than other noninvasive models.

Conclusion

A novel ML model for the prediction of PHLF using common clinical parameters was constructed and validated. The novel ML model performed better than did existing noninvasive models for the prediction of PHLF.

Interim efficacy and safety of PD-1 inhibitors in preventing recurrence of hepatocellular carcinoma after interventional therapy

INTRODUCTION

Locoregional interventional therapy including transcatheter arterial chemoembolization (TACE) and ablation are the current standard of treatment for early-to-mid-stage hepatocellular carcinoma (HCC). However, questions remain unanswered regarding the management of recurrence after locoregional treatment. PD-1 inhibitors can block inhibitory signals of T-cell activation and proliferation to reduce the recurrence. We conducted a single-arm phase 2 trial to evaluate the efficacy and safety of PD-1 inhibitors following locoregional interventional therapy in HCC patients with high recurrence risk guided by our novel scoring system.

METHODS

Patients enrolled initially treated by TACE combined with ablation, then willingly joined the experimental group. One month later, they received the anti-PD-1 adjuvant therapy (intravenous injection of 200 mg), which was repeated every 3 weeks for a total of 4 or 8 cycles. Within this same period, other patients were screened into the control group to match the experimental group by 1:1 based on the propensity score matching method (PSM). The primary endpoint was relapse-free survival (RFS). Secondary endpoints included overall survival (OS) recurrence modality, safety, and quality of life.

RESULT

At the time of data cutoff, the median RFS of the control group was 7.0 months while the experimental group had not reached it. Moreover, the 1-year RFS rate was 73.3% in the experimental group and 46.7% in the control group, showing a significant difference (P =0.02). The rate of local tumor progression in the experimental group was clearly lower than that in the control group (P = 0.027). Benefits associated with anti-PD-1 adjuvant therapy were observed in patients with multiple tumors and tumor size ≤2cm. Univariate and multivariate analyses demonstrated that anti-PD-1 adjuvant therapy was an independent favorable prognostic factor for RFS in HCC patients. The most frequent AE observed in this study was RCCEP, and other AEs included diarrhea, hepatotoxicity, rash, pruritus, and fatigue. The incidence of GRADE ≥3 AE and withdrawal in this study was low with no deaths recorded.

CONCLUSIONS

Interim analysis from the study suggest the addition of anti-PD-1 adjuvant therapy after TACE combined with ablation could significantly prolong RFS with controllable safety for early-to-mid-stage HCC patients with high recurrence risk.

Developmental artificial neural network model to evaluate the preoperative safe limit of future liver remnant volume for HCC combined with clinically significant portal hypertension

Background & aims: Finding a way to comprehensively integrate the presence and grade of clinically significant portal hypertension, amount of preserved liver function and extent of hepatectomy into the guidelines for choosing appropriate candidates to hepatectomy remained challenging. This study sheds light on these issues to facilitate precise surgical decisions for clinicians. Methods: Independent risk factors associated with grade B/C post-hepatectomy liver failure were identified by stochastic forest algorithm and logistic regression in hepatitis B virus-related hepatocellular carcinoma patients. Results: The artificial neural network model was generated by integrating preoperative pre-ALB, prothrombin time, total bilirubin, AST, indocyanine green retention rate at 15 min, standard future liver remnant volume and clinically significant portal hypertension grade. In addition, stratification of patients into three risk groups emphasized significant distinctions in the risk of grade B/C post-hepatectomy liver failure. Conclusion: The authors' artificial neural network model could provide a reasonable therapeutic option for clinicians to select optimal candidates with clinically significant portal hypertension for hepatectomy and supplement the hepatocellular carcinoma surgical treatment algorithm.

Sarcopenia Predicts Major Complications after Resection for Primary Hepatocellular Carcinoma in Compensated Cirrhosis

Simple Summary

Sarcopenia, which is defined as a loss of skeletal muscle mass, function and strength, is the result of major metabolic changes often observed in advanced liver disease. Its evaluation mirrors the nutritional and functional status of the patients, and thus has been recently implicated as an outcome predictor of patients with liver diseases and hepatocellular carcinoma. This study provides evidence that sarcopenia, as assessed by the skeletal muscle index, is associated with age and body mass index in liver surgery candidates. More importantly, it is associated with higher rates of major complications (Clavien-Dindo grade III or IV) in patients with compensated advanced chronic liver disease and/or portal hypertension undergoing liver resection for primary hepatocellular carcinoma.

Abstract

The burden of post-operative complications of patients undergoing liver resection for hepatocellular carcinoma (HCC) is a cause of morbidity and mortality. Recently, sarcopenia has been reported to influence the outcome of patients with cirrhosis. We aimed to assess factors associated with sarcopenia and its prognostic role in liver surgery candidates. We included all patients with compensated advanced chronic liver disease (cACLD) undergoing liver resection for primary HCC consecutively referred to the University of Bologna from 2014 to 2019 with an available preoperative abdominal CT-scan performed within the previous three months. A total of 159 patients were included. The median age was 68 years, and 80.5% of the patients were male. Sarcopenia was present in 82 patients (51.6%). Age and body mass index (BMI) were associated with the presence of sarcopenia at multivariate analysis. Thirteen (8.2%) patients developed major complications and 14 (8.9%) presented PHLF grade B-C. The model for end-stage liver disease score was associated with the development of major complications, whereas cACLD presence, thrombocytopenia, portal hypertension (PH), Child-Pugh score and Albumin-Bilirubin score were found to be predictors of clinically significative PHLF. The rate of major complications was 11.8% in sarcopenic patients with cACLD compared with no complications (0%) in patients without sarcopenia and cACLD (p = 0.032). The rate of major complications was significantly higher in patients with (16.3%) vs. patients without (0%) sarcopenia (p = 0.012) in patients with PH. In conclusion, sarcopenia, which is associated with age and BMI, may improve the risk stratification of post-hepatectomy major complications in patients with cACLD and PH.

A Novel Predictive Scoring System for 90-Day Mortality among Patients with Hepatocellular Cell Carcinoma Receiving Major Hepatectomy

Simple Summary

Hepatocellular carcinoma (HCC) is a major malignancy correlated with many cancer-related deaths. Surgical intervention provides superior long-term survival; however, perioperative mortality is a major concern for clinicians while making treatment decisions, especially for major hepatectomy. Scoring systems for predicting 90-day mortality in patients with HCC undergoing major hepatectomy are not available. By using the stepwise selection of the multivariate Cox proportional hazards model, we divided the patients with HCC receiving major hepatectomy into four risk groups. The Chang Gung-PohAi predictive scoring system showed significant differences in the 90-day mortality rate among the four risk groups (very low risk: 2.42%, low risk: 4.09%, intermittent risk: 17.1%, and high risk 43.6%). The Chang Gung-PohAi predictive scoring system is a promising tool for predicting 90-day perioperative mortality in patients with HCC undergoing major hepatectomy.

Abstract

Purpose: Hepatocellular carcinoma (HCC) is a major malignancy and the common cause of cancer-related deaths. Surgical intervention provides superior long-term survival outcomes; however, perioperative mortality is a major concern for clinicians while making treatment decisions, especially for major hepatectomy. Scoring systems for predicting 90-day mortality in patients with HCC undergoing major hepatectomy are not available. Methods: This study used the Taiwan Cancer Registry Database that is linked to the National Health Insurance Research Database to analyze data of 60,250 patients with HCC who underwent major hepatectomy and determine risk factors to establish a novel predictive scoring system. By using the stepwise selection of the multivariate Cox proportional hazards model, we divided the patients with HCC undergoing major hepatectomy into four risk groups. Results: The Chang Gung-PohAi predictive scoring system exhibited significant differences in the 90-day mortality rate among the four risk groups (very low risk: 2.42%, low risk: 4.09%, intermittent risk: 17.1%, and high risk: 43.6%). Conclusion: The Chang Gung-PohAi predictive scoring system is a promising tool for predicting 90-day perioperative mortality in patients with HCC undergoing major hepatectomy.

Novel combined fibrosis-based index predicts the long-term outcomes of hepatocellular carcinoma after hepatic resection

AIM

Liver fibrosis influences liver regeneration and surgical outcomes. The fibrosis-4 (FIB-4) index is strongly associated with liver fibrosis and cirrhosis. This study aimed to examine the prognostic significance of the combination of FIB-4 index and Protein Induced by Vitamin K Absence or Antagonist-II (PIVKA-II) (PIVKA-II-FIB-4 index score) in patients who underwent curative resection for hepatocellular carcinoma (HCC).

METHODS

We included 284 patients who underwent elective hepatic resection for HCC between January 2000 and December 2018. We retrospectively investigated how FIB-4 index is related to disease-free survival and overall survival.

RESULTS

According to a receiver operating characteristic (ROC) analysis, the optimal cutoff value of the FIB-4 index was 3.44. In a multivariate analysis, high PIVKA-II and FIB-4 index values were independent predictors of both disease-free survival (P = 0.013 and P = 0.005, respectively) and overall survival (P = 0.048 and P < 0.001, respectively). We classified the PIVKA-II and FIB-4 index levels into two groups (high vs. low) and calculated a new score (PIVKA-II-FIB-4 index score; 0-2) by the sum of each measurement (high, 1; low, 0). The 5 year overall survival rates of patients with PIVKA-II-FIB-4 index scores of 0, 1, and 2 were 84.9, 74.4, and 47.1%, respectively (P < 0.001).

CONCLUSION

The combination of the preoperative PIVKA-II and FIB-4 index may be a prognostic factor of HCC after hepatic resection, suggesting that the combined score is useful in assessing the liver fibrosis status in cancer cases.

A systematic review of prediction models for post-hepatectomy liver failure in patients undergoing liver surgery

BACKGROUND

The aim of this systematic review is to evaluate the current evidence in the context of clinical prediction model for post-hepatectomy liver failure (PHLF).

METHODS

A systematic search of the English literature for a period from December 2005 to September 2020 was conducted. Primary outcome was defined using the three common PHLF criteria (50-50 criteria, peak bilirubin>7 mg/dl criteria, and ≥ grade B PHLF criteria by the International Study Group of Liver Surgery). Studies that reported the value of area under receiver operative characteristic curve (AUC) for the occurrence of PHLF were included.

RESULTS

Twenty eight of 1327 screened articles were eligible for inclusion. Eighteen studies developed the prediction models. The median AUC was found to be 0.79 (0.65-0.933). The parameters related to the amount of future liver remnant volume were most commonly identified as significant predictors for PHLF in statistical analysis (24 studies) and were most frequently incorporated in the prediction models (18 studies). The parameters associated with portal hypertension were significant for predicting PHLF in 16 studies and were adopted in the prediction models in 14 studies.

CONCLUSION

Parameters related to future liver remnant volume and portal hypertension seem to be facilitating in predicting PHLF.

Resection of NAFLD-Associated HCC: Patient Selection and Reported Outcomes

Global prevalence of non-alcoholic fatty liver disease (NAFLD) has been growing in the last decades, especially in western countries, due to increased prevalence of diabetes, obesity or other components of metabolic syndrome. NAFLD recently became an important cause of hepatocellular carcinoma (HCC), even in non-cirrhotic patients. Patients with HCC-NAFLD are usually older, with more morbidities (especially cardiovascular diseases and metabolic disorders) and have advanced disease at the diagnosis due to the absence of surveillance, which is considered not cost-effective in patients without advanced fibrosis/cirrhosis, given the large prevalence of NAFLD in the general population. For these reasons, patients with HCC-NAFLD unlikely underwent curative treatments, and have been reported to have lower overall survival (OS) compared to individuals with HCC related to other aetiologies. However, this difference is not confirmed by data of patient subgroups who received curative treatment. In our review, we selected studies published over the past 8 years that analyse characteristics and outcomes of HCC-NAFLD patients who underwent surgery with the aim of identifying features that could predict outcomes and potential selection criteria. All the studies confirm that patients with HCC-NAFLD are older, with many comorbidities and that HCC occurs frequently even in non-cirrhotic livers. There is no agreement about intraoperative and perioperative complications. Regarding outcomes, all papers agree that patients with HCC in NAFLD who undergo surgery have a better OS compared to other aetiologies. Summarizing, surgery is a good curative option for patients with HCC-NAFLD, perhaps even better than transplantation in terms of OS. In this group of patients, it seems to be essential to evaluate cardio-pulmonary and general operative risk, in addition to the normal risk assessment related to liver function to avoid an underestimation, especially for patients without severe underlying fibrosis.

The combination of the preoperative albumin-bilirubin grade and the fibrosis-4 index predicts the prognosis of patients with hepatocellular carcinoma after liver resection

There is little information regarding the use of a combination of the albumin-bilirubin (ALBI) grade and the fibrosis-4 index (FIB-4) in predicting hepatocellular carcinoma (HCC) patient outcomes after liver resection. In this study, we aimed to analyze the predictive ability of a combination of the ALBI grade and the FIB-4 score (ALBI-FIB-4) for HCC patients within the Milan criteria after liver resection. The data of HCC patients within the Milan criteria who underwent liver resection between 2011 and 2019 at our center were reviewed (n = 544). Patients with an FIB-4 index > 3.25 were considered to have a high FIB-4 index and were given a score of 1, whereas patients with an FIB-4 index ≤ 3.25 were considered to have a low FIB-4 index and were given a score of 0. The ALBI-FIB-4 score was a summary score that combined the ALBI grade and the score based on the FIB-4 index. During the follow-up period, 279 patients experienced recurrence, and 175 patients died. Multivariate analysis showed that tumor size, the presence of multiple tumors, the presence of microvascular invasion and the ALBI-FIB-4 score were four independent risk factors for both postoperative recurrence-free survival (RFS) and overall survival (OS). The 5-year RFS of patients with high ALBI-FIB-4 scores of 1, 2, and 3 were 55.0%, 44.2% and 35.3%, respectively (p = 0.004). The 5-year OS rates of patients with high ALBI-FIB-4 scores of 1, 2, and 3 were 72.9%, 66.4% and 54.8%, respectively (p = 0.011). The ALBI-FIB-4 score may be a surrogate marker for predicting the prognosis of patients with HCC after liver resection. A high ALBI-FIB-4 score was associated with a high incidence of postoperative recurrence and mortality.

Platelets and Hepatocellular Cancer: Bridging the Bench to the Clinics

Growing interest is recently being focused on the role played by the platelets in favoring hepatocellular cancer (HCC) growth and dissemination. The present review reports in detail both the experimental and clinical evidence published on this topic. Several growth factors and angiogenic molecules specifically secreted by platelets are directly connected with tumor progression and neo-angiogenesis. Among them, we can list the platelet-derived growth factor, the vascular endothelial growth factor, the endothelial growth factor, and serotonin. Platelets are also involved in tumor spread, favoring endothelium permeabilization and tumor cells’ extravasation and survival in the bloodstream. From the bench to the clinics, all of these aspects were also investigated in clinical series, showing an evident correlation between platelet count and size of HCC, tumor biological behavior, metastatic spread, and overall survival rates. Moreover, a better understanding of the mechanisms involved in the platelet–tumor axis represents a paramount aspect for optimizing both current tumor treatment and development of new therapeutic strategies against HCC.