A novel surgical scheme for hepatectomy in hepatocellular carcinoma patients with clinically significant portal hypertension.

OBJECTIVE: Clinically significant portal hypertension (CSPH) seriously affects the feasibility and safety of surgical treatment for hepatocellular carcinoma (HCC) patients. The aim of this study was to establish a new surgical scheme defining risk classification of post-hepatectomy liver failure (PHLF) to facilitate the surgical decision-making and identify suitable candidates for individual hepatectomy among HCC patients with CSPH. BACKGROUNDS: Hepatectomy is the preferred treatment for HCC. Surgeons must maintain a balance between the expected oncological outcomes of HCC removal and short-term risks of severe PHLF and morbidity. CSPH aggravates liver decompensation and increases the risk of severe PHLF thus complicating hepatectomy for HCC. METHODS: Multivariate logistic regression and stochastic forest algorithm were performed, then the independent risk factors of severe PHLF were included in a nomogram to determine the risk of severe PHLF. Further, a conditional inference tree (CTREE) through recursive partitioning analysis validated supplement the misdiagnostic threshold of the nomogram. RESULTS: This study included 924 patients, of whom 137 patients (14.8%) suffered from mild-CSPH and 66 patients suffered from (7.1%) with severe-CSPH confirmed preoperatively. Our data showed that preoperative prolonged prothrombin time, total bilirubin, indocyanine green retention rate at 15 min, CSPH grade, and standard future liver remnant volume were independent predictors of severe PHLF. By incorporating these factors, the nomogram achieved good prediction performance in assessing severe PHLF risk, and its concordance statistic was 0.891, 0.850 and 0.872 in the training cohort, internal validation cohort and external validation cohort, respectively, and good calibration curves were obtained. Moreover, the calculations of total points of diagnostic errors with 95% CI were concentrated in 110.5 (range 76.9-178.5). It showed a low risk of severe PHLF (2.3%), indicating hepatectomy is feasible when the points fall below 76.9, while the risk of severe PHLF is extremely high (93.8%) and hepatectomy should be rigorously restricted at scores over 178.5. Patients with points within the misdiagnosis threshold were further examined using CTREE according to a hierarchic order of factors represented by the presence of CSPH grade, ICG-R15, and sFLR. CONCLUSION: This new surgical scheme established in our study is practical to stratify risk classification in assessing severe PHLF, thereby facilitating surgical decision-making and identifying suitable candidates for individual hepatectomy.

Radiotherapy is superior to transarterial chemoembolization as adjuvant therapy after narrow-margin hepatectomy in patients with hepatocellular carcinoma: A single-center prospective randomized study.

BACKGROUND: This study was recruited to compare the efficacy and safety of radiotherapy (RT) and transarterial chemoembolization (TACE) as postoperative adjuvant therapy after narrow-margin hepatectomy in hepatocellular carcinoma (HCC) patients. METHODS: This single-center prospective randomized study was conducted in the Cancer Hospital, Guang Xi Medical University, Nanning. A total of 72 patients who received treatment in this hospital between August 2017 and July 2019 were included and randomly allocated to TACE group (n = 48) and RT group (n = 24). Next, overall survival (OS) and progression-free survival (PFS) rates, recurrence patterns, financial burden, and safety were evaluated. RESULTS: The difference between the RT and TACE groups was not significant in one-, three-, and five-year OS (87.5%, 79.0%, and 62.5% vs. 93.8%, 75.9%, and 63.4%, respectively, P = 0.071) and PFS rates (79.0%, 54.2%, and 22.6% vs. 75.0%, 47.9%, and 32.6%, respectively, P = 0.071). Compared to the TACE group, the RT group had significantly lower intrahepatic recurrence rate (20.8% vs. 52.1%, P = 0.011), higher extrahepatic recurrence rate (37.5% vs. 14.6%, P = 0.034), and no marginal and diffuse recurrences (0% vs. 16.7%, P < 0.05). The mean overall treatment cost was higher (¥62,550.59 ± 4397.27 vs. ¥40,732.56 ± 9210.54, P < 0.01), the hospital stay (15.1 ± 3.7 vs. 11.8 ± 4.1 days, P < 0.01) was longer, and the overall treatment stay (13.3 ± 5.3 vs. 41.29 ± 12.4 days, P < 0.01) was shorter in the TACE group than in the RT group. Besides, both groups did not exhibit significant differences in the frequency and severity of adverse events. CONCLUSION: Both adjuvant TACE and RT can better the OS and PFS of patients with HCC. However, RT has a significantly better performance than TACE in terms of improving intrahepatic recurrence rate, treatment cost and hospital stay.

C-Reactive Protein-Albumin Ratio (CAR): A More Promising Inflammation-Based Prognostic Marker for Patients Undergoing Curative Hepatectomy for Hepatocellular Carcinoma.

Background: Systemic inflammatory response is a hallmark of cancer and plays a significant role in the development and progression of various malignant tumors. This research aimed to estimate the prognostic function of the C-reactive protein-albumin ratio (CAR) in patients undergoing hepatectomy for hepatocellular carcinoma (HCC) and compare it with other inflammation-based prognostic scores, including the neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, monocyte-lymphocyte ratio, systemic immune inflammation index, prognostic index, Glasgow prognostic score, and modified Glasgow prognostic score. Methods: Retrospective analysis was conducted on data from 1039 HCC cases who underwent curative liver resection. The prognostic performance of CAR was compared with other scores using the area under the time-dependent receiver operating characteristic (t-ROC) curve. Multivariable Cox regression analyses were performed to confirm independent predictors for disease-free survival (DFS) and overall survival (OS). Results: The area under the t-ROC curve for CAR in the evaluation of DFS and OS was significantly greater than that of other scores and alpha-fetoprotein (AFP). Patients were stratified based on the optimal cut-off value of CAR, and the data revealed that both DFS and OS were remarkably worse in the high-CAR set compared to the low-CAR set. Multivariable Cox analysis demonstrated that CAR was an independent prognostic parameters for assessing DFS and OS. Regardless of AFP levels, all patients were subsequently divided into significantly different subgroups of DFS and OS based on CAR risk stratification. Similar results were observed when applying CAR risk stratification to other scoring systems. CAR also showed good clinical applicability in patients with different clinical features. Conclusion: CAR is a more effective inflammation-based prognostic marker than other scores and AFP in predicting DFS as well as OS among patients with HCC after curative hepatectomy.

Laparoscopic and open liver resection for hepatocellular carcinoma with type 2 diabetes mellitus: multicenter propensity score-matched study.

PURPOSE: This study aimed at analyzing and comparing the perioperative results and long-term oncological outcomes of hepatocellular carcinoma (HCC) patients with type 2 diabetes mellitus (T2DM) treated with laparoscopic (LLR) versus open liver resection (OLR). METHODS: Clinicopathological data of HCC patients with T2DM who underwent LLR or OLR as initial treatment from four medical centers were retrospectively reviewed. The survival outcomes of patients who underwent laparoscopic liver resection (LLR) were compared with those of patients who underwent open liver resection (OLR). Using the Kaplan-Meier method, survival curves for the two groups of patients were generated, and the log-rank test was used to compare survival differences. Propensity score matching (PSM) analysis was used to match patients of the LLR and OLR groups in a 1:1 ratio. RESULTS: 230 HCC patients with T2DM were enrolled, including 101 patients in the LLR group and 129 patients in the OLR group. After PSM, 90 patients were matched in each of the study group. Compared with the OLR group, the LLR group had less blood loss, a shorter hospitalization and fewer postoperative complications. The LLR group had a significantly better overall survival (OS) and recurrence-free survival (RFS) than the OLR group before and after PSM. Subgroup analysis demonstrated that HCC patients with T2DM had survival benefits from LLR regardless of the course of T2DM. CONCLUSIONS: Laparoscopic liver resection for HCC patients with T2DM can be safely performed with favorable perioperative and long-term oncological outcomes at high-volume liver cancer centers, regardless of the course of T2DM.

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.

Hepatectomy involves removing the tumor from the liver and is considered the most effective treatment for hepatocellular carcinoma (HCC). Clinically significant portal hypertension is characterized by the presence of gastric and/or esophageal varices and a platelet count <100 × 10⁹/l with the presence of splenomegaly, which would aggravate the risk of post-hepatectomy liver failure, and is therefore regarded as a contraindication to hepatectomy. Over the past few decades, with improvement in surgical techniques and perioperative care, the morbidity of postoperative complications and mortality have decreased greatly. Current HCC guidelines recommend the expansion of hepatectomy to HCC patients with clinically significant portal hypertension. However, determining how to select optimal candidates for hepatectomy remains challenging. The authors' artificial neural network is a mathematical tool developed by simulating the properties of neurons with large-scale information distribution and parallel structure. Here the authors retrospectively enrolled 871 hepatitis B virus-related HCC patients and developed an artificial neural network model to predict the risk of post-hepatectomy liver failure, which could provide a reasonable therapeutic option and facilitate precise surgical decisions for clinicians.

Perioperative and long-term survival outcomes of laparoscopic versus laparotomic hepatectomy for BCLC stages 0-A hepatocellular carcinoma patients associated with or without microvascular invasion: a multicenter, propensity score matching analysis.

PURPOSE: To analyze the long-term oncological outcomes of Barcelona Clinic Liver Cancer (BCLC) stages 0-A hepatocellular carcinoma (HCC) patients associated with or without microvascular invasion (MVI) treated with laparoscopic versus laparotomic liver resection. METHODS: Clinicopathological data of HCC patients with BCLC stages 0-A from four medical centers were retrospectively reviewed. The survival outcomes of patients who underwent laparoscopic hepatectomy were compared with those who underwent laparotomic hepatectomy. Subgroup analyses in terms of MVI were further performed to explore the effect of surgical approaches on the long-term survival outcomes. Propensity score matching (PSM) analysis was used to match patients between the laparoscopic and laparotomic resection groups in a 1:1 ratio. RESULTS: 495 HCC patients at BCLC stages 0-A were enrolled, including 243 in the laparoscopic resection group and 252 in the laparotomic resection group. Laparoscopic resection group had a shorter operation time, less blood loss, a lower frequency of blood transfusion and postoperative complication rates. The laparoscopic resection group had a significantly better overall survival (OS) and recurrence-free survival (RFS) than the laparotomic resection group before and after PSM. Subgroup analysis demonstrated that OS and RFS of patients without MVI were remarkably better in the laparoscopic resection group compared with the laparotomic resection group. However, no significant differences in OS and RFS between the two groups were found in patients with MVI after PSM. CONCLUSIONS: Pure laparoscopic hepatectomy for patients with BCLC stages 0-A HCC can be performed safely with favorable perioperative and long-term oncological outcomes at high-volume liver cancer centers, regardless of the presence of MVI.

Impact of type 2 diabetes mellitus on the prognosis of patients with hepatocellular carcinoma after laparoscopic liver resection: A multicenter retrospective study.

Background: The effect of type 2 diabetes mellitus (T2DM) on survival of patients with hepatocellular carcinoma (HCC) after laparoscopic liver resection (LLR) has not been reported. This study aimed to explore the relationship between preoperative T2DM and long-term prognosis in HCC patients undergoing LLR. Methods: HCC patients receiving LLR as initial treatment at four cancer centers were retrospectively included in this study. Clinicopathological factors associated with the prognosis of HCC patients were identified using univariate and multivariate Cox regression analysis. Recurrence-free survival (RFS) and overall survival (OS) curves between different cohorts of patients were generated using the Kaplan-Meier method and compared using the log-rank test. Results: Of 402 HCC patients included, 62 patients had T2DM and 340 patients did not have T2DM. The OS and RFS of patients with T2DM were significantly worse compared to those without T2DM (P = 0.001 and 0.032, respectively). In Cox multivariate analysis, T2DM was identified as an independent risk factors for OS (HR = 2.31, 95% CI = 1.38-3.85, P = 0.001) and RFS (HR = 1.66, 95% CI = 1.08-2.55, P = 0.020). Conclusions: Following laparoscopic surgical approach, HCC patients with T2DM had poorer prognoses than those without T2DM. Preoperative T2DM was an independent risk factor for HCC patients. Thus, patients with concurrent HCC and T2DM should be closely monitored after LLR.

A Prospective Study of Liver Regeneration After Radiotherapy Based on a New (Su'S) Target Area Delineation.

BACKGROUND: In this study, we designed a new (Su'S) target area delineation to protect the normal liver during liver regeneration and prospectively evaluate liver regeneration after radiotherapy, as well as to explore the clinical factors of liver regeneration and established a model and nomogram. METHODS: Thirty patients treated with preoperative downstaging radiotherapy were prospectively included in the training cohort, and 21 patients treated with postoperative adjuvant radiotherapy were included in the validation cohort. The cut-off points of each optimal predictor were obtained using receiver-operating characteristic analysis. A model and nomogram for liver regeneration after radiotherapy were developed and validated. RESULTS: After radiotherapy, 12 (40%) and 13 (61.9%) patients in the training and validation cohorts experienced liver regeneration, respectively. The risk stratification model based on the cutoffs of standard residual liver volume spared from at least 20 Gy (SVs20 = 303.4 mL/m2) and alanine aminotransferase (ALT=43 u/L) was able to effectively discriminate the probability of liver regeneration. The model and nomogram of liver regeneration based on SVs20 and ALT showed good prediction performance (AUC=0.759) in the training cohort and performed well (AUC=0.808) in the validation cohort. CONCLUSIONS: SVs20 and ALT were optimal predictors of liver regeneration. This model may be beneficial to the constraints of the normal liver outside the radiotherapy-targeted areas.

Artificial neural network model to predict post-hepatectomy early recurrence of hepatocellular carcinoma without macroscopic vascular invasion.

BACKGROUND: The accurate prediction of post-hepatectomy early recurrence (PHER) of hepatocellular carcinoma (HCC) is vital in determining postoperative adjuvant treatment and monitoring. This study aimed to develop and validate an artificial neural network (ANN) model to predict PHER in HCC patients without macroscopic vascular invasion. METHODS: Nine hundred and three patients who underwent curative liver resection for HCC participated in this study. They were randomly divided into derivation (n = 679) and validation (n = 224) cohorts. The ANN model was developed in the derivation cohort and subsequently verified in the validation cohort. RESULTS: PHER morbidity in the derivation and validation cohorts was 34.8 and 39.2%, respectively. A multivariable analysis revealed that hepatitis B virus deoxyribonucleic acid load, γ-glutamyl transpeptidase level, α-fetoprotein level, tumor size, tumor differentiation, microvascular invasion, satellite nodules, and blood loss were significantly associated with PHER. These factors were incorporated into an ANN model, which displayed greater discriminatory abilities than a Cox's proportional hazards model, preexisting recurrence models, and commonly used staging systems for predicting PHER. The recurrence-free survival curves were significantly different between patients that had been stratified into two risk groups. CONCLUSION: When compared to other models and staging systems, the ANN model has a significant advantage in predicting PHER for HCC patients without macroscopic vascular invasion.

S100P as a novel biomarker of microvascular invasion and portal vein tumor thrombus in hepatocellular carcinoma.

BACKGROUND: Portal vein tumor thrombus (PVTT) and microvascular invasion (MVI) are types of intrahepatic vascular metastasis of hepatocellular carcinoma (HCC) and are highly correlated with poor prognosis. However, the underlying biomarkers of PVTT and MVI are unclear. METHODS: We identified a PVTT/MVI-associated gene S100P by cDNA microarray analysis, and assess the potential value of serum S100P measurement in the differential diagnosis of HCC and prediction of MVI status with large retrospective and perspective cohort studies. RESULTS: The mRNA and protein of S100P was increased in HCCs with PVTT or MVI. High S100P immunostaining in tumors was correlated with inferior tumor-free survival. Serum S100P values discriminated patients with HCCs from those with benign liver tumors, and it showed predictive potential of MVI status in both retrospective and perspective cohorts. S100P may regulate HCC tumorigenicity and invasive ability; S100P also was associated with up-regulation of CD44, which may mediate HCC cell adhesion to form PVTT/MVI. CONCLUSIONS: Serum S100P may be a novel differential diagnostic marker for HCC and a potential predictor of MVI status pre-surgery for HCC patients. S100P overexpression in HCC is highly correlated with the formation of PVTT and MVI, which may make S100P as a potential therapeutic target for HCC metastasis.

Combining Aspartate Aminotransferase-to-Platelet Ratio Index with Future Liver Remnant to Assess Preoperative Hepatic Functional Reserve in Patients with Hepatocellular Carcinoma.

BACKGROUND: Accurate preoperative assessment of hepatic functional reserve is essential for conducting a safe hepatectomy. In recent years, aspartate aminotransferase-to-platelet ratio index (APRI) has been used as a noninvasive model for assessing fibrosis stage, hepatic functional reserve, and prognosis after hepatectomy with a high level of accuracy. The purpose of this research was to evaluate the clinical value of combining APRI with standardized future liver remnant (sFLR) for predicting severe post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC). METHODS: Six hundred thirty-seven HCC patients who had undergone hepatectomy were enrolled in this study. The performance of the Child-Pugh (CP) grade, model for end-stage liver disease (MELD), APRI, sFLR, and APRI-sFLR in predicting severe PHLF was assessed using the area under the ROC curve (AUC). RESULTS: Severe PHLF was found to have developed in 101 (15.9%) patients. Multivariate logistic analyses identified that prealbumin, cirrhosis, APRI score, sFLR, and major resection were significantly associated with severe PHLF. The AUC values of the CP, MELD, APRI, and sFLR were 0.626, 0.604, 0.725, and 0.787, respectively, indicating that the APRI and sFLR showed significantly greater discriminatory abilities than CP and MELD (P < 0.05 for all). After APRI was combined with sFLR, the AUC value of APRI-sFLR for severe PHLF was 0.816, which greatly improved the prediction accuracy, compared with APRI or sFLR alone (P < 0.05 for all). Stratified analysis using the status of cirrhosis and extent of resection yielded similar results. Moreover, the incidence and grade of PHLF were significantly different among the three risk groups. CONCLUSION: The combination of APRI and sFLR can be considered to be a predictive factor with increased accuracy for severe PHLF in HCC patients, compared with CP grade, MELD, APRI, or sFLR alone.

Development and Validation of a Nomogram to Preoperatively Estimate Post-hepatectomy Liver Dysfunction Risk and Long-term Survival in Patients With Hepatocellular Carcinoma.

OBJECTIVE: To develop a nomogram to estimate the risk of SPLD (International Study Group of Liver Surgery definition grade B or C) and long-term survival in patients with HCC before hepatectomy. BACKGROUND: SPLD is the leading cause of post-hepatectomy mortality. The decision to refer an HCC patient for hepatectomy is mainly based on the survival benefit and SPLD risk. Prediction of SPLD risk before hepatectomy is of great significance. METHODS: A total of 2071 consecutive patients undergoing hepatectomy for HCC were recruited and randomly divided into the development cohort (n = 1036) and internal validation cohort (n = 1035). Five hundred ninety patients from another center were enrolled as the external validation cohort. A nomogram was developed based on independent preoperative predictors of SPLD determined in multivariable logistic regression analysis. RESULTS: The SPLD incidences in the development, internal, and external validation cohorts were 10.1%, 9.5%, and 8.6%, respectively. Multivariable analysis identified total bilirubin, albumin, gamma-glutamyl transpeptidase, prothrombin time, clinically significant portal hypertension, and major resection as independent predictors for SPLD. Incorporating these variables, the nomogram showed good concordance statistics of 0.883, 0.851, and 0.856, respectively in predicting SPLD in the 3 cohorts. Its predictive performance in SPLD, 90-day mortality, and overall survival (OS) outperformed Child-Pugh, model for end-stage liver disease, albumin-bilirubin, and European Association for the Study of the Liver recommended algorithm. With a nomogram score of 137, patients were stratified into low and high risk of SPLD. High-risk patients also had decreased OS. CONCLUSIONS: The nomogram showed good performance in predicting both SPLD and OS. It could help surgeons select suitable HCC patients for hepatectomy.

Nomogram for prediction of the international study Group of Liver Surgery (ISGLS) grade B/C Posthepatectomy liver failure in HBV-related hepatocellular carcinoma patients: an external validation and prospective application study.

BACKGROUND: To develop a nomogram for predicting the International Study Group of Liver Surgery (ISGLS) grade B/C posthepatectomy liver failure (PHLF) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients. METHODS: Patients initially treated with hepatectomy were included. Univariate regression analysis and stochastic forest algorithm were applied to extract the core indicators and reduce redundancy bias. The nomogram was then constructed by using multivariate logistic regression, and validated in internal and external cohorts, and a prospective clinical application. RESULTS: There were 900, 300 and 387 participants in training, internal and external validation cohorts, with the morbidity of grade B/C PHLF were 13.5, 11.0 and 20.2%, respectively. The nomogram was generated by integrating preoperative total bilirubin, platelet count, prealbumin, aspartate aminotransferase, prothrombin time and standard future liver remnant volume, then achieved good prediction performance in training (AUC = 0.868, 95%CI = 0.836-0.900), internal validation (AUC = 0.868, 95%CI = 0.811-0.926) and external validation cohorts (AUC = 0.820, 95%CI = 0.756-0.861), with well-fitted calibration curves. Negative predictive values were significantly higher than positive predictive values in training cohort (97.6% vs. 33.0%), internal validation cohort (97.4% vs. 25.9%) and external validation cohort (94.3% vs. 41.1%), respectively. Patients who had a nomogram score < 169 or ≧169 were considered to have low or high risk of grade B/C PHLF. Prospective application of the nomogram accurately predicted grade B/C PHLF in clinical practise. CONCLUSIONS: The nomogram has a good performance in predicting ISGLS grade B/C PHLF in HBV-related HCC patients and determining appropriate candidates for hepatectomy.

Artificial Neural Network Model for Liver Cirrhosis Diagnosis in Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma.

BACKGROUND: Testing for the presence of liver cirrhosis (LC) is one of the most critical diagnostic and prognostic assessments for patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). More non-invasive tools are needed to diagnose LC but the predictive abilities of current models are still inconclusive. This study aimed to develop and validate a novel and non-invasive artificial neural network (ANN) model for diagnosing LC in patients with HBV-related HCC using routine laboratory serological indicators. METHODS: A total of 1152 HBV-related HCC patients who underwent hepatectomy were included and randomly divided into the training set (n = 864, 75%) and validation set (n = 288, 25%). The ANN model was constructed from the training set using multivariate Logistic regression analysis and then verified in the validation set. RESULTS: The morbidity of LC in the training and validation sets was 41.2% and 46.8%, respectively. Multivariate analysis showed that age, platelet count, prothrombin time and total bilirubin were independent risk factors for LC (P < 0.05). The area under the ROC curve (AUC) analyses revealed that the ANN model had higher predictive accuracy than the Logistic model (ANN: 0.757 vs Logistic: 0.721; P < 0.001), and other scoring systems (ANN: 0.757 vs CP: 0.532, MELD: 0.594, ALBI: 0.575, APRI: 0.621, FIB-4: 0.644, AAR: 0.491, and GPR: 0.604; P < 0.05 for all) in diagnosing LC. Similar results were obtained in the validation set. CONCLUSION: The ANN model has better diagnostic capabilities than other commonly used models and scoring systems in assessing LC risk in patients with HBV-related HCC.

Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma.

BACKGROUND: Posthepatectomy liver failure is a worrisome complication after major hepatectomy for hepatocellular carcinoma and is the leading cause of postoperative mortality. Recommendations for hepatectomy for hepatocellular carcinoma are based on the risk of severe posthepatectomy liver failure, and accurately predicting posthepatectomy liver failure risk before undertaking major hepatectomy is of great significance. Thus, herein, we aimed to establish and validate an artificial neural network model to predict severe posthepatectomy liver failure in patients with hepatocellular carcinoma who underwent hemihepatectomy. METHODS: Three hundred and fifty-three patients who underwent hemihepatectomy for hepatocellular carcinoma were included. We randomly divided the patients into a development set (n = 265, 75%) and a validation set (n = 88, 25%). Multivariate logistic analysis facilitated identification of independent variables that we incorporated into the artificial neural network model to predict severe posthepatectomy liver failure in the development set and then verified in the validation set. RESULTS: The morbidity of patients with severe posthepatectomy liver failure in the development and validation sets was 24.9% and 23.9%, respectively. Multivariate analysis revealed that platelet count, prothrombin time, total bilirubin, aspartate aminotransferase, and standardized future liver remnant were all significant predictors of severe posthepatectomy liver failure. Incorporating these factors, the artificial neural network model showed satisfactory area under the receiver operating characteristic curve for the development set of 0.880 (95% confidence interval, 0.836-0.925) and for the validation set of 0.876 (95% confidence interval, 0.801-0.950) in predicting severe posthepatectomy liver failure and achieved well-fitted calibration ability. The predictive performance of the artificial neural network model for severe posthepatectomy liver failure outperformed the traditional logistic regression model and commonly used scoring systems. Moreover, stratification into 3 risk groups highlighted significant differences between the incidences and grades of posthepatectomy liver failure. CONCLUSION: The artificial neural network model accurately predicted the risk of severe posthepatectomy liver failure in patients with hepatocellular carcinoma who underwent hemihepatectomy. Our artificial neural network model might help surgeons identify intermediate and high-risk patients to facilitate earlier interventions.

Combination Of ALBI And APRI To Predict Post-Hepatectomy Liver Failure After Liver Resection For HBV-Related HCC Patients.

PURPOSE: Post-hepatectomy liver failure (PHLF) is a severe complication in hepatocellular carcinoma (HCC) patients who have undergone hepatectomy. This research aimed to investigate the combination of albumin-bilirubin (ALBI) score and aspartate aminotransferase-platelet ratio index (APRI) as a novel approach in predicting PHLF risk in hepatitis B virus (HBV)-related HCC patients. PATIENTS AND METHODS: HBV-related HCC patients who underwent hepatectomy from January 2006 to October 2013 were enrolled in this study. A novel model was constructed using a combination of ALBI and APRI scores to predict PHLF risk, and the prognostic value of the model was evaluated and compared with Child-Pugh (C-P) grade, ALBI score and APRI score. RESULTS: A total of 1,055 HCC patients were retrospectively studied, which included 151 experienced PHLF. Univariable and multivariate analyses showed that the ALBI and APRI scores were independent predictors of PHLF. The area under the ROC curve (AUC) of the ALBI score, APRI score, and C-P grade was 0.717, 0.720, and 0.602, respectively, with AUC (ALBI) > AUC (C-P) (P <0.001) and AUC (APRI) > AUC (C-P) (P <0.001). After ALBI was associated with APRI, the AUC (ALBI-APRI) was 0.766, and AUC (ALBI-APRI) > AUC (ALBI) (P <0.001), AUC (ALBI-APRI) > AUC (APRI) (P =0.047). Our results indicated that ALBI and APRI scores had higher discriminatory abilities than C-P grade in predicting the risk of PHLF, and the ALBI-APRI model could enhance the capability of predicting PHLF compared to ALBI or APRI alone. CONCLUSION: ALBI-APRI score is a novel and effective predictive model of PHLF for HBV-related HCC patients, and its accuracy in predicting the risk of PHLF is better than that of C-P, ALBI and APRI scores.

Upregulation of Long Non-Coding RNA ENST00000429227.1 Is Correlated with Poor Prognosis in Human Hepatocellular Carcinoma.

BACKGROUND Long non-coding RNAs (lncRNAs) have been shown to play an important regulatory role in many tumors. This study was designed to investigate the expression of lncRNA ENST00000429227.1 in hepatocellular carcinoma (HCC) and to determine whether the expression of lncRNA ENST00000429227.1 affects the prognosis of HCC. MATERIAL AND METHODS lncRNA ENST00000429227.1 showing differences in expression between M1 and M2 was screened by microarray expression measurements. Quantitative real-time PCR (qRT-PCR) was used to detect the expression of lncRNA ENST00000429227.1 in 161 HCC patients. The chi-square test was used to evaluate the relationship between the expression of ENST00000429227.1 and clinicopathological parameters. A survival curve was drawn and analyzed by Kaplan-Meier method. Cox regression was used for univariate and multivariate analysis to determine whether lncRNA ENST00000429227.1 is an independent factor of the occurrence and prognosis of HCC. RESULTS A total of 3703 differentially expressed lncRNAs were obtained, of which 1777 were upregulated and 1926 were downregulated, with multiple change >1.5. The expression of lncRNA ENST00000429227.1 was upregulated in M2 cells. The expression of lncRNA ENST00000429227.1 in HCC tissues was higher than that in adjacent normal tissues (p<0.05), which was correlated with pathological parameters such as surgical margin (p=0.042), AFP (p=0.022) and Barcelona Clinic Liver Cancer (BCLC) stage (p=0.008). Survival analysis showed that high expression of lncRNA ENST00000429227.1 was associated with a decrease in overall survival (OS) rate of HCC patients. Cox regression analysis showed that high expression of ENST00000429227.1 may be an independent risk factor affecting the prognosis of HCC patients. CONCLUSIONS The results suggest that upregulation of ENST00000429227.1 is associated with poor prognosis of HCC patients, and may be a new biomarker for the diagnosis of HCC.

Preoperative aspartate aminotransferase-to-platelet-ratio index as a predictor of posthepatectomy liver failure for resectable hepatocellular carcinoma.

PURPOSE: This study aimed to investigate the efficacy of preoperative aspartate aminotransferase-to-platelet-ratio index (APRI) score to predict the risk of posthepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC) after liver resection, and to compare the discriminatory performance of the APRI with the Child-Pugh score, model for end-stage liver disease (MELD) score, and albumin-bilirubin (ALBI) score. PATIENTS AND METHODS: A total of 1,044 consecutive patients with HCC who underwent liver resection were enrolled and studied. Univariate and multivariate analyses were performed to investigate risk factors associated with PHLF. Predictive discrimination of Child-Pugh, MELD, ALBI, and APRI scores for predicting PHLF were assessed according to area under the ROC curve. The cutoff value of the APRI score for predicting PHLF was determined by ROC analysis. APRI scores were stratified by dichotomy to analyze correlations with incidence and grade of PHLF. RESULTS: PHLF occurred in 213 (20.4%) patients. Univariate and multivariate analyses revealed that Child-Pugh, MELD, ALBI, and APRI scores were significantly associated with PHLF. Area under the ROC analysis revealed that the APRI score for predicting PHLF was significantly more accurate than Child-Pugh, MELD, or ALBI scores. With an optimal cutoff value of 0.55, the sensitivity and specificity of the APRI score for predicting PHLF were 72.2% and 68.0%, respectively, and the incidence and grade of PHLF in patients with high risk (APRI score >0.55) was significantly higher than in the low-risk cohort (APRI score <0.55). CONCLUSION: The APRI score predicted PHLF in patients with HCC undergoing liver resection more accurately than Child-Pugh, MELD, or ALBI scores.

Comparison of the ability of Child-Pugh score, MELD score, and ICG-R15 to assess preoperative hepatic functional reserve in patients with hepatocellular carcinoma.

BACKGROUND: Assessing hepatic functional reserve before hepatectomy is beneficial to reduce the incidence of posthepatectomy liver failure (PHLF). This study aimed to compare the ability of the Child-Pugh score, model for end-stage liver disease (MELD) score, and retention test at 15 minutes (indocyanine green [ICG]-R15) to assess hepatic functional reserve. METHODS: A total of 185 patients with hepatocellular carcinoma (HCC) undergoing hepatectomy were enrolled in this study. The ability of Child-Pugh score, MELD score, and ICG-R15 predicting severe PHLF were compared. RESULTS: A total of 23 patients (12.4%) developed severe PHLF. Multivariate analyses identified that platelet count, ICG-R15, clinically significant portal hypertension, and major resection were independent factors for predicting severe PHLF. The area under the receiver operating characteristic curve of ICG-R15 for predicting severe PHLF was higher than that of both Child-Pugh score and MELD score. With an optimal cutoff value of 7.1%, the sensitivity and specificity of ICG-R15 for predicting severe PHLF were 52.2% and 89.5%, respectively. Both the incidence of severe PHLF and mortality in patients with ICG-R15 >7.1% were significantly higher than the figures for patients with ICG-R15 ≤7.1%. CONCLUSION: ICG-R15 is more accurate than the Child-Pugh score and MELD score in predicting hepatic functional reserve before hepatectomy.

Circulating Tumor Cells Undergoing EMT Provide a Metric for Diagnosis and Prognosis of Patients with Hepatocellular Carcinoma.

To clarify the significance of circulating tumor cells (CTC) undergoing epithelial-mesenchymal transition (EMT) in patients with hepatocellular carcinoma (HCC), we used an advanced CanPatrol CTC-enrichment technique and in situ hybridization to enrich and classify CTC from blood samples. One hundred and one of 112 (90.18%) patients with HCC were CTC positive, even with early-stage disease. CTCs were also detected in 2 of 12 patients with hepatitis B virus (HBV), both of whom had small HCC tumors detected within 5 months. CTC count ≥16 and mesenchymal-CTC (M-CTC) percentage ≥2% prior to resection were significantly associated with early recurrence, multi-intrahepatic recurrence, and lung metastasis. Postoperative CTC monitoring in 10 patients found that most had an increased CTC count and M-CTC percentage before clinically detectable recurrence nodules appeared. Analysis of HCC with high CTC count and high M-CTC percentage identified 67 differentially expressed cancer-related genes involved in cancer-related biological pathways (e.g., cell adhesion and migration, tumor angiogenesis, and apoptosis). One of the identified genes, BCAT1, was significantly upregulated, and knockdown in Hepg2, Hep3B, and Huh7 cells reduced cell proliferation, migration, and invasion while promoting apoptosis. A concomitant increase in epithelial marker expression (EpCAM and E-cadherin) and reduced mesenchymal marker expression (vimentin and Twist) suggest that BCAT1 may trigger the EMT process. Overall, CTCs were highly correlated with HCC characteristics, representing a novel marker for early diagnosis and a prognostic factor for early recurrence. BCAT1 overexpression may induce CTC release by triggering EMT and may be an important biomarker of HCC metastasis.Significance: In liver cancer, CTC examination may represent an important "liquid biopsy" tool to detect both early disease and recurrent or metastatic disease, providing cues for early intervention or adjuvant therapy. Cancer Res; 78(16); 4731-44. ©2018 AACR.