Proposal of a new prognostic model for hepatocellular carcinoma: an analysis of 403 patients

Proposal of an integrated staging system using albumin-bilirubin grade and serum alpha-fetoprotein values for predicting postoperative prognosis of recurrent hepatocellular carcinoma

BACKGROUND

Because repeat hepatectomy for recurrent hepatocellular carcinoma is a potentially invasive procedure, it is necessary to identify patients who truly benefit from repeat hepatectomy. Albumin-bilirubin grading has been reported to predict survival in patients with hepatocellular carcinoma. However, as prognosis also depends on tumor factors, a staging system that adds tumor factors to albumin-bilirubin grading may lead to a more accurate prognostication in patients with recurrent hepatocellular carcinoma.

METHODS

Albumin-bilirubin grading and serum alpha-fetoprotein levels were combined and the albumin-bilirubin-alpha-fetoprotein score was created ([albumin-bilirubin grading = 1; 1 point, 2 or 3; 2 points] + [alpha-fetoprotein<75 ng/mL, 0 points; ≥5, 1 point]). Patients were classified into three groups, and their characteristics and survival were evaluated. The predictive ability of the albumin-bilirubin-alpha-fetoprotein score was compared with that of the Cancer of the Liver Italian Program and the Japan Integrated Stage scores.

RESULTS

Albumin-bilirubin-alpha-fetoprotein score significantly stratified postoperative survival (albumin-bilirubin-alpha-fetoprotein score = 1/2/3: 5-year recurrence-free survival [%]: 22.4/20.7/0.0, p < 0.001) and showed the highest predictive value for survival among the integrated systems (albumin-bilirubin-alpha-fetoprotein score/Japan Integrated Stage/Cancer of the Liver Italian Program: 0.785/0.708/0.750).

CONCLUSIONS

Albumin-bilirubin-alpha-fetoprotein score is useful for predicting the survival of patients with recurrent hepatocellular carcinoma undergoing repeat hepatectomy.

British Society of Gastroenterology guidelines for the management of hepatocellular carcinoma in adults

Deaths from the majority of cancers are falling globally, but the incidence and mortality from hepatocellular carcinoma (HCC) is increasing in the United Kingdom and in other Western countries. HCC is a highly fatal cancer, often diagnosed late, with an incidence to mortality ratio that approaches 1. Despite there being a number of treatment options, including those associated with good medium to long-term survival, 5-year survival from HCC in the UK remains below 20%. Sex, ethnicity and deprivation are important demographics for the incidence of, and/or survival from, HCC. These clinical practice guidelines will provide evidence-based advice for the assessment and management of patients with HCC. The clinical and scientific data underpinning the recommendations we make are summarised in detail. Much of the content will have broad relevance, but the treatment algorithms are based on therapies that are available in the UK and have regulatory approval for use in the National Health Service.

A Retrospective Study on Predicting Recurrence of Intermediate-Stage Hepatocellular Carcinoma After Radical Therapy

Purpose

This study aimed to investigate the potential benefits of radical therapy in patients with stage B disease.

Patients and Methods

A retrospective analysis was conducted on a cohort of 437 patients diagnosed with stage B hepatocellular carcinoma, who underwent either hepatic resection (HR) or radiofrequency ablation (RFA) at the Cancer Institute and Hospital of Tianjin Medical University from May 2011 to May 2022. Multivariate COX regression analysis was performed to identify the independent prognostic factors related to recurrence-free survival (RFS). The performance of the developed nomogram was evaluated using various statistical measures, including the concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

Results

Multivariate analysis revealed that tumor diameter, number of tumors, number of involved liver segments, alpha-fetoprotein (AFP), carbohydrate antigen 19-9 (CA19-9), lactate dehydrogenase (LDH), and systemic immune inflammation index (SII) were independent prognostic factors influencing patients' RFS, and these factors were incorporated into the nomogram. The C-index of the nomogram in the training cohort was 0.721, and the AUC at 2 and 3 years was 0.772 and 0.790, respectively. These values were appreciably higher than commonly used clinic staging systems and other predictive models. The calibration curve and DCA demonstrated good calibration and net benefit. Survival analysis comparing stage B patients who received radical treatment with stage A patients with multiple lesions did not reveal a significant difference in Kaplan-Meier survival curves (P=0.91).

Conclusion

The nomogram provided a precise prediction of the recurrence for stage B hepatocellular carcinoma patients undergoing radical treatment. Furthermore, certain stage B patients may benefit from radical treatment.

Comparison of patients with hepatitis B virus-associated hepatocellular carcinoma: Data from two hospitals from Turkey and China

Aims

There are many studies on the incidence of hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC), but very little is known about the HCC features in different populations. The study aimed to compare characteristics in two cohorts of patients with HBV-associated hepatocellular carcinoma, from Turkey and China.

Methods

Data on patients with HBV-associated HCC diagnosed by imaging or liver biopsy were retrospectively collected from Shandong Provincial Hospital (n = 578) and Inonu University Hospital (n = 359) between January 2002 and December 2020, and the liver function and HCC characteristics were compared. Continuous variables were compared using Student's t-test or Mann-Whitney U test and categorical variables were compared using the χ2 test or Fisher's exact test.

Results

The patients in the Turkish cohort had significantly worse Child-Pugh scores (Child-Pugh A: 38.3% vs. 87.9%; Child-Pugh B: 40.3% vs. 11.1%; Child-Pugh A: 24.1% vs. 1.0%; p < 0.001) and significantly higher levels of aspartate aminotransferase (66.5 vs. 36.0; p < 0.001), alanine aminotransferase (47.5 vs. 33.0; p < 0.001), total bilirubin (20.8 vs. 17.9; p < 0.001), and lower albumin levels (32.0 vs. 40.0; p < 0.001) than patients in Chinese cohort. The tumor characteristics showed the Barcelona Clinic Liver Cancer (BCLC) score (BCLC 1: 5.1% vs. 71.8%; BCLC 2: 48.7% vs. 24.4%; BCLC 3: 24.4% vs. 3.8%; BCLC 4: 21.8% vs. 0; all p < 0.001), maximum tumor diameter (5.0 vs. 3.5; p < 0.001), alpha-fetoprotein values (27.7 vs. 13.2; p < 0.001), and percentage of patients with portal vein tumor thrombus (33% vs. 6.1%; p < 0.001) were all significantly worse in the Turkish cohort compared with Chinese cohort.

Conclusions

HBV-associated HCC from the Turkish cohort had worse liver function and more aggressive clinical characteristics than patients from the Chinese cohort.

An integrative view on glucagon function and putative role in the progression of pancreatic neuroendocrine tumours (pNETs) and hepatocellular carcinomas (HCC)

Cancer metabolism research area evolved greatly, however, is still unknown the impact of systemic metabolism control and diet on cancer. It makes sense that systemic regulators of metabolism can act directly on cancer cells and activate signalling, prompting metabolic remodelling needed to sustain cancer cell survival, tumour growth and disease progression. In the present review, we describe the main glucagon functions in the control of glycaemia and of metabolic pathways overall. Furthermore, an integrative view on how glucagon and related signalling pathways can contribute for pancreatic neuroendocrine tumours (pNETs) and hepatocellular carcinomas (HCC) progression, since pancreas and liver are the major organs exposed to higher levels of glucagon, pancreas as a producer and liver as a scavenger. The main objective is to bring to discussion some glucagon-dependent mechanisms by presenting an integrative view on microenvironmental and systemic aspects in pNETs and HCC biology.

Development and Validation of Novel Models Including Tumor Micronecrosis for Predicting the Postoperative Survival of Patients with Hepatocellular Carcinoma

Background

The heterogeneity of hepatocellular carcinoma (HCC) leads to the unsatisfying predictive performance of current staging systems. HCC patients with pathological tumor micronecrosis have an immunosuppressive microenvironment. We aimed to develop novel prognostic models by integrating micronecrosis to predict the survival of HCC patients after hepatectomy more precisely.

Methods

We enrolled 765 HCC patients receiving curative hepatic resection. They were randomly divided into a training cohort (n= 536) and a validation cohort (n = 229). We developed two prognostic models for postoperative recurrence-free survival (RFS) and overall survival (OS) based on independent factors identified through multivariate Cox regression analyses. The predictive performance was assessed using the Harrell concordance index (C-index) and the time-dependent area under the receiver operating characteristic curve, compared with six conventional staging systems.

Results

The RFS and OS nomograms were developed based on tumor micronecrosis, tumor size, albumin-bilirubin grade, tumor number and prothrombin time. The C-indexes for the RFS nomogram and OS nomogram were respectively 0.66 (95% CI, 0.62-0.69) and 0.74 (95% CI, 0.69-0.79) in the training cohort, which was significantly better than those of the six common staging systems (0.52-0.61 for RFS and 0.53-0.63 for OS). The results were further confirmed in the validation group, with the C-indexes being 0.66 and 0.77 for the RFS and OS nomograms, respectively.

Conclusion

The two nomograms could more accurately predict RFS and OS in HCC patients receiving curative hepatic resection, thereby aiding in formulating personalized postoperative follow-up plans.

Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis

This study was conducted to identify risk factors affecting overall survival (OS) and provide prognostication for patients with hepatocellular carcinoma (HCC) using nationwide big data. Between January 2008 and December 2014, 10,573 adult patients with new HCC were registered in a nationwide database. Among them, 6830 patients without missing data were analyzed to construct a prognostication system. A validation cohort of 4580 patients was obtained from a tertiary hospital. All patients were assumed to have received the best treatment. A conditional inference tree analysis was performed to establish a prognostic system. The C-index and calibration plot for 5-year survival were estimated for validation. As a result, the tumor burden (TB) grade was the most significant factor in determining OS, and the cutoff was TB3 (TB1‒3 versus TB4). The patients were ultimately divided into 13 prognosis groups. The C-indexes were 0.714 and 0.737 (95% confidence interval, 0.733-0.742) in the nationwide (derivation) and hospital (validation) cohorts, respectively. In the calibration plot, the 5-year survival of the validation cohort largely matched the 45-degree line. In conclusion, the proposed prognostication system with a simple tree structure enabled the detailed stratification of patient prognosis and visualized the strata of risk factors affecting OS.

Mortality Evaluation and Life Expectancy Prediction of Patients with Hepatocellular Carcinoma with Data Mining

BACKGROUND

The complexity of systemic variables and comorbidities makes it difficult to determine the best treatment for patients with hepatocellular carcinoma (HCC). It is impossible to perform a multidimensional evaluation of every patient, but the development of guidelines based on analyses of said complexities would be the next best option. Whereas conventional statistics are often inadequate for developing multivariate predictive models, data mining has proven more capable. Patients, methods and findings: Clinical profiles and treatment responses of 537 patients diagnosed with Barcelona Clinic Liver Cancer stages B and C from 2009 to 2019 were retrospectively analyzed using 4 decision tree algorithms. A combination of 19 treatments, 7 biomarkers, and 4 states of hepatitis was tested to determine which combinations would result in survival times greater than a year in duration. Just 2 of the algorithms produced complete models through single trees, which made them only the ones suitable for clinical judgement. A combination of alpha fetoprotein ≤210.5 mcg/L, glutamic oxaloacetic transaminase ≤1.13 µkat/L, and total bilirubin ≤ 0.0283 mmol/L was shown to be a good predictor of survival >1 year, and the most effective treatments for such patients were radio-frequency ablation (RFA) and transarterial chemoembolization (TACE) with radiation therapy (RT). In patients without this combination, the best treatments were RFA, TACE with RT and targeted drug therapy, and TACE with targeted drug therapy and immunotherapy. The main limitation of this study was its small sample. With a small sample size, we may have developed a less reliable model system, failing to produce any clinically important results or outcomes.

CONCLUSION

Data mining can produce models to help clinicians predict survival time at the time of initial HCC diagnosis and then choose the most suitable treatment.

The prognostic value of the GPAT/AGPAT gene family in hepatocellular carcinoma and its role in the tumor immune microenvironment

Background

Liver cancer is the sixth most commonly diagnosed cancer and the third leading cause of cancer-related death worldwide. Hepatocellular carcinoma accounts for an estimated 90% of all liver cancers. Many enzymes of the GPAT/AGPAT family are required for the synthesis of triacylglycerol. Expression of AGPAT isoenzymes has been reported to be associated with an increased risk of tumorigenesis or development of aggressive phenotypes in a variety of cancers. However, whether members of the GPAT/AGPAT gene family also influence the pathophysiology of HCC is unknown.

Methods

Hepatocellular carcinoma datasets were obtained from the TCGA and ICGC databases. Predictive models related to the GPAT/AGPAT gene family were constructed based on LASSO-Cox regression using the ICGC-LIRI dataset as an external validation cohort. Seven immune cell infiltration algorithms were used to analyze immune cell infiltration patterns in different risk groups. IHC, CCK-8, Transwell assay, and Western blotting were used for in vitro validation.

Results

Compared with low-risk patients, high-risk patients had shorter survival and higher risk scores. Multivariate Cox regression analysis showed that risk score was a significant independent predictor of overall survival (OS) after adjustment for confounding clinical factors (p < 0.001). The established nomogram combined risk score and TNM staging to accurately predict survival at 1, 3, and 5 years in patients with HCC with AUC values of 0.807, 0.806, and 0.795, respectively. This risk score improved the reliability of the nomogram and guided clinical decision-making. In addition, we comprehensively analyzed immune cell infiltration (using seven algorithms), response to immune checkpoint blockade, clinical relevance, survival, mutations, mRNA expression-based stemness index, signaling pathways, and interacting proteins related to the three core genes of the prognostic model (AGPAT5, LCLAT1, and LPCAT1). We also performed preliminary validation of the differential expression, oncological phenotype, and potential downstream pathways of the three core genes by IHC, CCK-8, Transwell assay, and Western blotting.

Conclusion

These results improve our understanding of the function of GPAT/AGPAT gene family members and provide a reference for prognostic biomarker research and individualized treatment of HCC.

Pre- to postoperative alpha-fetoprotein ratio-based nomogram to predict tumor recurrence in patients with hepatocellular carcinoma

Background

This study aimed to investigate the role of the alpha fetoprotein (AFP) ratio before and after curative resection in the prognosis of patients with hepatocellular carcinoma (HCC) and to develop a novel pre- to postoperative AFP ratio nomogram to predict recurrence free survival (RFS) for HCC patients after curative resection.

Methods

A total of 485 pathologically confirmed HCC patients who underwent radical hepatectomy from January 2010 to December 2018 were retrospectively analyzed. The independent prognostic factors of hepatocellular carcinoma were identified by multivariate COX proportional model analysis, and the nomogram model was constructed. The receiver operating characteristic and the C-index were used to evaluate the accuracy and efficacy of the model prediction, the correction curve was used to assess the calibration of the prediction model, and decision curve analysis was used to evaluate the clinical application value of the nomogram model.

Results

A total of 485 HCC patients were divided into the training cohort (n = 340) and the validation cohort (n = 145) by random sampling at a ratio of 7:3. Using X-tile software, it was found that the optimal cut-off value of the AFP ratio in the training cohort was 0.8. In both cohorts, the relapse-free survival of patients with an AFP ratio <0.8 (high-risk group) was significantly shorter than in those with an AFP ratio ≥0.8 (low-risk group) (P < 0.05). An AFP ratio <0.8 was an independent risk factor for recurrence of HCC after curative resection. Based on the AFP ratio, BCLC stage and cirrhosis diagnosis, a satisfactory nomogram was developed. The AUC of our nomogram for predicting 1-, 3-, and 5-year RFS was 0.719, 0.690, and 0.708 in the training cohort and 0.721, 0.682, and 0.681 in the validation cohort, respectively. Furthermore, our model demonstrated excellent stratification as well as clinical applicability.

Conclusion

The AFP ratio was a reliable biomarker for tumor recurrence. This easy-to-use AFP ratio-based nomogram precisely predicted tumor recurrence in HCC patients after curative resection.

Hepatocellular Carcinoma: Current Therapeutic Algorithm for Localized and Advanced Disease

Hepatocellular carcinoma (HCC) is the most common primary liver cancer in patients with liver cirrhosis of various etiologies. In recent years, there has been an advance in the knowledge of molecular mechanisms and a better staging definition of patients which has allowed the development of new therapies that have entered the therapeutic workup of these patients. Deep information on molecular drivers of HCC contributed to the development of targeted therapies with remarkable benefits. The novel strategies of targeting immune evasion using immune checkpoint inhibitors and CAR-T and TCR-T therapeutics have also shown promising results. For advanced diseases, the therapeutic algorithm has been recently updated, thanks to the efficacy of combining immunotherapy and antiangiogenic therapy in the first-line setting, and new drugs, both as single-agents or combinations, are currently under investigation.

Hazard rate for postoperative recurrence in patients with hepatocellular carcinoma at Barcelona Clinic Liver Cancer stage 0 or A1: A multicenter observational study

AIM

Surgical treatment is the first-line treatment for patients with Barcelona Clinic Liver Cancer (BCLC) stage 0 or A1 hepatocellular carcinoma (HCC), and postoperative monitoring improves long-term survival. We aimed to establish a reasonable short-interval follow-up duration for patients with HCC.

METHODS

The cohort for this retrospective study included 1396 HCC patients with BCLC stage 0 or A1 disease who underwent curative resection from 2013 to 2016 at five centers in China. Hazard rates for recurrence were calculated using the hazard function.

RESULTS

The recurrence rates in patients with BCLC stage 0 and A1 HCC were 46.4% and 58.0%, respectively. The hazard curve for stage 0 patients was relatively flat, and the hazard rate was consistently low (peak hazard rate 0.0163). The hazard rate curve for recurrence was initially high (peak hazard rate 0.0441) in patients with BCLC stage A1 disease and showed a rapid decreasing trend within 1 year, followed by a slow decreasing trend, reaching a low level (<0.0163) at approximately 36 months. The time to low risk was 47, 41, and 51 months in patients with cirrhosis, hepatitis B virus (HBV) infection, and satellite lesions, respectively.

CONCLUSIONS

A short-interval follow-up of 1 year is sufficient for HCC patients with BCLC stage 0 disease, whereas a short-interval follow-up time of 3 years should be considered for patients with stage A1 disease. The follow-up period should be appropriately prolonged for patients with cirrhosis, HBV infection, and satellite lesions.

Recurrence hazard rate in patients with hepatocellular carcinoma and bile duct tumor thrombus: a multicenter observational study

BACKGROUND

Patients with hepatocellular carcinoma (HCC) bile duct tumor thrombus (BDTT) have a high rate of postoperative recurrence. We aimed to describe the patterns and kinetics of recurrence in BDTT patients and provide management options accordingly.

METHODS

This retrospective study included 311 HCC patients with BDTT who underwent surgery from 2009 to 2017 at five centers in China. The hazard rate of recurrence was calculated using the hazard function.

RESULTS

The hazard rate of intrahepatic recurrence was higher than that of extrahepatic recurrence (0.0588 vs. 0.0301), and both showed a decreasing trend, and the intrahepatic recurrence and extrahepatic recurrence risk decreased to a lower level after 40 and 20 months, respectively. Patients who underwent anatomic resection had a consistently lower hazard rate of recurrence than patients who underwent nonanatomic resection, whereas patients who received postoperative adjuvant transarterial chemoembolization (TACE) mainly had a lower hazard rate of recurrence in the first year than patients who did not.

CONCLUSION

The follow-up of BDTT patients should be at least 40 months because of its high rate of recurrence, in parallel with the need for vigilance for extrahepatic recurrence within 20 months. Anatomic hepatectomy and adjuvant TACE are recommended to improve BDTT patient outcomes.

Comparison of the long-term outcomes of patients with hepatocellular carcinoma within the Milan criteria treated by ablation, resection, or transplantation

BACKGROUND

Liver transplantation (LT), resection (LR), and ablation (LA) are three curative-intent treatment options for patients with early hepatocellular carcinoma (HCC). We aimed to develop a prognostic calculator to compare the long-term outcomes following each of these therapies.

METHODS

A total of 976 patients with HCC within the Milan criteria who underwent LT, LR, and LA between 2009 and 2019 from four institutions were evaluated. Multistate competing risks prediction models for recurrence-free survival (RFS), recurrence within the Milan criteria (RWM), and HCC-specific survival (HSS) were derived to develop a prognostic calculator.

RESULTS

During a median follow-up of 51 months, 420 (43%) patients developed recurrence. In the multivariate analysis, larger tumor size, multinodularity, older age, male, higher alpha-fetoprotein (AFP), higher albumin-bilirubin (ALBI) grade, and the presence of portal hypertension were significantly associated with higher recurrence and decreased survival rates. The RFS and HSS were both significantly higher among patients treated by LT than by LR or LA and significantly higher between patients treated by LR than by LA (all p < 0.001). For multinodular HCC ≤3 cm, although LT had better RFS and HSS than LR or LA, LA was noninferior to LR. An online prognostic calculator was then developed based on the preoperative clinical factors that were independently associated with outcomes to evaluate RFS, RWM, and HSS at different time intervals for all three treatment options.

CONCLUSIONS

Although LT resulted in the best recurrence and survival outcomes, LR and LA also offered durable long-term alternatives. This prognostic calculator is a useful tool for clinicians to guide an informed and personalized discussion with patients based on their tumor biology and liver function.

A deep learning model with incorporation of microvascular invasion area as a factor in predicting prognosis of hepatocellular carcinoma after R0 hepatectomy

INTRODUCTION

Microvascular invasion (MVI) is a known risk factor for prognosis after R0 liver resection for hepatocellular carcinoma (HCC). The aim of this study was to develop a deep learning prognostic prediction model by incorporating a new factor of MVI area to the other independent risk factors.

METHODS

Consecutive patients with HCC who underwent R0 liver resection from January to December 2016 at the Eastern Hepatobiliary Surgery Hospital were included in this retrospective study. For patients with MVI detected on resected specimens, they were divided into two groups according to the size of the maximal MVI area: the small-MVI group and the large-MVI group.

RESULTS

Of 193 patients who had MVI in the 337 HCC patients, 130 patients formed the training cohort and 63 patients formed the validation cohort. The large-MVI group of patients had worse overall survival (OS) when compared with the small-MVI group (p = 0.009). A deep learning model was developed based on the following independent risk factors found in this study: MVI stage, maximal MVI area, presence/absence of cirrhosis, and maximal tumor diameter. The areas under the receiver operating characteristic of the deep learning model for the 1-, 3-, and 5-year predictions of OS were 80.65, 74.04, and 79.44, respectively, which outperformed the traditional COX proportional hazards model.

CONCLUSION

The deep learning model, by incorporating the maximal MVI area as an additional prognostic factor to the other previously known independent risk factors, predicted more accurately postoperative long-term OS for HCC patients with MVI after R0 liver resection.

Prognostic significance of the preoperative hemoglobin to albumin ratio for the short-term survival of gastric cancer patients

BACKGROUND

Hemoglobin and albumin are associated with the prognosis of gastric cancer (GC) patients. However, the prognostic value of the hemoglobin to albumin ratio (HAR) for the short-term survival of GC patients with D2 radical resection has not been studied.

AIM

To investigate the significance of the HAR in evaluating the short-term survival of GC patients after D2 radical resection and to construct a nomogram to predict the prognosis in GC patients after surgery, thus providing a reference for the development of postoperative individualized treatment and follow-up plans.

METHODS

Cox regression and Kaplan-Meier analysis was used for prognostic analysis. Logistic regression was used to analyze the relationships between HAR and the clinicopathological characteristics of the GC patients. A prognostic nomogram model for the short-term survival of GC patients was constructed by R software.

RESULTS

HAR was an independent risk factor for the short-term survival of GC patients. GC patients with a low HAR had a poor prognosis (P < 0.001). Low HAR was markedly related to high stage [odds ratio (OR) = 0.45 for II vs I; OR = 0.48 for III vs I], T classification (OR = 0.52 for T4 vs T1) and large tumor size (OR = 0.51 for ≥ 4 cm vs < 4 cm) (all P < 0.05). The nomogram model was based on HAR, age, CA19-9, CA125 and stage, and the C-index was 0.820.

CONCLUSION

Preoperative low HAR was associated with short-term survival in GC patients. The prognostic nomogram model can accurately predict the short-term survival of GC patients with D2 radical resection.

Immune Checkpoint Inhibitors as Therapy to Down-Stage Hepatocellular Carcinoma Prior to Liver Transplantation

Hepatocellular Carcinoma (HCC) is the most common liver malignancy and third leading cause of cancer death worldwide. For early- and intermediate-stage disease, liver-directed therapies for locoregional control, or down-staging prior to definitive surgical therapy with hepatic resection or liver transplantation, have been studied broadly, and are the mainstays of current treatment guidelines. As HCC incidence has continued to grow, and with more patients presenting with advanced disease, our current treatment modalities do not suffice, and better therapies are needed to improve disease-specific and overall survival. Until recently, sorafenib was the only systemic therapy utilized, and was associated with dismal results. The advent of immuno-oncology has been of significant interest, and has changed the paradigm of therapy for HCC. Lately, combination regimens including atezolizumab plus bevacizumab; durvalumab plus tremelimumab; and pembrolizumab plus Lenvatinib have shown impressive responses of between 25-35%; this is much higher than responses observed with single agents. Complete responses with checkpoint inhibitor therapy have been observed in advanced-stage HCC patients. These dramatic results have naturally led to several questions. Can or should checkpoint inhibitors, or other immunotherapy combinations, be used routinely before resection or transplant? Is there a synergistic effect of immunotherapy with locoregional therapy, and will pre-treatment increase disease-free survival after surgical intervention? Is it immunologically safe to use these therapies prior to transplantation? Much is still to be learned in terms of the dosing, timing, and overall utility of the use of immune checkpoint inhibitors for pre-transplant care and down-staging. More studies will be needed to understand the management of adverse events while maximizing the therapeutic window of these agents. In this review, we look at the current data on therapy with immune checkpoint inhibitors in advanced HCC, with a focus on pre-transplant treatment prior to liver transplant.

Nomogram for prediction of long-term survival with hepatocellular carcinoma based on NK cell counts

INTRODUCTION

Among all immune cells, natural killer (NK) cells play an important role as the first line of defense against tumor. The purpose of our study is to observe whether the NK cell counts can predict the overall survival of patients with hepatocellular carcinoma (HCC).

METHODS

To develop a novel model, from January 2010 to June 2015, HCC patients enrolled in Beijing Ditan hospital were divided into training and validation cohort. Cox multiple regression analysis was used to analyze the independent risk factors for 1-year, 3-year and 5-year overall survival (OS) of patients with HCC, and the nomogram was used to establish the prediction model. In addition, the decision tree was established to verify the contribution of NK cell counts to the survival of patients with HCC.

RESULTS

The model used in predicting overall survival of HCC included six variables (namely, NK cell counts, albumin (ALB) level, alpha-fetoprotein (AFP) level, portal vein tumor thrombus (PVTT), tumor number and treatment). The C-index of nomogram model in HCC patients predicting 1-year, 3-year and 5-year overall survival was 0.858, 0.788 and 0.782 respectively, which was higher than tumor-lymph node-metastasis (TNM) staging system, Okuda, model for end-stage liver disease (MELD), MELD-Na, the Chinese University Prognostic Index (CUPI) and Japan Integrated Staging (JIS) scores (p < 0.001). The decision tree showed the specific 5-year OS probability of HCC patients under different risk factors, and found that NK cell counts were the third in the column contribution.

CONCLUSIONS

Our study emphasizes the utility of NK cell counts for exploring interactions between long-term survival of HCC patients and predictor variables.

A Novel Prognostic Model for Identifying the Risk of Hepatocellular Carcinoma Based on Angiogenesis Factors

Hepatocellular carcinoma (HCC) is the most common primary liver cancer with poor prognosis. An optimized stratification of HCC patients to discriminate clinical benefit regarding different degrees of malignancy is urgently needed because of no effective and reliable prognostic biomarkers currently. HCC is typically characterized by rich vascular. The dysregulated vascular endothelial growth factor was proved a pivotal regulator of the development of HCC. Therefore, we investigated the capability of angiogenic factors (AFs) in stratifying patients and constructed a prognostic risk model. A total of 6 prognostic correlated AFs (GRM8, SPC25, FSD1L, SLC386A, FAM72A and SLC39A10) were screened via LASSO Cox regression, which provided the basis for developing a novel prognostic risk model. Based on the risk model, HCC patients were subdivided into high-risk and low-risk groups. Kaplan-Meier curve indicated that patients in the high-risk group have a lower survival rate compared with those in the low-risk group. The prognostic model showed good predictive efficacy, with AUCs reaching 0.802 at 1 year, 0.694 at 2 years, and 0.672 at 3 years. Univariate and multivariate cox regression analysis demonstrated that the risk score had significant prognostic value and was an independent prognostic factor for HCC. Moreover, this model also showed a good diagnostic positive rate in the ICGC-LIRI-JP and GSE144269. Finally, we demonstrated the efficacy of the AF-risk model in HCC patients following sorafenib adjuvant chemotherapy. And revealed the underlying molecular features involving tumor stemness, immune regulation, and genomic alterations associated with the risk score. Based on a large population, we established a novel prognostic model based on 6 AFs to help identify HCC patients with a greater risk of death. The model may provide a reference for better clinical management of HCC patients in the era of cancer precision medicine.

Proposal and Validation of a Novel Scoring System for Hepatocellular Carcinomas Beyond Curability Borders

Optimal scoring system for clinical prognostic factors in patients with unresectable hepatocellular carcinoma (HCC) is currently uncertain. We aimed to develop and externally validate an easy to use tool, particularly for this population, and named it the "unresectable hepatocellular carcinoma prognostic index" (UHPI). We evaluated the data of patients with treatment-naive unresectable HCC who were diagnosed in the training center from 2010 to 2019 (n = 209). A simple prognostic model was developed by assigning points for each covariate in proportion to the beta coefficients in the Cox multivariable model. Predictive performance and distinction ability of the UHPI were further evaluated in an independent European validation cohort (n = 147) and compared with 11 other available models. A simple scoring system was derived, assigning 0.5/1/2 scores for six independent covariates including, the Child-Pugh score, Eastern Cooperative Oncology Group performance status, maximum tumor size, vascular invasion or extrahepatic metastasis, lymph node involvement, and alpha-fetoprotein. The UHPI score, ranging from 0 to 6, showed superior performance in prognosis prediction and outperformed 11 other staging or prognostic models, giving the highest homogeneity (c-index, 6-month and 1-year area under the receiver operator characteristic curves), lowest Akaike information criterion, and -2 log-likelihood ratio values. The UHPI score allocated well the risk of patients with unresectable HCC for mortality within the first year, using two cut-off values (low-risk, <0.5; intermediate-risk, 0.5-2; high-risk, >2). Conclusion: The UHPI score can predict prognosis better than other systems in subjects with unresectable HCC and can be used in clinical practice or trials to estimate the 6-month and 1-year survival probabilities for this group.

Patient stratification in hepatocellular carcinoma: impact on choice of therapy

INTRODUCTION

HCC comprises around 60 to 80% of all primary liver cancers and exhibits wide geographical variability. Appropriate treatment allocation needs to include both patient and tumor characteristics.

AREAS COVERED

Current HCC classification systems to guide therapy are either liver function-centric and evaluate physiologic liver function to guide therapy or prognostic stratification classification systems broadly based on tumor morphologic parameters, patient performance status, and liver reserve assessment. This review focuses on different classification systems for HCC, their strengths, and weaknesses as well as the use of artificial intelligence in improving prognostication in HCC.

EXPERT OPINION

Future HCC classification systems will need to incorporate clinic-pathologic data from a multitude of sources and emerging therapies to develop patient-specific treatment plans targeting a patient's unique tumor profile.

Prognostic Value of Microvascular Invasion in Eight Existing Staging Systems for Hepatocellular Carcinoma: A Bi-Centeric Retrospective Cohort Study

Background

Microvascular invasion (MVI) is a significant risk factor affecting survival outcomes of patients after R0 liver resection (LR) for hepatocellular carcinoma (HCC). However, whether the existing staging systems of hepatocellular carcinoma can distinguish the prognosis of patients with MVI and the prognostic value of MVI in different subtypes of hepatocellular carcinoma remains to be clarified.

Methods

A dual-center retrospective data set of 1,198 HCC patients who underwent R0 LR was included in the study between 2014 and 2016. Baseline characteristics and staging information were collected. Homogeneity and modified Akaike information criterion (AICc) were compared between each system. And the prognostic significance of MVI for overall survival (OS) was studied in each subgroup.

Results

In the entire cohort, there were no significant survival differences between Cancer of the Liver Italian Program (CLIP) score 2 and 3 (p = 0.441), and between Taipei Integrated Scoring System (TIS) score 3 and 4 (p = 0.135). In the MVI cohort, there were no significant survival differences between Barcelona Clinic Liver Cancer stages B and C (p=0.161), CLIP scores 2 and 3 (p = 0.083), TIS scores 0 and 1 (p = 0.227), TIS scores 2 and 3 (p =0.794), Tokyo scores 3 and 4 (p=0.353), and American Joint Committee on Cancer Tumor-Node-Metastasis 7^th stage I and II (p=0.151). Among the eight commonly used HCC staging systems, the Hong Kong Liver Cancer (HKLC) staging system showed the highest homogeneity and the lowest AICc value in both the entire cohort and MVI cohort. In each subgroup of the staging systems, MVI generally exhibited poor survival outcomes.

Conclusions

The HKLC staging system was the most accurate model for discriminating the prognosis of MVI patients, among the eight staging systems. Meanwhile, our findings suggest that MVI may be needed to be incorporated into the current HCC staging systems as one of the grading criteria.

Risk factors for cancer-specific survival in elderly gastric cancer patients after curative gastrectomy

BACKGROUND/OBJECTIVES

This study aimed to investigate cancer-specific survival (CSS) and associated risk factors in elderly gastric cancer (EGC) patients.

SUBJECTS/METHODS

EGC patients (≥ 70 yrs) who underwent curative gastrectomy between January 2013 and December 2017 at our hospital were included. Clinicopathologic characteristics and survival data were collected. Receiver operating characteristic (ROC) analysis was used to extract the best cutoff point for body mass index (BMI). A Cox proportional hazards model was used to determine the risk factors for CSS.

RESULTS

In total, 290 EGC patients were included, with a median age of 74.7 yrs. The median follow-up time was 31 (1–77) mon. The postoperative 1-yr, 3-yr and 5-yr CSS rates were 93.7%, 75.9% and 65.1%, respectively. Univariate analysis revealed risk factors for CSS, including age (hazard ratio [HR] = 1.08; 95% confidence interval [CI], 1.01–1.15), intensive care unit (ICU) admission (HR = 1.73; 95% CI, 1.08–2.79), nutritional risk screening (NRS 2002) score ≥ 5 (HR = 2.33; 95% CI, 1.49–3.75), and preoperative prognostic nutrition index score < 45 (HR = 2.06; 95% CI, 1.27–3.33). The ROC curve showed that the best BMI cutoff value was 20.6 kg/m². Multivariate analysis indicated that a BMI ≤ 20.6 kg/m² (HR = 2.30; 95% CI, 1.36–3.87), ICU admission (HR = 1.97; 95% CI, 1.17–3.30) and TNM stage (stage II: HR = 5.56; 95% CI, 1.59–19.43; stage III: HR = 16.20; 95% CI, 4.99–52.59) were significantly associated with CSS.

CONCLUSIONS

Low BMI (≤ 20.6 kg/m²), ICU admission and advanced pathological TNM stages (II and III) are independent risk factors for CSS in EGC patients after curative gastrectomy. Nutrition support, better perioperative management and early diagnosis would be helpful for better survival.

Systematic review and meta-analysis of validated prognostic models for resected hepatocellular carcinoma patients

BACKGROUND

Many prognostic models for Hepatocellular Carcinoma (HCC) have been developed to inform patients and doctors about individual prognosis. Previous reviews of these models were qualitative and did not assess performance at external validation. We assessed the performance of prognostic models for HCC and set a benchmark for biomarker studies.

METHODS

All externally validated models predicting survival for patients with resected HCC were systematically reviewed. After selection, we extracted descriptive statistics and aggregated c-indices using meta-analysis.

RESULTS

Thirty-eight validated prognostic models were included. Models used on average 7 (IQR:4-9) prognostic factors. Tumor size, tumor number, and vascular invasion were almost always included. Alpha-fetoprotein (AFP) was commonly incorporated since 2007. Recently, the more subjective items ascites and encephalopathy have been dropped. Eight established models performed poor to moderate at external validation, with a pooled C-index below 0.7; including the Barcelona Clinic Liver Cancer (BCLC) system, the American Joint Committee on Cancer (AJCC) 7th edition, the Cancer of the Liver Italian (CLIP) Program, and the Japan Integrated Staging (JIS) score. Out of 24 prognostic models predicting OS, only 6 (25%) had good performance at external validation with pooled C-indices above 0.7; the Li-post (0.77), Li-OS (0.74), Yang-pre (0.74), Yang-post (0.76), Shanghai-score (0.70), and Wang-nomogram (0.71). Models improved over time, but overall performance and study quality remained low.

CONCLUSIONS

Six validated prognostic models demonstrated good performance for predicting survival after resection of HCC. These models can guide patients and doctors and are a benchmark for future models incorporating novel biomarkers.

Development of a Prognostic Scoring System for Hepatocellular Carcinoma Patients With Main Portal Vein Tumor Thrombus Undergoing Conventional Transarterial Chemoembolization: An Analysis of 173 Patients

Background

Patients with hepatocellular carcinoma (HCC) with main portal vein tumor thrombus (mPVTT) have poor prognosis. Promising systemic therapies, such as target therapies, have limited benefits. The purpose of this study is to retrospectively evaluate the benefits of conventional TACE (c-TACE) and to establish a prognostic stratification of HCC patients with mPVTT.

Methods

This is a single center retrospective study conducted over 5 years (duration of performing c-TACE), on consecutive HCC patients with mPVTT receiving c-TACE. Univariable and multivariable analysis were used to explore factors independently associated with overall survival (OS). Based on Cox-regression analysis, prognostic models were developed and internally validated by bootstrap methods. Discrimination and performance were measured by Akaike information criterion, concordance index, and likelihood ratio test.

Results

A total of 173 patients were included. Median OS was 6.0 months (95%CI: 3.92~8.08). The independent variables correlated with survival were largest tumor diameter, tumor number, mPVTT extension, and AFP. In the final model, patients were assigned 2 points if largest tumor diameter ≥8 cm, or tumor number ≥2, 1point if main trunk was complete obstructed, or AFP ≥400 ng/ml. By summing up these points, patients were divided into three risk groups according to the score at the 15rd and 85th percentiles, in which median OS were 18, 7, and 3.5months, respectively (p<0.001). The model shown optimal discrimination, performance, and calibration.

Conclusions

c-TACE could provide survival benefits in HCC patients with mPVTT and the proposed prognostic stratification may help to identify good candidates for the treatment, and those for whom c-TACE may be futile.

Development and Validation of a Model Including Distinct Vascular Patterns to Estimate Survival in Hepatocellular Carcinoma

IMPORTANCE

Because of tumor heterogeneity, traditional clinical variables remain insufficient to predict recurrence, which impairs long-term survival among patients undergoing radical hepatectomy for hepatocellular carcinoma (HCC). Vessels encapsulating tumor clusters (VETC) constitute a novel vascular pattern distinct from microvascular invasion (MVI), representing biological aggressiveness of HCC.

OBJECTIVE

To establish a model to estimate individualized recurrence-free survival (RFS) in HCC by integrating VETC and MVI.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study included 498 patients undergoing radical hepatectomy for HCC from 5 academic centers in China from January 1, 2013, to December 31, 2016, and consisted of 3 cohorts: training (243 [48.8%]), internal validation (122 [24.5%]), and external validation (133 [26.7%]). Follow-up was completed on March 30, 2020, and the data were analyzed from December 1 to 31, 2020.

EXPOSURES

VETC, MVI, tumor number, and maximum tumor size.

MAIN OUTCOMES AND MEASURES

The primary end point was RFS. The risk score for relative recurrence and nomogram for absolute RFS probability were derived from the final model, which contained variables recommended by multivariate least absolute shrinkage and selection operator Cox proportional hazards regression analysis. Their performance was quantified using the Harrell concordance index (C index), the time-dependent area under the receiver operating characteristic curve, and calibration curves and was compared with 6 prognostic systems. Recurrence-free survival was estimated by the Kaplan-Meier method, and RFS curves were compared using a log-rank test.

RESULTS

Among the 498 patients, 432 (86.7%) were men; the mean (SD) age at diagnosis was 51.4 (11.3) years. Independent predictors for RFS identified included VETC, MVI, tumor number, and maximum tumor size, which were incorporated into the multivariate model (VMNS model). The C index (0.702; 95% CI, 0.653-0.752) for the VMNS score of the training cohort was significantly higher than those of 6 conventional systems (0.587 [95% CI, 0.535-0.638] to 0.657 [95% CI, 0.606-0.708]). Different recurrence risk groups defined by the VMNS score showed significantly different 2-year RFS (low-risk group, 81.4% [SE, 0.036]; medium-risk group, 62.1% [SE, 0.054]; high-risk group, 30.1% [SE, 0.079]; P < .001). Calibration curves of the VMNS nomogram showed good agreement between the nomogram-predicted RFS probability and actual RFS proportion. The internal and external validation cohorts confirmed the results.

CONCLUSIONS AND RELEVANCE

The VMNS model enabled individualized prognostication of RFS in patients with HCC undergoing curative resection.

Preoperative Albumin-to-Globulin Ratio Predicts Prognosis in Hepatocellular Carcinoma: A Cohort Study Including Non-Hepatitis Virus-Infected Patients

INTRODUCTION

We evaluated the prognostic significance of the preoperative albumin-to-globulin ratio (AGR) in patients with hepatocellular carcinoma (HCC) with various liver etiologies.

METHODS

We retrospectively analyzed 157 patients with HCC between July 2010 and February 2021. The relationship between clinicopathological variables was investigated using univariate and multivariate analyses. Statistical significance was set at p < 0.05.

RESULTS

The mean overall survival (OS) was 24.5 months. The 1-, 3-, and 5-year OS rates were 90.4%, 81.2%, and 68.7%, respectively. Patients were classified into 2 groups: AGR <1.16 (low-AGR group; n = 43) and AGR ≥1.16 (high-AGR group; n = 114). In univariate analysis, OS was significantly reduced in patients with a low AGR (AGR <1.16), an alpha-fetoprotein level ≥25 ng/mL, a tumor size ≥3.5 cm, microvascular invasion, and poor tumor differentiation. In multivariate analysis, a low AGR (hazard ratio [95% confidence interval]) (2.394 [1.092-5.213]; p = 0.030) and microvascular invasion (2.268 [1.019-5.169]; p = 0.045) were independent predictors of OS.

DISCUSSION/CONCLUSION

A low AGR was significantly associated with poor OS in patients with HCC, regardless of liver etiology. This may assist in treatment stratification and better management of patients with HCC.

Prognostic nomogram predicting survival of patients with unresectable hepatocellular carcinoma after hepatic arterial infusion chemotherapy

BACKGROUND AND AIM

Hepatic arterial infusion chemotherapy (HAIC) has shown encouraging efficacy in the treatment of hepatocellular carcinoma (HCC). This study aims to establish and validate a novel nomogram to predict individualized survival outcomes for patients with unresectable HCC after HAIC.

METHODS

Between January 2016 and December 2018, 463 patients diagnosed with HCC who initially received HAIC were included in this study (training cohort: n = 308; validation cohort: n = 153). The prognostic nomogram was constructed based on the training cohort using the independent predictors assessed by the multivariate Cox proportional hazards model. The predictive accuracy and discriminative ability of the model were evaluated by the concordance index (C-index), calibration curve and area under the time-dependent receiver operating characteristic (tdAUC) curve.

RESULTS

After a median follow-up of 35.4 months, 358 patients had died. Six factors, including C-reactive protein, albumin-bilirubin grade, alpha fetoprotein, extrahepatic metastasis, portal vein invasion and tumor size, were selected to establish the nomogram. In the training cohort, the C-index of the nomogram was 0.710, which was significantly better than that of six conventional staging systems (P < 0.001), and the nomogram had a higher tdAUC over time. The calibration curve showed good agreement between the predicted probability and actual outcome. According to specified values, the nomogram stratified patients into three or four risk groups (P < 0.001). Similar findings could be observed in the validation cohort.

CONCLUSION

The nomogram in this study accurately predicted the OS of patients with unresectable HCC after HAIC.

Radiomics-based model using gadoxetic acid disodium-enhanced MR images: associations with recurrence-free survival of patients with hepatocellular carcinoma treated by surgical resection

PURPOSE

To develop a prediction model that combined magnetic resonance images (MRI)-based radiomics features with clinical factors to predict recurrence-free survival (RFS) of hepatocellular carcinoma (HCC) patients treated with surgical resection.

METHODS

HCC patients treated with surgical resection (n = 153) were randomly divided into training (n = 107) and validation (n = 46) datasets. The volumes of interest were manually outlined around the lesion and additional 2 mm and 5 mm peritumoral areas were created with automated dilatation in MRI to extract tumoral (T) and peritumoral (PT) radiomics features. The radiomics models were constructed using least absolute shrinkage and selection operator Cox regression. The combined model incorporated clinical factors and radiomics features using multivariable Cox regression based on the Akaike information criterion principle. Predictive performance of different models were evaluated by receiver operating characteristic (ROC) curves, decision curves, and calibration curves.

RESULTS

Among the radiomics models, similar performance was observed in the 2 mm and 5 mm PT models (C-index both 0.657), which were better than the T model or T + PT model (C-index 0.607 and 0.641, respectively) in the validation dataset, whereas the model combined with the three identified clinical risk factors showed the best performance (C-index 0.725). Results of the ROC curves, decision curves, and the calibration curves indicated that the combined model and the derived nomogram had better prediction performance, greater clinical benefits, and fair calibration efficiency.

CONCLUSION

The prediction model that combined MRI radiomics signatures with clinical factors can effectively predict the prognosis of patients with HCC treated with surgical resection.

Survival prognostic factors in patients with acute myeloid leukemia using machine learning techniques

This paper identifies prognosis factors for survival in patients with acute myeloid leukemia (AML) using machine learning techniques. We have integrated machine learning with feature selection methods and have compared their performances to identify the most suitable factors in assessing the survival of AML patients. Here, six data mining algorithms including Decision Tree, Random Forrest, Logistic Regression, Naive Bayes, W-Bayes Net, and Gradient Boosted Tree (GBT) are employed for the detection model and implemented using the common data mining tool RapidMiner and open-source R package. To improve the predictive ability of our model, a set of features were selected by employing multiple feature selection methods. The accuracy of classification was obtained using 10-fold cross-validation for the various combinations of the feature selection methods and machine learning algorithms. The performance of the models was assessed by various measurement indexes including accuracy, kappa, sensitivity, specificity, positive predictive value, negative predictive value, and area under the ROC curve (AUC). Our results showed that GBT with an accuracy of 85.17%, AUC of 0.930, and the feature selection via the Relief algorithm has the best performance in predicting the survival rate of AML patients.

Management of Hepatocellular Carcinoma in Japan: JSH Consensus Statements and Recommendations 2021 Update

The Clinical Practice Manual for Hepatocellular Carcinoma was published based on evidence confirmed by the Evidence-based Clinical Practice Guidelines for Hepatocellular Carcinoma along with consensus opinion among a Japan Society of Hepatology (JSH) expert panel on hepatocellular carcinoma (HCC). Since the JSH Clinical Practice Guidelines are based on original articles with extremely high levels of evidence, expert opinions on HCC management in clinical practice or consensus on newly developed treatments are not included. However, the practice manual incorporates the literature based on clinical data, expert opinion, and real-world clinical practice currently conducted in Japan to facilitate its use by clinicians. Alongside each revision of the JSH Guidelines, we issued an update to the manual, with the first edition of the manual published in 2007, the second edition in 2010, the third edition in 2015, and the fourth edition in 2020, which includes the 2017 edition of the JSH Guideline. This article is an excerpt from the fourth edition of the HCC Clinical Practice Manual focusing on pathology, diagnosis, and treatment of HCC. It is designed as a practical manual different from the latest version of the JSH Clinical Practice Guidelines. This practice manual was written by an expert panel from the JSH, with emphasis on the consensus statements and recommendations for the management of HCC proposed by the JSH expert panel. In this article, we included newly developed clinical practices that are relatively common among Japanese experts in this field, although all of their statements are not associated with a high level of evidence, but these practices are likely to be incorporated into guidelines in the future. To write this article, coauthors from different institutions drafted the content and then critically reviewed each other's work. The revised content was then critically reviewed by the Board of Directors and the Planning and Public Relations Committee of JSH before publication to confirm the consensus statements and recommendations. The consensus statements and recommendations presented in this report represent measures actually being conducted at the highest-level HCC treatment centers in Japan. We hope this article provides insight into the actual situation of HCC practice in Japan, thereby affecting the global practice pattern in the management of HCC.

Assessment of clinical factors affecting outcome of myasthenia gravis

INTRODUCTION/AIMS

In myasthenia gravis (MG) therapy, achieving Myasthenia Gravis Foundation of America minimal manifestation (MM) or better status is proposed as a desirable target. However, this level of control is often not achieved and clinical factors affecting prognosis remain unclear.

METHODS

Participants were 104 consecutive patients with MG who visited Osaka Medical College Hospital. We retrospectively assessed the association of clinical and laboratory features at baseline with prognosis. Eighty patients who achieved MM or better status were classified as the good outcome group and the remaining 24 patients were classified as the poor outcome group.

RESULTS

The rate of dysphagia at baseline was significantly higher in the poor outcome group than in the good outcome group (P = .002). The levels of serum total protein and albumin at baseline were both significantly lower in the poor outcome group than in the good outcome group (P = .036 and P = .014, respectively). In addition, Controlling Nutritional Status scores at baseline were significantly higher in the poor outcome group than in the good outcome group (P = .043). Multivariate analysis using a Cox proportional hazards model showed that dysphagia (hazard ratio [HR], 6.92; 95% confidence interval [CI], 1.49-40.31) and hypoalbuminemia (HR, 2.57; 95% CI, 1.04-6.57) at baseline were risk factors that predicted prognosis.

DISCUSSION

These findings suggest that dysphagia and hypoalbuminemia at baseline are associated with outcomes and are predictive risk factors for poorer outcomes in patients with MG.

Selecting an Optimal Staging System for Intermediate-Stage Hepatocellular Carcinoma: Comparison of 9 Currently Used Prognostic Models

Purpose

It remains unknown which staging system is best in predicting the survival of patients with intermediate stage hepatocellular carcinoma (HCC). We aimed to investigate the performance of nine currently used HCC staging systems.

Patients and Methods

Between 2005 and 2014, a large cohort of 880 consecutive patients with intermediate stage HCC and sufficient data for utilization in all staging systems were enrolled. The prognostic performance of each staging system was compared. Independent prognostic variables were also identified.

Results

Multivariate analysis revealed that alkaline phosphatase (ALP), aspartate aminotransferase (AST), etiology, alpha-fetoprotein (AFP), Child-Pugh stage, tumor size, and tumor number were independent prognostic factors for survival. In the entire cohort, the Hong Kong Liver Cancer (HKLC) staging system was associated with the highest Harrell’s c-index and lowest Akaike information criterion value in comparison with other systems. In subgroup analysis according to treatment strategy, the HKLC staging system remained the best prognostic model in patients undergoing hepatic resection (n=222) or transarterial chemoembolization (n=658). Additional prognostic factors of AST, ALP, etiology, and AFP improved the discriminatory ability of HKLC.

Conclusion

The HKLC staging system is stable and consistently the best prognostic model in all patients with intermediate-stage HCC and in patients subjected to different treatment strategies. Selecting an optimal staging system is helpful in improving the design of future clinical trials in intermediate stage HCC.

Overview of Prognostic Systems for Hepatocellular Carcinoma and ITA.LI.CA External Validation of MESH and CNLC Classifications

Prognostic assessment in patients with HCC remains an extremely difficult clinical task due to the complexity of this cancer where tumour characteristics interact with degree of liver dysfunction, patient general health status, and a large span of available treatment options. Several prognostic systems have been proposed in the last three decades, both from the Asian and European/North American countries. Prognostic scores, such as the CLIP score and the recent MESH score, have been generated on a solid statistical basis from real life population data, while staging systems, such as the BCLC scheme and the recent CNLC classification, have been created by experts according to recent HCC prognostic evidences from the literature. A third category includes combined prognostic systems that can be used both as prognostic scores and staging systems. A recent example is the ITA.LI.CA prognostic system including either a prognostic score and a simplified staging system. This review focuses first on an overview of the main prognostic systems for HCC classified according to the above three categories, and, second, on a comprehensive description of the methodology required for a correct comparison between different systems in terms of prognostic performance. In this second section the main studies in the literature comparing different prognostic systems are described in detail. Lastly, a formal comparison between the last prognostic systems proposed for each of the above three categories is performed using a large Italian database including 6882 HCC patients in order to concretely apply the comparison rules previously described.

Monofocal hepatocellular carcinoma: How much does size matter?

BACKGROUND & AIMS

According to the Barcelona Clinic Liver Cancer (BCLC) staging system, monofocal hepatocellular carcinoma (HCC) is classified as early (BCLC A) irrespective of its size, even though controversies still exist regarding staging and treatment of large tumours. We aimed at evaluating the appropriate staging and treatment for large (>5 cm) monofocal (HCC).

METHODS

From the Italian Liver Cancer database, we selected 924 patients with small early monofocal HCC (2-5 cm; SEM-HCC), 163 patients with larger tumours (>5 cm; LEM-HCC) and 1048 intermediate stage patients (BCLC B).

RESULTS

LEM-HCC patients had a worse overall survival (OS) than SEM-HCC (31.0 vs 49.0 months; P < .0001), and this was confirmed at multivariate analysis (HR 1.63, 95% CI 1.29-2.05; P < .0001). The small difference in OS between LEM-HCC and BCLC B patients (31.0 vs 27.0 months; P = .03) disappeared in the multivariate model (HR 0.98, 95% CI 0.77-1.25; P = .89). In all monofocal tumours, treatment was the strongest independent predictor of survival, with a progressively decreasing survival benefit moving from "curative" to "palliative" therapies. The survival of resected patients with LEM-HCC was significantly shorter than that of SEM-HCC (44.0 vs 78.0 months; P = .002), but liver resection provided the highest survival benefit in both groups compared to other treatments.

CONCLUSIONS

Monofocal HCC larger than 5 cm should not be staged as BCLC A and either a different staging system or a different subgrouping of patients (e.g. BCLC AB) should be used. Liver resection, if feasible, remains the recommended treatment for all these patients.

A Machine Learning Approach Yields a Multiparameter Prognostic Marker in Liver Cancer

A number of staging systems have been developed to predict clinical outcomes in hepatocellular carcinoma (HCC). However, no general consensus has been reached regarding the optimal model. New approaches such as machine learning (ML) strategies are powerful tools for incorporating risk factors from multiple platforms. We retrospectively reviewed the baseline information, including clinicopathologic characteristics, laboratory parameters, and peripheral immune features reflecting T-cell function, from three HCC cohorts. A gradient-boosting survival (GBS) classifier was trained with prognosis-related variables in the training dataset and validated in two independent cohorts. We constructed a 20-feature GBS model classifier incorporating one clinical feature, 14 laboratory parameters, and five T-cell function parameters obtained from peripheral blood mononuclear cells. The GBS model-derived risk scores demonstrated high concordance indexes (C-indexes): 0.844, 0.827, and 0.806 in the training set and validation sets 1 and 2, respectively. The GBS classifier could separate patients into high-, medium- and low-risk subgroups with respect to death in all datasets (P < 0.05 for all comparisons). A higher risk score was positively correlated with a higher clinical stage and the presence of portal vein tumor thrombus (PVTT). Subgroup analyses with respect to Child-Pugh class, Barcelona Clinic Liver Cancer stage, and PVTT status supported the prognostic relevance of the GBS-derived risk algorithm independent of the conventional tumor staging system. In summary, a multiparameter ML algorithm incorporating clinical characteristics, laboratory parameters, and peripheral immune signatures offers a different approach to identify patients with the greatest risk of HCC-related death.

Comparison between hepatocellular carcinoma prognostic scores: A 10-year single-center experience and brief review of the current literature

BACKGROUND

Hepatocellular carcinoma (HCC) represents the most common primitive liver malignancy. A relevant concern involves the lack of agreement on staging systems, prognostic scores, and treatment allocation algorithms. 

AIM

To compare the survival rates among already developed prognostic scores.

METHODS

We retrospectively evaluated 140 patients with HCC diagnosed between February 2006 and November 2017. Patients were categorized according to 15 prognostic scoring systems and estimated median survivals were compared with those available from the current medical literature.

RESULTS

The median overall survival of the cohort of patients was 35 (17; 67) mo, and it was statistically different in relation to treatment choice, ultrasound surveillance, and serum alpha-fetoprotein. The Italian Liver Cancer (ITA.LI.CA) tumor staging system performed best in predicting survival according to stage allocation among all 15 evaluated prognostic scores. Using the ITA.LI.CA prognostic system, 28.6%, 40.7%, 22.1%, and 8.6% of patients fell within stages 0-1, 2-3, 4-5 and > 5 respectively. The median survival was 57.9 mo for stages 0-1, 43 mo for stages 2-3, 21.7 mo for stages 4-5, and 10.4 mo for stage > 5. The 1-, 3-, and 5-year survival rates were respectively 95%, 65%, and 20%, for stages 0-1; 94.7%, 43.9% and 26.3% for stages 2-3; 71%, 25.8% and 16.1% for stages 4-5; and 50%, 16.7% and 8.3% for stage > 5. At the same time, although statistically significant in prognostic stratification, the most commonly used Barcelona Clinic Liver Cancer system showed one of the most relevant differences in median survival, especially for stages A and C, when compared to the medical literature. In fact, 10.7%, 59.3%, 27.1%, 1.4%, and 0% of patients were stratified into stages 0, A, B, C, and D respectively. The median survival was > 81.1 mo for stage 0, 44.9 mo for stage A, 21.3 mo for stage B, and 3.1 mo for stage C. The 1-, 3-, and 5-year survival rates were respectively 86.7%, 60%, and 46.7% for stage 0; 91.6%, 50.6%, and 20.5% for stage A; 73.7%, 23.7% and 13.2% for stage B; and 2%, 0% and 0% for stage C.

CONCLUSION

Survival analysis shows excellent prognostic ability of the ITA.LI.CA scoring system compared to other staging systems.

A Novel Pathological Scoring System for Hepatic Cirrhosis with Hepatocellular Carcinoma

Purpose

This study aimed to propose an effective quantitative pathological scoring system and to establish nomogram to assess the stage of cirrhosis and predict postoperative survival of hepatocellular carcinoma (HCC) with cirrhosis patients after hepatectomy.

Methods

The scoring system was based on a retrospective study on 163 patients who underwent partial hepatectomy for HCC with cirrhosis. The clinicopathological and follow-up data of 163 HCC with cirrhosis patients who underwent hepatectomy in our hospital from 2010 to 2014 were retrospectively reviewed. A scoring system was established based on the total value of independent predictive factors of cirrhosis. The results were validated using 97 patients operated on from 2011 to 2015 at the same institution. Nomogram was then formulated using a multivariate Cox proportional hazards model to analyze.

Results

The scoring system was ultimately composed of 4 independent predictive factors and was divided into 3 levels. The new cirrhosis system score strongly correlated with Child–Pugh score (r=0.8058, P<0.0001) 3 months after surgery; higher cirrhosis system scores predicted poorer liver function and stronger liver damage 3 months after surgery. Then, a four-factor nomogram for survival prediction was established. The concordance indices were 0.79 for the survival-prediction nomogram. The calibration curves showed good agreement between predictions by the nomogram and actual survival outcomes.

Conclusion

This new scoring system of cirrhosis can help us predict the liver function and liver injury 3 months after surgery, and the nomogram enabled accurate predictions of risk of overall survival in patients of HCC with cirrhosis after hepatectomy.

Relationship between presarcopenia and event occurrence in patients with primary hepatocellular carcinoma

Presarcopenia is a prognostic factor in patients with hepatocellular carcinoma (HCC). The Japan integrated staging (JIS) score is a prognostic method that combines the Child–Turcotte–Pugh classification and the tumor-node-metastasis (TNM) staging for HCC. We investigated the relationship between presarcopenia, the JIS score, and prognosis in patients with primary HCC. This retrospective study included 153 patients with primary HCC who were hospitalized from October 2011 to March 2018 at Municipal Hospital of Kofu. The skeletal muscle mass was measured using simplified psoas muscle mass index (PMI) based on CT imaging, and PMI using the volume analyzer SYNAPSE VINCENT ver3.0. We diagnosed presarcopenia based on the cut off value according to the assessment criteria for sarcopenia in liver disease defined by the Japan Society of Hepatology. Forty-three patients (28%) were diagnosed with presarcopenia. The median event-free survival was significantly worse in patients with presarcopenia than those without presarcopenia (P = 0.016). In multivariate analysis, presence of presarcopenia, JIS score ≥3, alpha-fetoprotein ≥200 ng/ml, and prothrombin induced by vitamin K absence-II ≥ 200 mAU/ml were significant prognostic factors. Among the patients with JIS scores ≥3, there was no difference in the event occurrence rate with presence of presarcopenia (P = 0.96). Among the patients with JIS scores ≤2, the median event-free-survival was significantly shorter in those with presarcopenia than those without presarcopenia (P = 0.045). Presarcopenia was an independent prognostic factor in patients with primary HCC. In patients with JIS scores ≤2, the median event-free survival was significantly shorter in those with presarcopenia compared to those without presarcopenia. In the patients with JIS scores ≥3, there was no difference in the event occurrence rates in those with and without presarcopenia.

Talin-1 Gene Expression as a Tumor Marker in Hepatocellular Carcinoma Patients: A Pilot Study

Background & Aims:

Hepatocellular Carcinoma (HCC) is the most common primary liver tumor. It is the second most common cancer in men and the sixth in women in Egypt. One of the proteins participating in the trans-endothelial migration is Talin-1. It also has a role in the formation and metastasis of different types of cancer. This study aimed to evaluate the diagnostic impact of Talin-1 gene expression in HCC Egyptian patients.

Methods:

Our study included forty HCC patients, thirty liver cirrhosis patients without HCC and thirty healthy subjects. For all groups, clinical and biochemical parameters were investigated. Tumor characteristics were assessed and tumor staging was done using Okuda, CLIP, VISUM and Tokyo staging systems. In addition, Serum Alpha-Fetoprotein (AFP) levels were assayed using Enzyme Immunoassay (EIA) and Talin-1 gene expression was assessed in the Peripheral Blood Mononuclear Cells (PBMCs) via quantitative real-time Polymerase Chain Reaction (PCR).

Results:

Talin-1 gene expression was significantly upregulated in HCC patients in comparison to cirrhotic and control subjects. The Receiver Operating Characteristic (ROC) analysis indicated that Talin-1 gene expression surpasses serum levels of AFP in the diagnosis of HCC. In particular, the cut off value of 9.5 (2-∆∆Ct) recorded an AUC of 85.7% with a sensitivity of 93.3% and specificity of 80%.

Conclusion:

Our data confirmed an évident diagnostic role of Talin-1 gene expression for HCC detection.

Prognostic model for identifying candidates for hepatectomy among patients with hepatocellular carcinoma and hepatic vein invasion

BACKGROUND

Hepatic vein tumour thrombus (HVTT) is a major determinant of survival outcomes for patients with hepatocellular carcinoma (HCC). An Eastern Hepatobiliary Surgery Hospital (EHBH)-HVTT model was established to predict the prognosis of patients with HCC and HVTT after liver resection, in order to identify optimal candidates for liver resection.

METHODS

Patients with HCC and HVTT from 15 hospitals in China were included. The EHBH-HVTT model with contour plot was developed using a non-linear model in the training cohort, and subsequently validated in internal and external cohorts.

RESULTS

Of 850 patients who met the inclusion criteria, there were 292 patients who had liver resection and 198 who did not in the training cohort, and 124 and 236 in the internal and external validation cohorts respectively. Contour plots for the EHBH-HVTT model were established to predict overall survival (OS) rates of patients visually, based on tumour diameter, number of tumours and portal vein tumour thrombus. This differentiated patients into low- and high-risk groups with distinct long-term prognoses in the liver resection cohort (median OS 34·7 versus 12·0 months; P < 0·001), internal validation cohort (32·8 versus 10·4 months; P = 0·002) and external validation cohort (15·2 versus 6·5 months; P = 0·006). On subgroup analysis, the model showed the same efficacy in differentiating patients with HVTT in peripheral and major hepatic veins, the inferior vena cava, or in patients with coexisting portal vein tumour thrombus.

CONCLUSION

The EHBH-HVTT model was accurate in predicting prognosis in patients with HCC and HVTT after liver resection. It identified optimal candidates for liver resection among patients with HCC and HVTT, including tumour thrombus in the inferior vena cava, or coexisting portal vein tumour thrombus.

An Albumin-Bilirubin (ALBI) Grade-based Prognostic Model For Patients With Hepatocellular Carcinoma Within Milan Criteria

OBJECTIVE

The Milan criteria are recommended as the major reference for liver transplantation in patients with small hepatocellular carcinoma (HCC). However, alternative anticancer treatments are often utilized due to severe donor organ shortage. This study aimed to develop and validate an albumin-bilirubin (ALBI) grade-based prognostic model to stratify survival in patients within Milan criteria undergoing nontransplant therapy.

PATIENTS AND METHODS

A total of 1655 patients were assigned into the derivation and validation cohort according to treatment modalities. Multivariate analysis was used to identify independent predictors of survival in the derivation cohort. An ALBI-based model was evaluated in the validation cohort.

RESULTS

In the Cox multivariate model, age 65 years or older (hazard ratio [HR]=1.576, P<0.001), serum α-fetoprotein (AFP) level >100 ng/mL (HR=1.671, P<0.001), ascites (HR=1.808, P<0.001), performance status 1 to 4 (HR=1.738, P<0.001), ALBI grade 2 (HR=1.827, P<0.001), and ALBI grade 3 (HR=3.589, P<0.001) were independent predictors of poor survival in the derivation cohort. An ALBI-based prognostic model with a total of 0 to 6 points was derived with the sum of 5 variables: 1 point each for age 65 years or older, AFP >100 ng/mL, presence of ascites, performance status 1 to 4, and ALBI grade 2, and 2 points for ALBI grade 3. This model can accurately predict long-term outcome in the validation cohort (P<0.001) and discriminate survival in patients stratified by curative and noncurative treatments (both P<0.001).

CONCLUSION

The proposed ALBI grade-based model is feasible in predicting survival in HCC patients within the Milan criteria, and helps identify high-risk patients who need timely liver transplantation.

Evolution of etiology, presentation, management and prognostic tool in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related death worldwide, but its current status is unclear. We aimed to investigate the evolution of etiology, presentation, management and prognostic tool in HCC over the past 12 years. A total of 3349 newly diagnosed HCC patients were enrolled and retrospectively analyzed. The comparison of survival was performed by the Kaplan-Meier method with the log-rank test. Hepatitis B and C virus infection in HCC were continuously declining over the three time periods (2004–2007, 2008–2011, 2012–2015; p < 0.001). At diagnosis, single tumor detection rate increased to 73% (p < 0.001), whereas vascular invasion gradually decreased to 20% in 2012–2015 (p < 0.001). Early stage HCC gradually increased from 2004–2007 to 2012–2015 (p < 0.001). The probability of patients receiving curative treatment and long-term survival increased from 2004–2007 to 2012–2015 (p < 0.001). The Cancer of Liver Italian Program (CLIP) and Taipei Integrated Scoring (TIS) system were two more accurate staging systems among all. In conclusion, the clinical presentations of HCC have significantly changed over the past 12 years. Hepatitis B and C virus-associated HCC became less common, and more patients were diagnosed at early cancer stage. Patient survival increased due to early cancer detection that results in increased probability to undergo curative therapies.

Development and validation of a risk score to predict the overall survival following surgical resection of hepatocellular carcinoma in non-cirrhotic liver

BACKGROUND

The aim of this study was to develop and validate a risk score to predict overall survival (OS) in patients undergoing surgical resection for hepatocellular carcinoma in non-cirrhotic liver (NC-HCC).

METHODS

Patients who underwent resection for NC-HCC between 2004 and 2013 were identified from the SEER database. A derivation set of 75% of this cohort was used to develop a risk score. This was then internally validated on the remaining patients, and externally validated using a cohort of patients from The HPB Unit, Birmingham, UK.

RESULTS

A total of 3897 patients were included from the SEER database, with a median post-diagnosis survival of 59 months. In the derivation set, multivariable analyses identified male sex, increasing tumour size, the presence of multiple tumours, bilobar tumours and major vascular invasion as adverse prognostic factors. A risk score generated from these factors was significantly predictive of OS, and was used to classify patients into low, medium and high-risk groups. These groups had a five-year OS of 69%, 51% and 19% in the internal, and 73%, 50% and 45% in the external validation sets.

CONCLUSION

The proposed risk score is useful in the selection, pre-operative consenting and counselling of patients for surgery and to allow patients to make an informed decision regarding treatment.

A New Prognostic Model Based on Albumin-Bilirubin Grade for Hepatocellular Carcinoma Beyond the Milan Criteria

BACKGROUND

The survival of patients with advanced hepatocellular carcinoma (HCC) is highly variable due to heterogeneous tumoral characteristics. We proposed and validated an albumin-bilirubin (ALBI)-based model for HCC beyond Milan criteria, the ALBI-HOME, for these patients.

METHODS

A total of 2186 patients were enrolled and randomly assigned to the derivation cohort (n = 1093) and validation cohort (n = 1093). Multivariate Cox proportional hazards model was used to determine significant prognostic factors in the derivation cohort. The performance of ALBI-HOME was evaluated in the validation cohort.

RESULTS

In the Cox model, six factors were identified as independent predictors of poor survival: ALBI grade 2 [hazard ratio (HR) 1.848, 95% confidence incidence (CI) 1.556-2.195, p < 0.001], ALBI grade 3 (HR 3.266, 95% CI 2.531-4.215, p < 0.001), serum AFP ≥ 100 ng/ml (HR 1.482, 95% CI 1.279-1.717, p < 0.001), total tumor volume ≥ 250 cm³ (HR 1.503, 95% CI 1.294-1.746, p < 0.001), ascites (HR 1.400, 95% CI 1.187-1.561, p < 0.001), performance status 0-1 (HR 1.756, 95% CI 1.485-2.076 p < 0.001), and vascular invasion or metastasis (HR 2.110, 95% CI 1.809-2.0, p < 0.001). The ALBI-HOME is based on these six parameters, and the score ranges from 0 to 7. This model was associated with the best prognostic ability among different HCC staging systems to predict survival in patients beyond Milan criteria; its ability remained consistently stable in different treatment subgroups and viral etiologies.

CONCLUSIONS

The proposed ALBI-HOME is a simple and feasible predictive model for HCC beyond Milan criteria. It demonstrates superior prognostic performance among the currently used staging systems and may help identify at-risk patients to undergo more aggressive treatments.

NIACE score refines the overall survival of hepatocellular carcinoma by Barcelona clinic liver cancer staging

BACKGROUND AND AIM

The NIACE score provides prognostic values for hepatocellular carcinoma (HCC) in European studies. We aim to evaluate the prognostic value of the NIACE score in Asian patients.

METHODS

Patients with HCC were retrospectively enrolled from a tertiary medical center in Taiwan during 2009-2014, and their clinical information were collected. The NIACE score was calculated according to the Nodular numbers, tumor Infiltration, Alpha-fetoprotein level, Child-Pugh score, and Eastern Cooperative Oncology Group score. The prognostic values of NIACE score for overall survival according to individual treatment and the Barcelona clinic liver cancer (BCLC) staging were analyzed.

RESULTS

A total of 468 patients were included with a median follow-up of 30 months. A greater NIACE score correlated with lower median survival and higher BCLC staging. Regardless of treatment modalities, NIACE scores (0, 1-1.5, 2.5-3, and 4-7) significantly predicted survival between groups (log-rank P < 0.001). Specifically, NIACE score (0, 1-1.5, 2.5-3, and 4-7) significantly predicted survival in patients receiving transarterial chemoembolization (log-rank P < 0.001). NIACE score 1, 2.5, and 4 further distinguished overall survival in BCLC A, B, and C patients, respectively (all log-rank P < 0.01). After adjustment of the confounders and the BCLC staging, NIACE score of 2.5-3 and 4-7 (vs 0) had a significantly increased risk of mortality with a hazard ratio of 4.04 (95% confidence interval: 2.14-7.64, P < 0.001) and 7.45 (95% confidence interval: 3.22-17.23, P < 0.001), respectively.

CONCLUSIONS

The NIACE score helps refine differential prognosis among BCLC A, B, and C subgroups of Asian patients with HCC, especially in those receiving transarterial chemoembolization.

Biology and significance of alpha-fetoprotein in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related deaths globally due, in part, to the majority of patients being diagnosed with intermediate or advanced stage disease. Our increased understanding of the heterogeneous molecular pathogenesis of HCC has led to significant developments in novel targeted therapies. Despite these advances, there remains a high unmet need for new treatment options. HCC is a complex disease with multiple pathogenic mechanisms caused by a variety of risk factors, making it difficult to characterize with a single biomarker. In fact, numerous biomarkers have been studied in HCC, but alpha-fetoprotein (AFP) remains the most widely used and accepted serum marker since its discovery over 60 years ago. This review summarizes the most relevant studies associated with the regulation of AFP at the gene and protein levels; the pathophysiology of AFP as a pro-proliferative protein; and the correlation of AFP with molecular HCC subclasses, the vascular endothelial growth factor pathway and angiogenesis. Also described are the historical and current uses of AFP for screening and surveillance, diagnosis, its utility as a prognostic and predictive biomarker and its role as a tumour antigen in HCC. Taken together, these data demonstrate the relevance of AFP for patients with HCC and identify several remaining questions that will benefit from future research.

Newly Proposed ALBI Grade and ALBI-T Score as Tools for Assessment of Hepatic Function and Prognosis in Hepatocellular Carcinoma Patients

BACKGROUND

Because of the rapid progression of antiviral treatment options and the increasing frequency of nonviral-related hepatocellular carcinoma (HCC) due to the aging of society, the number of HCC patients with good hepatic function has been increasing and a more detailed method of assessment of hepatic function is needed. The Child-Pugh classification (CP) is used worldwide as an assessment tool for hepatic reserve function, even though it has some weaknesses. Recently, the albumin-bilirubin (ALBI) grade, calculated based on only albumin and total bilirubin, was proposed, and recent investigations have suggested that ALBI grade instead of CP can be used as an assessment tool for hepatic function as part of therapeutic strategies such as Barcelona Clinic Liver Cancer staging and a practical guideline presented by the Japan Society of Hepatology as well for total staging scoring systems. There has been an increasing number of reports showing that it has better capability than CP for HCC patients who undergo not only curative but also palliative treatments. Transcatheter arterial chemoembolization (TACE) is a major palliative treatment used for unresectable HCC, and the idea of TACE-refractory status has been proposed to indicate the possibility of switching to a tyrosine kinase inhibitor (TKI). However, TKI administration requires a maintained hepatic reserve function, thus the importance of assessment of hepatic function in patients undergoing TACE treatments has increased. We consider that ALBI grade might also play a significant role as part of a detailed assessment of relative changes in hepatic function during treatment. In this review, we evaluate the practical usefulness of ALBI grade for assessing hepatic function and HCC prognosis.

KEY MESSAGE

A detailed assessment of hepatic function is required for recent HCC therapeutic strategies. ALBI grade may be a powerful tool to improve treatment options for affected patients.