Factors influencing the short-term and long-term survival of hepatocellular carcinoma patients with portal vein tumor thrombosis who underwent chemoembolization

A meta-analysis of the value of indocyanine green fluorescence imaging in guiding surgical resection of primary and metastatic liver cancer

OBJECTIVE

This meta-analysis aimed to evaluate the value of indocyanine green fluorescence imaging in precision resection surgery for primary and metastatic liver cancer.

METHODS

A systematic search of PubMed, Embase, Scopus, Cochrane Library, Web of Science, ScienceDirect, and major scientific websites was conducted until June 2024. Randomized controlled trials and observational studies comparing indocyanine green fluorescence imaging-guided liver cancer resection with traditional methods were included. The meta-analysis incorporated overall outcomes and subgroup outcomes based on liver cancer types (primary and metastatic). StataSE 12.0 software was used for statistical analysis after a quality assessment of the included studies.

RESULTS

Twenty studies involving 1,283 patients with liver cancer were included. The results showed that indocyanine green fluorescence imaging significantly reduced intraoperative blood loss [Weighted mean difference (WMD), -88.75; 95 % CI, -128.48 to -49.02, p < 0.05], transfusion rate [Odds ratios (OR), 0.5; 95 % CI, 0.36-0.7, p < 0.05], hospital stay duration [WMD, -1.11; 95 % CI, -1.79 to -0.43, p < 0.05], and the overall complication rate [OR, 0.59; 95 % CI, 0.44-0.79, p < 0.05]. However, no significant differences were observed in operative time or in the subgroup analysis for metastatic liver cancer.

CONCLUSION

Indocyanine green fluorescence imaging is a safe and effective intraoperative navigation technique that improves surgical outcomes and prognostic indicators in liver cancer resection. However, its efficacy in metastatic liver cancer surgery requires further validation through larger-scale, rigorous, prospective, randomized controlled trials.

A New Approach to Analysis of Clinical Data and Prognostication for Patients with Hepatocellular Carcinoma, Based Upon a Network Phenotyping Strategy (NPS) Computational Method

Objectives

There is a multi-component nature of the influences on HCC progression but integrating them has been difficult. Network phenotyping strategy (NPS) integrates all multi-component relationship facets of HCC progression and aims to lead to a new way of understanding human HCC biology.

Methods

We converted baseline patient demographics, tumor characteristics, blood hematology and liver function test results, consisting of values of 17 standard clinical variables, collected time-coherently at the index visit, into a graph-theoretical data representation.

Results

These data were analyzed by NPS, which processes the patient parameter values together with their complete relationships network. NPS identified 25 disease-progression ordered HCC phenotypes. Clinically relevant NPS results are a) Portal vein thrombosis incidence during HCC progression stratified into 5 narrow ranges; b) NPS identified patients according to aggressive, slow and intermediate tumor growth sub-types; c) Personalized prognostication of mortality was achieved by the 25 NPS phenotypes, independently optimized for respective phenotype sub-cohorts.

Conclusion

The NPS results were implemented as an internet application (https://apkatos.github.io/webpage_nps), where input of 17 clinical parameters provides the patient phenotype, phenotype-characteristic average mortality and personal survival estimate.

Development and Validation of a Novel Prognostic Nomogram Based on Platelet and CD8+T Cell Counts in Hepatocellular Carcinoma Patients with Portal Vein Tumor Thrombosis

Purpose

Portal vein tumor thrombosis (PVTT) is one of the hallmarks of advanced Hepatocellular carcinoma (HCC). Platelet (PLT) function parameters and CD8+T cells (CD8+Ts) play an important role in HCC progression and metastasis. This study is committed to establishing an efficient prognosis prediction model and exploring the combined effect of PLT and CD8+Ts on PVTT prognosis.

Patients and Methods

This retrospective study collected 932 HCC patients with PVTT from 2007 to 2017 and randomly divided them into a training cohort (n = 656) and a validation cohort (n = 276). We performed multivariable Cox and Elastic-net regression analysis, constructed a nomogram and used Kaplan-Meier survival curves to compare overall survival and progression-free survival rates in different substrata. Relationships between indicators involved were also analyzed.

Results

We found tumor number, size, treatment, PLT, γ-glutamyl transferase, alpha-fetoprotein, mean platelet volume, and CD8+Ts were related to the 5-year OS of patients with PVTT, and established a nomogram. The area under the receiver operating characteristic curve (AUCs) for predicting the 1-year OS rates were 0.767 and 0.794 in training and validation cohorts. The calibration curve and decision curve indicated its predictive consistency and strong clinical utility. We also found those with low PLT (<100*10^9/L) and high CD8+Ts (>320 cells/μL) had a better prognosis.

Conclusion

We established a well-performing prognostic model for PVTT based on platelet functional parameters and CD8+Ts, and found that PT-8 formed by PLT and CD8+Ts was an excellent predictor of the prognosis of PVTT.

Symptoms and symptom clusters in patients with hepatocellular carcinoma and commonly used instruments: An integrated review

Objective

This study aimed to synthesize the available knowledge of identifying hepatocellular carcinoma (HCC) symptoms and symptom clusters in patients with HCC and instruments used for these assessments to maximize symptom management.

Methods

Whittemore and Knafl's integrative review method was employed to guide a systematic search for literature in five databases (PubMed, ScienceDirect, Scopus, CINAHL, and ThaiJO). The retrieved articles were limited to those which were peer-reviewed, published between 2005 and 2022, and had English abstracts. All of identified studies were screened, extracted, and analyzed independently by two researchers.

Result

Fourteen articles were included in this review. They were grouped into three themes: symptoms, symptom assessment, and symptom clusters of HCC patients. Fatigue, lack of energy, stomach or abdominal pain/distension, loss of appetite, change in taste, sleep disturbance, distress, and sadness are the most prevalent symptoms reported in HCC patients. The different concurrent symptoms are related to the stage and treatment. Five types of symptom assessment instruments were commonly used (symptoms-specific HCC, general cancer symptom, measuring non-symptom constructs, measuring specific symptoms, such as fatigue, sleep disturbance, anxiety, and depression, and symptom assessment with clinical examination). Furthermore, the symptom clusters in HCC patients were classified into five categories: 1) pain-related symptoms, 2) gastrointestinal symptoms, 3) neuropsychological symptom clusters and sensory symptoms, 4) liver dysfunction-related symptom clusters, and 5) others (including sickness symptom clusters, fatigue clusters, location pain symptoms, and asymptomatic or symptomatic).

Conclusion

The findings of this review add to the body of knowledge on symptoms, symptom assessment, and symptom clusters in patients with HCC. Despite a variety of instruments being available, none covers all symptoms experienced by HCC patients. It is recommended that future studies should include larger and more homogenous samples to evaluate assessment instruments more precisely, avoid ambiguity in classifying symptoms into symptom clusters, and increase the effectiveness of symptom management.

Efficacy and Prognostic Factors of Regorafenib in the Treatment of BCLC Stage C Hepatocellular Carcinoma After Failure of the First-Line Therapy

Purpose

Regorafenib is a standard second-line treatment for hepatocellular carcinoma (HCC). This study aimed to evaluate the efficacy and safety of regorafenib in the treatment of patients with Barcelona clinic liver cancer (BCLC) stage C HCC after failure of the first-line therapy and to analyze factors affecting the efficacy of regorafenib as the second-line treatment.

Methods

A retrospective analysis was conducted on 103 BCLC stage C HCC patients who received regorafenib as the second-line treatment. Among them, 51 patients received regorafenib plus transarterial chemoembolization (TACE) and 52 patients received regorafenib alone. Progression-free survival (PFS), overall survival (OS), and adverse events were compared between the two groups, and factors influencing the efficacy of regorafenib were analyzed.

Results

In patients with BCLC stage C HCC after failure of the first-line therapy, there was no statistically significant difference in median PFS between regorafenib plus TACE group and regorafenib group (5.3 vs 4.0 months, P=0.432). The median OS was significantly longer in the regorafenib plus TACE group than that in the regorafenib group (11.3 vs 8.2 months, P=0.034). Patients in both groups experienced adverse events at rates of 78.43% and 75%, respectively. Rates of grade III-IV serious adverse events were 19.61% and 13.46%, respectively. Hand-foot skin reactions, fatigue, abdominal pain, and hypertension were common side effects of regorafenib. The number of tumors was noted as an independent prognostic factor for PFS in the univariate and multivariate Cox regression analyses, while Eastern Cooperative Oncology Group (ECOG) performance status (ECOG-PS) score, tumor size, the number of tumors, and combined local therapy were independent prognostic factors for OS. Regorafenib combined with TACE treatment improved OS for patients with ECOG-PS scores of 0-1, tumor size < 5 cm, and the number of tumors ≥ 3 compared with regorafenib alone.

Conclusion

Regorafenib exhibited to be a safe and effective sequential therapy for patients with BCLC stage C HCC after failure of the first-line treatment, and its combination with TACE could achieve a higher efficacy. ECOG-PS score, tumor size, the number of tumors, and combined local therapy were noted as prognostic factors affecting patients with BCLC stage C HCC who were treated with regorafenib.

Machine learning models in the prediction of 1-year mortality in patients with advanced hepatocellular cancer on immunotherapy: a proof-of-concept study

INTRODUCTION

Immunotherapy is a new promising treatment for patients with advanced hepatocellular carcinoma (HCC), but is costly and potentially associated with considerable side effects. This study aimed to evaluate the role of machine learning (ML) models in predicting the 1-year cancer-related mortality in advanced HCC patients treated with immunotherapy.

METHOD

395 HCC patients who had received immunotherapy (including nivolumab, pembrolizumab or ipilimumab) between 2014 and 2019 in Hong Kong were included. The whole data sets were randomly divided into training (n = 316) and internal validation (n = 79) set. The data set, including 47 clinical variables, was used to construct six different ML models in predicting the risk of 1-year mortality. The performances of ML models were measured by the area under receiver operating characteristic curve (AUC) and their performances were compared with C-Reactive protein and Alpha Fetoprotein in ImmunoTherapY score (CRAFITY) and albumin-bilirubin (ALBI) score. The ML models were further validated with an external cohort between 2020 and 2021.

RESULTS

The 1-year cancer-related mortality was 51.1%. Of the six ML models, the random forest (RF) has the highest AUC of 0.92 (95% CI 0.87-0.98), which was better than logistic regression (0.82, p = 0.01) as well as the CRAFITY (0.68, p < 0.01) and ALBI score (0.84, p = 0.04). RF had the lowest false positive (2.0%) and false negative rate (5.2%), and performed better than CRAFITY score in the external validation cohort (0.91 vs 0.66, p < 0.01). High baseline AFP, bilirubin and alkaline phosphatase were three common risk factors identified by all ML models.

CONCLUSION

ML models could predict 1-year cancer-related mortality in HCC patients treated with immunotherapy, which may help to select patients who would benefit from this treatment.

OUP accepted manuscript

Background

This phase I dose de-escalation study aimed to assess the tolerability, safety, pharmacokinetics (PK), and efficacy of sequentially decreasing doses of sorafenib in combination (SAM) with atorvastatin (A, 10 mg) and metformin (M, 500 mg BD) in patients with advanced hepatocellular carcinoma (HCC).

Methods

Patients were enrolled in 1 of 4 sequential cohorts (10 patients each) of sorafenib doses (800 mg, 600 mg. 400 mg, and 200 mg) with A and M. Progression from one level to the next was based on prespecified minimum disease stabilization (at least 4/10) and upper limits of specific grade 3-5 treatment-related adverse events (TRAE).

Results

The study was able to progress through all 4 dosing levels of sorafenib by the accrual of 40 patients. Thirty-eight (95%) patients had either main portal vein thrombosis or/and extra-hepatic disease. The most common grade 3-5 TRAEs were hand-foot-syndrome (grade 2 and grade 3) in 3 (8%) and transaminitis in 2 (5%) patients, respectively. The plasma concentrations of sorafenib peaked at 600 mg dose, and the concentration threshold of 2400 ng/mL was associated with higher odds of achieving time to exposure (TTE) concentrations >75% centile (odds ratio [OR] = 10.0 [1.67-44.93]; P = .01). The median overall survival for patients without early hepatic decompensation (n = 31) was 8.9 months (95% confidence interval [CI]: 3.2-14.5 months).

Conclusion

The SAM combination in HCC patients with predominantly unfavorable baseline disease characteristics showed a marked reduction in sorafenib-related side effects. Studies using sorafenib 600 mg per day in this combination along with sorafenib drug level monitoring can be evaluated in further trials.

(Trial ID: CTRI/2018/07/014865).

Photodynamic therapy: A next alternative treatment strategy for hepatocellular carcinoma?

Liver cancer is one of the most common cancers in the world. Of all types of liver cancer, hepatocellular carcinoma (HCC) is known to be the most frequent primary liver malignancy and has seriously compromised the health status of the general population. Locoregional thermal ablation techniques such as radiofrequency and microwave ablation, have attracted attention in clinical practice as an alternative strategy for HCC treatment. However, their aggressive thermal effect may cause undesirable complications such as hepatic decompensation, hemorrhage, bile duct injury, extrahepatic organ injuries, and skin burn. In recent years, photodynamic therapy (PDT), a gentle locoregional treatment, has attracted attention in ablation therapy for patients with superficial or luminal tumors as an alternative treatment strategy. However, some inherent defects and extrinsic factors of PDT have limited its use in clinical practice for deep-seated HCC. In this contribution, the aim is to summarize the current status and challenges of PDT in HCC treatment and provide potential strategies to overcome these deficiencies in further clinical translational practice.