Ascitic microbiota alteration is associated with portal vein tumor thrombosis occurrence and prognosis in hepatocellular carcinoma.

Portal vein tumor thrombosis (PVTT) frequently leads to malignant ascites (MA) in individuals with hepatocellular carcinoma (HCC), remaining a bottleneck in the treatment. This study aimed to explore the differences in microbes in paired groups and provide novel insights into PVTT and MA-related treatments. Formalin-fixed paraffin embedding ascite samples were collected from MA secondary to HCC and benign ascites (BA) secondary to liver cirrhosis (LC). Ascitic microbiota profiles were determined in the HCC and LC groups by 16S rRNA sequencing. Prognostic risk factors were screened using survival analysis. The correlation between the significantly different microbial signatures in the groups with PVTT (WVT) and non-PVTT (NVT) and clinical characteristics was explored. The expression of different immune cells was determined by labeling four markers in the MA tissue chips using multiplex immunohistochemistry. A total of 240 patients (196 with HCC with MA and 44 with LC with BA) were included in this study. Microbial profiles differed between the HCC and LC groups. PVTT and Barcelona Clinic Liver Cancer stage were shown to be prognostic risk factors. Significant differences in the alpha and beta diversities were observed between the WVT and NVT groups. Gammaproteobacteria and Acinetobacter were the most abundant in the HCC MA. Differences in microbial signatures between the WVT and NVT groups were correlated with the level of C-reactive protein and apolipoprotein A1. This study revealed the microbial differences in the tumor microenvironment of MA secondary to HCC and BA secondary to LC.IMPORTANCEFirst, we explored the alteration of the ascites ecosystem through the microbiota in patients with hepatocellular carcinoma (HCC) and liver cirrhosis. Second, this is the first clinical study to investigate the differences between patients with HCC with and without portal vein tumor thrombosis via 16S rRNA sequencing. These results revealed a decreased microbial diversity and metabolic dysregulation in individuals with HCC and portal vein tumor thrombosis. Gammaproteobacteria and Acinetobacter were the most abundant in the HCC malignant ascitic fluid. Our study provides a new perspective on treating malignant ascites secondary to HCC.

Association between ascites Gustave Roussy immune score and the intratumoural microbiome in malignant ascites secondary to hepatocellular carcinoma.

BACKGROUNDS: The Gustave Roussy Immune (GRIm) score predicts survival outcomes in several cancers. However, the prognostic significance of the GRIm score in patients with malignant ascites has not yet been investigated. METHODS: Clinical samples were collected from a cohort of patients with malignant ascites secondary to hepatocellular carcinoma (HCC). We calculated serum GRIm (sGRIm) and ascites GRIm (aGRIm) scores and divided the samples into low and high GRIm score groups. Survival analysis was used to compare the prognostic significance of the sGRIm and aGRIm scores. 16S rRNA sequencing was performed to determine the profiles of the intratumoral microbiota in the groups. A fluorescent multiplex immunohistochemistry (mIHC) assay was used to detect the expression of different immune cells by labeling seven markers of malignant ascites. RESULTS: 155 patients with HCC and malignant ascites were enrolled in this study. Survival analysis revealed that the aGRIm score showed a superior prognostic significance compared to the sGRIm score. Microbial analysis demonstrated that the bacterial richness and diversity were higher in the low aGRIm score group than in the high aGRIm score group. LefSe analysis revealed that certain bacteria were correlated with high aGRIm scores. Fluorescent mIHC displayed the tumor microenvironment of malignant ascites and found that the density of CD8 + T cells was significantly higher in the low aGRIm score group than in the high aGRIm score group. CONCLUSIONS: Our present study identified a novel scoring system (aGRIm score) that can predict the survival outcome of patients with malignant ascites secondary to HCC.

Global burden and risk factors of gastritis and duodenitis: an observational trend study from 1990 to 2019.

In recent years, there has been a global trend of aging, which has resulted in significant changes to the burden of gastritis and duodenitis (GD). Using the global burden of disease (GBD) database spanning 1990 to 2019, we evaluated the temporal trends of age-standardized incidence rates (ASIR), age-standardized death rates (ASDR), and age-standardized disability-adjusted life years (AS-DALYs) for GD using estimated annual percentage changes (EAPC). Additionally, we examined the burden of GD across various strata, including social demographic index (SDI), age, and sex. Finally, the risk factors linked to the incidence and mortality of GD, utilizing Pearson correlation analysis. In 2019, there were 31 million GD patients globally, a notable increase of 12 million from 1990, while the ASIR, ASDR, and AS-DALYs for GD all showed a decrease. Correlation analysis showed a significant negative relationship between ASIR and SDI. Factors like hand hygiene and vitamin A deficiency had significant positive correlations with ASIR and ASDR in 2019. Over the past thirty years, the burden of GD has increased alongside global population aging. Future efforts should focus on exploring prevention for GD, with special attention to the elderly population in low SDI regions.

Comparison of Helicobacter pylori positive and negative gastric cancer via multi-omics analysis.

Helicobacter pylori (H. pylori) has been regarded as a definite carcinogenic bacterium for gastric cancer (GC). This multi-omics research was designed to investigate the genetic, microbial, and metabolic changes of GC patients when they are infected with H. pylori. We first mined The Cancer Genome Atlas Stomach Adenocarcinoma (STAD) data to identify the key genes and critical pathways in H. pylori-positive individuals with GC compared to H. pylori-negative individuals with GC. Then, fresh stool samples were collected from GC individuals screened for eligibility, and we analyzed the microbial changes and metabolite alterations between H. pylori-positive and H. pylori-negative GC individuals. Finally, we tried to explore the interaction between key gut flora and metabolite changes in GC patients infected with H. pylori. We identified three genes (GCG, APOA1, and IGFBP1) with significant relevance to H. pylori infection, and the survival monogram based on the three H. pylori-related genes showed good predictive ability for overall survival among GC individuals. 16S rRNA sequencing showed that the abundance of Escherichia-Shigella, Bacteroides, Enterococcus, and Lactobacillus was upregulated in GC cases with H. pylori at the level of genus. There exists a great difference in alpha and beta diversity between H. pylori group and non-H. pylori group. The untargeted metabolome analysis identified 295 significant fecal metabolites, and the levels of penitrem E, auberganol, stercobilinogen, and lys thr are upregulated in the H. pylori group. Finally, correlation analysis showed that there exists a significant correlation between the fecal metabolites and gut bacterial strains. This is the first clinical research to investigate the difference between GC patients with H. pylori and GC patients without H. pylori via multi-omics analysis. 16S rRNA sequencing along with untargeted metabolomics demonstrated decreased microbial diversity and metabolic dysregulation in gastric carcinoma individuals with H. pylori infection.IMPORTANCEThis is the first clinical research to systematically expound the difference between gastric cancer (GC) individuals with Helicobacter pylori and GC individuals without H. pylori from the perspective of multi-omics. This clinical study identified significant genes, microbes, and fecal metabolites, which exhibited nice power for differentiating GC individuals with H. pylori infection from GC individuals without H. pylori infection. This study provides a crucial basis for a better understanding of eradication therapy among the GC population.

Research hotspot and trend analysis in the diagnosis of inflammatory bowel disease: A machine learning bibliometric analysis from 2012 to 2021.

Aims: This study aimed to conduct a bibliometric analysis of the relevant literature on the diagnosis of inflammatory bowel disease (IBD), and show its current status, hot spots, and development trends. Methods: The literature on IBD diagnosis was acquired from the Science Citation Index Expanded of the Web of Science Core Collection. Co-occurrence and cooperation relationship analysis of authors, institutions, countries, journals, references, and keywords in the literature were carried out through CiteSpace software and the Online Analysis platform of Literature Metrology. At the same time, the relevant knowledge maps were drawn, and the keywords cluster analysis and emergence analysis were performed. Results: 14,742 related articles were included, showing that the number of articles in this field has increased in recent years. The results showed that PEYRIN-BIROULET L from the University Hospital of Nancy-Brabois was the author with the most cumulative number of articles. The institution with the most articles was Mayo Clin, and the United States was far ahead in the article output and had a dominant role. Keywords analysis showed that there was a total of 818 keywords, which were mainly focused on the research of related diseases caused or coexisted by IBD, such as colorectal cancer and autoimmune diseases, and the diagnosis and treatment methods of IBD. Emerging analysis showed that future research hotspots and trends might be the treatment of IBD and precision medicine. Conclusion: This research was the first bibliometric analysis of publications in the field of IBD diagnosis using visualization software and data information mining, and obtained the current status, hotspots, and development of this field. The future research hotspot might be the precision medicine of IBD, and the mechanism needed to be explored in depth to provide a theoretical basis for its clinical application.

Distant Metastasis Pattern and Prognostic Prediction Model of Colorectal Cancer Patients Based on Big Data Mining.

Aims: This study aimed to investigate the distant metastasis pattern from newly diagnosed colorectal cancer (CRC) and also construct and validate a prognostic nomogram to predict both overall survival (OS) and cancer-specific survival (CSS) of CRC patients with distant metastases. Methods: Primary CRC patients who were initially diagnosed from 2010 to 2016 in the SEER database were included in the analysis. The independent risk factors affecting the OS, CSS, all-cause mortality, and CRC-specific mortality of the patients were screened by the Cox regression and Fine-Gray competitive risk model. The nomogram models were constructed to predict the OS and CSS of the patients. The reliability and accuracy of the prediction model were evaluated by consistency index (C-index) and calibration curve. The gene chip GSE41258 was downloaded from the GEO database, and differentially expressed genes (DEGs) were screened by the GEO2R online tool (p < 0.05, |logFC|>1.5). The Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway and Gene Ontology (GO) annotation and String website were used for enrichment analysis and protein-protein interaction (PPI) analysis of DEGs, respectively, and Cytoscape software was used to construct PPI network and screen function modules and hub genes. Results: A total of 57,835 CRC patients, including 47,823 without distant metastases and 10,012 (17.31%) with metastases, were identified. Older age, unmarried status, poorly differentiated or undifferentiated grade, right colon site, larger tumor size, N2 stage, more metastatic sites, and elevated carcinoembryonic antigen (CEA) might lead to poorer prognosis (all p < 0.01). The independent risk factors of OS and CSS were included to construct a prognosis prediction model for predicting OS and CSS in CRC patients with distant metastasis. C-index and calibration curve of the training group and validation group showed that the models had acceptable predictive performance and high calibration degree. Furthermore, by comparing CRC tissues with and without liver metastasis, 158 DEGs and top 10 hub genes were screened. Hub genes were mainly concentrated in liver function and coagulation function. Conclusion: The big data in the public database were counted and transformed into a prognostic evaluation tool that could be applied to the clinic, which has certain clinical significance for the formulation of the treatment plan and prognostic evaluation of CRC patients with distant metastasis.

Low APOA-1 Expression in Hepatocellular Carcinoma Patients Is Associated With DNA Methylation and Poor Overall Survival.

Background: Hepatocellular carcinoma (HCC) is the most frequent fatal malignancy, and it has a poor prognosis. Apolipoprotein 1 (APOA-1), the main protein component of high-density lipoproteins, is involved in numerous biological processes. Thus, this study was performed to detect the clinical significance of APOA-1 mRNA, APOA-1 expression, and APOA-1DNA methylation in patients with HCC. Methods: Data mining was performed using clinical and survival data from the Cancer Genome Atlas (TCGA) and Oncomine databases. The serum concentration of APOA-1 was measured in 316 patients with HCC and 100 healthy individuals at Renmin Hospital of Wuhan University, and the intact clinical information was reviewed and determined using univariate and multivariate Cox hazard models. Results: Bioinformatic analysis revealed that APOA-1 mRNA was present at lower levels in the serum of patients with HCC than in that of healthy individuals, and there was a strong negative correlation between levels of APOA-1 mRNA and APOA-1 DNA methylation. High expression of APOA-1 transcription correlated with better overall survival (p = 0.003), and APOA-1 hypermethylation correlated with progress-free survival (p = 0.045) in HCC sufferers. Next, the clinical data analysis demonstrated that APOA-1 protein levels in the serum were significantly lower in patients with HCC than in healthy controls. Furthermore, the expression of APOA-1 was significantly associated with some significant clinical indexes, and elevated APOA-1 expression was significantly associated with favorable (OS; HR:1.693, 95% CI: 1.194-2.401, p = 0.003) and better progression-free survival (PFS; HR = 1.33, 95% CI = 1.194-2.401, p = 0.045). Finally, enrichment analysis suggested that co-expressed genes of APOA-1 were involved in lipoprotein metabolism and FOXA2/3 transcription factor networks. Conclusion: APOA-1 mRNA expression is negatively regulated by DNA methylation in HCC. Low expression of APOA-1 might be a potential risk biomarker to predict survival in patients with HCC.

Expression Status and Prognostic Significance of Gamma-Glutamyl Transpeptidase Family Genes in Hepatocellular Carcinoma.

PURPOSE: Gamma-glutamyl transpeptidase (GGT) family genes play crucial roles in the formation and progression of several solid tumors. However, the expression patterns and the prognostic significance of GGT members in hepatocellular carcinoma (HCC) remain unknown. This study was designed to determine the expression profiles of GGT family members in HCC and validate the prognostic value of serum GGT protein in patients with HCC. METHOD: We comprehensively searched public resources based on the LIHC dataset to determine the expression patterns, prognostic significance, DNA methylation status, immune infiltration, and biological pathways of GGT family genes in HCC. Subsequently, we validated the prognostic value of serum GGT protein in 85 patients with early-stage HCC subjected to curative hepatectomy from the Renmin Hospital of Wuhan University. RESULTS: Except for GGT1, other GGT family members (GGT5, GGT6, and GGT7) were found to be differentially expressed in primary HCC samples (N = 371) and normal control tissues (N = 50). Furthermore, a positive relationship was not only observed between GGT1 and GGT5 (Spearman coefficient: 0.24, P = 5.143 × 10-6) but also between GGT5 and GGT6 (Spearman coefficient: 0.38, P = 1.24 × 10-13). The expression of GGT1, GGT5, and GGT7 was correlated with overall survival (OS), and GGT7 was associated with disease-free survival (DFS) in patients with HCC. Negative associations between DNA methylation and expression of mRNA were observed for GGT1 (Spearman coefficient: -0.38, P = 6.24e-14), GGT6 (Spearman coefficient: -0.29, P = 1.23e-8), and GGT7 (Spearman coefficient: -0.34, P=6.7e-11). GGT family genes were well correlated with the infiltration levels of immune cells in HCC, especially CD4+ T cells, macrophages, and dendritic cells. Finally, when validated with clinical data from the Renmin cohort, a high expression of serum GGT protein was identified as a strong prognostic element of unfavorable OS (HR = 3.114, P = 0.025), but not of DFS (HR = 1.198, P = 0.05) in patients with HCC subjected to curative hepatectomy. CONCLUSION: To our knowledge, this is the first comprehensive analysis of the expression patterns and clinical value of GGT family genes in patients with HCC. Our study laid the foundation for the clinical application of the GGT protein in the survival assessment of patients with HCC.

Oncological Effects and Prognostic Value of AMAP1 in Gastric Cancer.

PURPOSE: We examined the diagnostic significance, prognostic value, and potential function of AMAP1 in gastric cancer (GC). METHODS: Comprehensive bioinformatic analysis was conducted to investigate differential expression of AMAP1 mRNA and protein in GC. Meta-analyses were utilized to determine the overall prognostic correlation of AMAP1 mRNA in patients with GC. A panel of vitro assays was applied to assess target microRNA and AMAP1 protein in GC cell lines and tissues, respectively. RESULTS: AMAP1 mRNA and protein levels were upregulated in GC specimens, compared to matched normal tissues. AMAP1 mRNA exhibited promising results regarding differential diagnosis of GC and normal tissue. Meta-analysis based on the TCGA and GEO databases revealed that high AMAP1 mRNA abundance was associated with poor overall survival (HR = 1.42; 95% CI: 1.06-1.89) and was correlated with reduced progression-free survival (HR = 1.89; 95% CI: 1.51-2.36) in GC patients. Moreover, AMAP1 was negatively correlated with miR-192-3p (r = -0.3843; P < 0.0001). A dual-luciferase assay revealed that miR-192-3p targeted AMAP1. Levels of miR-192-3p were significantly higher in GC tissues and GC cells than in normal tissues and cells. Moreover, AMAP1 silencing resulted in reduced GC proliferation, migration, and invasion. CONCLUSION: AMAP1 is a novel oncogene in GC and is negatively correlated with by miR-192-3p. AMAP1 may act as a diagnostic and prognostic marker of GC.

Development and validation a simple model for identify malignant ascites.

The differential diagnosis of benign ascites and malignant ascites is incredibly challenging for clinicians. This research aimed to develop a user-friendly predictive model to discriminate malignant ascites from non-malignant ascites through easy-to-obtain clinical parameters. All patients with new-onset ascites fluid were recruited from January 2014 to December 2018. The medical records of 317 patients with ascites for various reasons in Renmin Hospital of Wuhan University were collected and reviewed retrospectively. Thirty-six parameters were included and selected using univariate logistic regression, multivariate logistic regression, and receiver operating characteristic (ROC) curve analyses to establish a mathematical model for differential diagnosis, and its diagnostic performance was validated in the other groups. Age, cholesterol, hypersensitivity C-reactive protein (hs-CRP) in serum, ascitic fluid adenosine deaminase (AF ADA), ascitic fluid lactate dehydrogenase (AF LDH) involvement in a 5-marker model. With a cut-off level of 0.83, the sensitivity, specificity, accuracy, and area under the ROC of the model for identifying malignant ascites in the development dataset were 84.7%, 88.8%, 87.6%, and 0.874 (95% confidence interval [CI], 0.822-0.926), respectively, and 80.9%, 82.6%, 81.5%, and 0.863 (95% CI,0.817-0.913) in the validation dataset, respectively. The diagnostic model has a similar high diagnostic performance in both the development and validation datasets. The mathematical diagnostic model based on the five markers is a user-friendly method to differentiate malignant ascites from benign ascites with high efficiency.

Clinical characteristics of COVID-19 complicated with pleural effusion.

BACKGROUND: Epidemiological and clinical features of patients with corona virus disease 2019 (COVID-19) were well delineated. However, no researches described the patients complicated with pleural effusion (PE). In the present study, we aimed to clinically characterize the COVID-19 patients complicated with PE and to create a predictive model on the basis of PE and other clinical features to identify COVID-19 patients who may progress to critical condition. METHODS: This retrospective study examined 476 COVID-19 inpatients, involving 153 patients with PE and 323 without PE. The data on patients' past history, clinical features, physical checkup findings, laboratory results and chest computed tomography (CT) findings were collected and analyzed. LASSO regression analysis was employed to identify risk factors associated with the severity of COVID-19. RESULTS: Laboratory findings showed that patients with PE had higher levels of white blood cells, neutrophils, lactic dehydrogenase, C-reactive protein and D-dimer, and lower levels of lymphocytes, platelets, hemoglobin, partial pressure of oxygen and oxygen saturation. Meanwhile, patients with PE had higher incidence of severe or critical illness and mortality rate, and longer hospital stay time compared to their counterparts without pleural effusion. Moreover, LASSO regression analysis exhibited that pleural effusion, lactic dehydrogenase (LDH), D-dimer and total bilirubin (TBIL) might be risk factors for critical COVID-19. CONCLUSIONS: Pleural effusion could serve as an indicator for severe inflammation and poor clinical outcomes, and might be a complementary risk factor for critical type of COVID-19.

DNA Methylation-Driven Genes for Developing Survival Nomogram for Low-Grade Glioma.

Low-grade gliomas (LGG) are heterogeneous, and the current predictive models for LGG are either unsatisfactory or not user-friendly. The objective of this study was to establish a nomogram based on methylation-driven genes, combined with clinicopathological parameters for predicting prognosis in LGG. Differential expression, methylation correlation, and survival analysis were performed in 516 LGG patients using RNA and methylation sequencing data, with accompanying clinicopathological parameters from The Cancer Genome Atlas. LASSO regression was further applied to select optimal prognosis-related genes. The final prognostic nomogram was implemented together with prognostic clinicopathological parameters. The predictive efficiency of the nomogram was internally validated in training and testing groups, and externally validated in the Chinese Glioma Genome Atlas database. Three DNA methylation-driven genes, ARL9, CMYA5, and STEAP3, were identified as independent prognostic factors. Together with IDH1 mutation status, age, and sex, the final prognostic nomogram achieved the highest AUC value of 0.930, and demonstrated stable consistency in both internal and external validations. The prognostic nomogram could predict personal survival probabilities for patients with LGG, and serve as a user-friendly tool for prognostic evaluation, optimizing therapeutic regimes, and managing LGG patients.

Development and validation of a novel scoring system developed from a nomogram to identify malignant pleural effusion.

BACKGROUND: This study aimed to establish and validate a novel scoring system based on a nomogram for the differential diagnosis of malignant pleural effusion (MPE) and benign pleural effusion (BPE). METHODS: Patients with PE and confirmed aetiology who underwent diagnostic thoracentesis were included in this study. One retrospective set (N = 1261) was used to develop and internally validate the predictive model. The clinical, radiological and laboratory features were collected and subjected to logistic regression analyses. The primary predictive model was displayed as a nomogram and then modified into a novel scoring system, which was externally validated in an independent set (N = 172). FINDINGS: The novel scoring system was composed of fever (3 points), erythrocyte sedimentation rate (4 points), effusion adenosine deaminase (7 points), serum carcinoembryonic antigen (CEA) (4 points), effusion CEA (10 points) and effusion/serum CEA (8 points). With a cutoff value of 15 points, the area under the curve, specificity and sensitivity for identifying MPE were 0.913, 89.10%, and 82.63%, respectively, in the training set, 0.922, 93.48%, 81.51%, respectively, in the internal validation set and 0.912, 87.61%, 81.36%, respectively, in the external validation set. Moreover, this scoring system was exclusively applied to distinguish lung cancer with PE from tuberculous pleurisy and showed a favourable diagnostic performance in the training and validation sets. INTERPRETATION: This novel scoring system was developed from a retrospective study and externally validated in an independent set based on six easily accessible clinical variables, and it exhibited good diagnostic performance for identifying MPE. FUNDING: NFSC grants (no. 81572942, no. 81800094).

High Efficient Isolation of Tumor Cells by a Three Dimensional Scaffold Chip for Diagnosis of Malignant Effusions.

High efficient detection of effusion tumor cells (ETCs) has great clinical significance to identify malignant from benign effusions, but few strategies are designed to enrich and identify tumor cells from effusions. Herein, we developed a three-dimensional scaffold microchip (3D scaffold chip) which could efficiently isolate individual ETC and ETC cluster (ETC/cluster) from pleural effusions and ascites by molecular recognition and physical obstruction. The 3D scaffold chip could enrich ETCs with 94.7% capture efficiency from 2 mL effusions in 20 min and was successfully applied to analysis of pleural effusions or ascites from 152 patients. The results showed that patients with malignant effusions possessed a much higher number of ETC/cluster than that of patients with benign effusions and receiver operating characteristic (ROC) analysis revealed that ETC/cluster count can be used as a complementary biomarker for diagnosis of malignant effusions. Finally, univariate and multivariate logistic regression analyses were adopted to find effusion variables with statistical difference in diagnosis of malignant effusions, and three variables (ETC/cluster count and effusion carcinoembryonic antigen) were selected to establish a three-marker predictive model for differentiating malignant and benign effusions in the training set. ROC analysis revealed that the AUC (area under the curve), sensitivity, and specificity of the predictive model were 0.939, 90.4%, and 91.8%, respectively. The three-marker predictive model was successfully applied to the validation set and proved that this model was promising for clinical diagnosis of effusions from patients.

Carvedilol vs endoscopic band ligation for the prevention of variceal bleeding: a meta-analysis.

OBJECTIVE: Variceal hemorrhage is the primary driver of mortality in patients with portal hypertension. Recent guidelines recommended that patients with esophageal varices should receive endoscopic band ligation (EBL) or carvedilol as prophylaxis of variceal bleeding. Several clinical trials have compared carvedilol use with EBL intervention, yielding controversial results. The present study aimed to perform a meta-analysis of randomized controlled trials (RCTs) evaluating the benefits and harms of carvedilol vs EBL for the prevention of variceal bleeding. METHODS: Studies were searched on Pubmed, Embase, Medline, and Cochrane library databases up to August 2018. Main outcomes in selected studies (variceal bleeding, all-cause deaths, bleeding-related deaths, and adverse events) were pooled into a meta-analysis. RESULTS: Seven RCTs were identified in this meta-analysis, including a total of 703 patients. A total of 359 patients were randomized to carvedilol group and 354 were randomized to EBL group. No significant difference in variceal bleeding was observed between carvedilol use and EBL groups (relative ratio [RR] =0.86, 95% CI =0.60-1.23, I 2=11%), without publication bias. No significant difference was found neither for all-cause deaths (RR =0.82, 95% CI =0.44-1.53, I 2=66%) nor for bleeding-related deaths (RR =0.85, 95% CI =0.39-1.87, I 2=42%) in four included studies. Moreover, no reduced trend was observed toward adverse events in carvedilol group compared with that in EBL group (RR =1.32, 95% CI =0.75-2.31, I 2=81%). CONCLUSION: There is no significant difference between carvedilol use and EBL intervention for the prophylaxis of variceal bleeding in patient with esophageal varices. Large-scale clinical trials are further needed to make a confirmed conclusion.