Clinical characteristics and prognosis of 2887 patients with hepatocellular carcinoma

Wang, Chunyan; Li, Shengmian

doi:10.1097/md.0000000000014070

Cited by 64 publications

(69 citation statements)

References 18 publications

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“…Further, univariate analysis employing clinical factors of patients found that tumor stage of patients can act as a strong prognostic factor in the various types of survival, i.e., OS, RFS/DFS, PFS, and DSS of patients. Eventually, the multivariate survival analysis revealed the tumor stage as a sole independent prognostic factor, which was also corroborated with the previous literature (Aino et al, 2014;Wang and Li, 2019). The correct tumor stage identification is quite a tedious and challenging task in comparison to the quantification of the expression of genes.…”

Section: Discussionsupporting

confidence: 86%

Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data

et al. 2020

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The high mortality rate of hepatocellular carcinoma (HCC) is primarily due to its late diagnosis. In the past, numerous attempts have been made to design genetic biomarkers for the identification of HCC; unfortunately, most of the studies are based on small datasets obtained from a specific platform or lack reasonable validation performance on the external datasets. In order to identify a universal expression-based diagnostic biomarker panel for HCC that can be applicable across multiple platforms, we have employed large-scale transcriptomic profiling datasets containing a total of 2,316 HCC and 1,665 non-tumorous tissue samples. These samples were obtained from 30 studies generated by mainly four types of profiling techniques (Affymetrix, Illumina, Agilent, and High-throughput sequencing), which are implemented in a wide range of platforms. Firstly, we scrutinized overlapping 26 genes that are differentially expressed in numerous datasets. Subsequently, we identified a panel of three genes (FCN3, CLEC1B, and PRC1) as HCC biomarker using different feature selection techniques. Three-genes-based HCC biomarker identified HCC samples in training/validation datasets with an accuracy between 93 and 98%, Area Under Receiver Operating Characteristic curve (AUROC) in a range of 0.97 to 1.0. A reasonable performance, i.e., AUROC 0.91-0.96 achieved on validation dataset containing peripheral blood mononuclear cells, concurred their non-invasive utility. Furthermore, the prognostic potential of these genes was evaluated on TCGA-LIHC and GSE14520 cohorts using univariate survival analysis. This analysis revealed that these genes are prognostic indicators for various types of the survivals of HCC patients (e.g., Overall Survival, Progression-Free Survival, Disease-Free Survival). These genes significantly stratified high-risk and low-risk HCC patients (p-value <0.05). In conclusion, we identified a universal platform-independent three-genes-based biomarker that can predict HCC patients with high precision and also possess significant prognostic potential. Eventually, we developed a web server HCCpred based on the above study to facilitate scientific community (http://webs.iiitd.edu.in/raghava/hccpred/).

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Section: Discussionsupporting

confidence: 86%

Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data

et al. 2020

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“…It is therefore crucial to enable access to HBV viral load monitoring and antiviral treatment to HBV-infected patients as it might prevent a significant proportion of HCC; HCV was also found as an important etiology of HCC in our study, therefore, efforts to prevent unsafe injection could potentially play an important role in the prevention of HCC. In our context of delayed consultation, survival was poorer compared to the results of Wang et al [25] who found a survival of 49.3% and 35.3% in 1 and 2 years respectively. In our work, we showed that the prognostic factors were the BCLC stage, the degree of hepatocellular insufficiency as in Asian studies [25] [26].…”

Section: Discussioncontrasting

confidence: 83%

“…In our context of delayed consultation, survival was poorer compared to the results of Wang et al [25] who found a survival of 49.3% and 35.3% in 1 and 2 years respectively. In our work, we showed that the prognostic factors were the BCLC stage, the degree of hepatocellular insufficiency as in Asian studies [25] [26].…”

Section: Discussioncontrasting

confidence: 83%

Characteristics and Prognosis of Patients with Hepatocellular Carcinoma at Campus Teaching Hospital of Lome

Bagny¹,

Lawson-Ananissoh²,

Bouglouga³

et al. 2019

OJGas

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Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world, as well as in Togo, where it is a major public health problem. HCC is the third most common cause of death from cancer. Chronic infection with HBV and HCV is the most important cause of HCC. Objective: To determine the epidemiological, diagnostic and evolutionary aspects of HCC in the hepatology and gastroenterology department of Campus Teaching Hospital of Lomé. Patients and method: Descriptive and analytical study, conducted from January 1, 2013 to December 31, 2017, on all patients admitted in the hepatology and gastroenterology department of Campus Teaching Hospital of Lome for hepatocellular carcinoma. The statistical analysis was done using Stata 13 software. The significance threshold was used for p < 0.05. Findings: A total of 250 patients were retained. Hospital prevalence was 6.1%. There was a male predominance with a sex ratio of 2.84. The average age was 47.15 ± 13.85 (extreme: 20-85 years). The average duration of symptoms was 67.08 ± 82.59 days. Pain in the right hypochondrium was the most common reason for consultation (64.6%). The average AFP value was 24,062 ± 33,318 ng/ml. Ultrasound found more than two nodules in 74.75% of cases and a portal thrombosis in 64.97% of cases. The main etiologies found were chronic hepatitis B (55%) and C (8%) virus infections. The majority (89.20%) of patients were in the BCLC D stage. Survival at 6 months was 45%. Factors associated with death were: chronic ethylism (OR = 16.87, p = 0.002), jaundice (OR = 341.57, p = 0.004), rupture of esophageal varices (OR = 42.45, p = 0.008) and a BCLC D score (OR = 9.82, p = 0.041). Conclusion: Young adults were the most affected by HCC, whose etiologies are dominated in our context by hepatitis B and C viruses.

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“…Advanced age has been widely reported to be associated with poor survival outcomes in HCC, regardless of the staging or therapeutic modes [28,29], but has never been explored in patients with HCC with spinal metastases. Previous studies used a variety of age cut points, ranging from 60 to 70 years old [27][28][29][30]. Our study is the rst one to demonstrate the effect of old age (> 60 years) on the survival of patients with HCC-derived spinal metastases.…”

Section: Discussionmentioning

confidence: 86%

Natural disease progression and novel survival prediction model for hepatocellular carcinoma with spinal metastases: a 10-year single-center study

Phinyo

Boonyanaruthee

Paholpak

et al. 2020

Preprint

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Background: Individual prediction of life expectancy in patients with spinal metastases from hepatocellular carcinoma (HCC) is key for optimal treatment selection, especially when identifying potential candidates for surgery. Most reported prognostic tools provide categorical predictions, and only a few include HCC-related factors. This study aimed to investigate the natural progression of the disease and develop a prognostic tool that is capable of providing individualized predictions.Methods: Patients with HCC-derived metastatic spinal disease were identified from a retrospective cohort of patients with spinal metastases who were diagnosed at Chiang Mai University Hospital between 2006 and 2015. Kaplain–Meier methods and log-rank tests were used to statistically evaluate potential factors. Significant predictors from univariable analysis were included in the flexible parametric survival regression for the development of a prognostic prediction model. Results: Of the 1,143 patients diagnosed with HCC, 69 (6%) had spinal metastases. The median survival time of patients with HCC after spinal metastases was 79 days. In the multivariable analysis, a total of 11 potential clinical predictors were included. After backward elimination, four final predictors remained: patients aged > 60 years, Karnofsky Performance Status, total bilirubin level, and multifocality of HCC. The model showed acceptable discrimination at C-statistics 0.73 (95% Confidence interval 0.68–0.79) and fair calibration. Conclusion: Four clinical parameters were used in the development of the individual survival prediction model for patients with HCC-derived spinal metastases of Chiang Mai University or HCC-SM CMU model. Prospective external validation studies in a larger population are required prior to the clinical implication of the model.

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Clinical characteristics and prognosis of 2887 patients with hepatocellular carcinoma

Cited by 64 publications

References 18 publications

Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data

Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data

Characteristics and Prognosis of Patients with Hepatocellular Carcinoma at Campus Teaching Hospital of Lome

Natural disease progression and novel survival prediction model for hepatocellular carcinoma with spinal metastases: a 10-year single-center study

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