Epidemiology of Hepatocellular Carcinoma

Epidemiology and Cancer Registration Unit, IDIBELL, Institut Català d'Oncologia, Avda. Gran Via s/n, Km 2.7, 08907 L'Hospitalet de Llobregat, Barcelona, Spain.
Clinics in Liver Disease (Impact Factor: 2.7). 06/2005; 9(2):191-211, v. DOI: 10.1016/j.cld.2004.12.009
Source: PubMed

ABSTRACT Year 2000 estimates of the incidence of cancer indicate that primary liver cancer remains the fifth most common malignancy in men and the eighth in women. The number of new cases has been predicted as 564,000, corresponding to 398,000 in men and 166,000 in women. The geographic areas at highest risk are located in Eastern Asia, Middle Africa, and some countries of Western Africa. Changes in incidence among migrant populations underline the predominant role of environmental factors in the etiology of primary liver cancer. In high-risk countries, the early cases of primary liver cancer occur already at ages 20 and above, underlying the impact of viral exposures early in life. In countries at low risk, primary liver cancer is rare before the 50s, translating the impact of late exposures with moderate risks and long latency intervals. Sex ratios are typically between 2 and 4. The incidence of primary liver cancer is increasing in several developed countries including the United States, and the increase will likely continue for several decades. The trend has a dominant cohort effect related to exposures to hepatitis B and C viruses. The variability of primary liver cancer incidence is largely explained by the distribution and the natural history of the hepatitis B and C viruses. The attributable risk estimates for the combined effects of these infections account for well over 80% of liver cancer cases worldwide. Primary liver cancer is the first human cancer largely amenable to prevention using hepatitis B virus vaccines and screening of blood and blood products for hepatitis B and C viruses.

    • "Hepatocellular carcinoma (HCC) is the most common primary liver cancer, the sixth most common cancer, and the third most common cause of cancer-related deaths in the world [1] [2]. This cancer generally develops secondarily to an underlying chronic liver disease, due to different aetiologies (B or C viral hepatitis, alcohol abuse, non-alcoholic steatohepatitis, genetic iron overload ) [3]. "
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    ABSTRACT: BACKGROUND & AIMS: Transarterial chemoembolization (TACE) is the standard of care for intermediate stage hepatocellular carcinoma (HCC) and it is the most commonly used treatment for HCC worldwide. However, no prognostic indices, designed to select appropriate candidates for repeat conventional TACE, have been incorporated in the guidelines. METHODS: From January 2007 to April 2012, 139 consecutive HCC patients, mainly with an alcohol- or viral-induced disease, were treated with TACE. Using a regression model on the prognostic variables of our population, we determined a score designed to help for repeat TACE and we validated it in two cohorts. We also compared it to the ART score. RESULTS: In the multivariate analysis, four prognostic factors were associated with overall survival: BCLC and AFP (>200ng/ml) at baseline, increase in Child-Pugh score by ⩾2 from baseline, and absence of radiological response. These factors were included in a score (ABCR, ranging from -3 to +6), which correlates with survival and identifies three groups. The ABCR score was validated in two different cohorts of 178 patients and proofed to perform better than the ART score in distinguishing between patients' prognosis. CONCLUSIONS: The ABCR score is a simple and clinically relevant index, summing four prognostic variables endorsed in HCC. An ABCR score ⩾4 prior to the second TACE identifies patients with dismal prognosis who may not benefit from further TACE sessions. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
    Journal of Hepatology 02/2015; 379. DOI:10.1016/j.jhep.2015.02.001 · 10.40 Impact Factor
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    • "Human hepatocellular carcinoma (HCC) is the 5th most common cancer occurring worldwide with prevalence in men and higher incidence rates in developing than developed countries [1]. Whereas about 80% of primary liver cancers develop through underlying Hepatitis B (HBV) and Hepatitis C (HCV) infections, other risk factors include smoking, diabetes, overweight and aflatoxin exposure in diet. "
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    ABSTRACT: In T cells mitochondria-derived reactive oxygen species (ROS) are indispensible for activation of the transcription factor NF-κB, expression of cytokines and the CD95 ligand (CD95L/FasL). Here we show that activation-induced ROS generation is dependent on mitochondrial fission. Inhibition of dynamin related protein 1 (Drp1) results in reduced ROS levels and transcriptional activity of NF-κB leading to diminished proliferation and CD95L-dependent activation-induced cell death (AICD). Upon stimulation Drp1 is S-nitrosylated, which is required for oxidative signalling, AICD and cytokine production. In conclusion, we describe a novel signalling pathway that links TCR-induced nitric oxide release to mitochondrial fission and oxidative signalling.
    FEBS letters 03/2014; 588(9). DOI:10.1016/j.febslet.2014.03.029 · 3.34 Impact Factor
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    • "Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death worldwide and the leading cause of death in patients with cirrhosis [1] [2]. In clinical practice, symptoms attributable to HCC are usually absent, so the majority of patients are diagnosed with advanced disease, often precluding potentially curative therapies. "
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    ABSTRACT: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. Clinical symptoms attributable to HCC are usually absent, thus often miss the best therapeutic opportunities. Traditional Chinese Medicine (TCM) plays an active role in diagnosis and treatment of HCC. In this paper, we proposed a particle swarm optimization-based hierarchical feature selection (PSOHFS) model to infer potential syndromes for diagnosis of HCC. Firstly, the hierarchical feature representation is developed by a three-layer tree. The clinical symptoms and positive score of patient are leaf nodes and root in the tree, respectively, while each syndrome feature on the middle layer is extracted from a group of symptoms. Secondly, an improved PSO-based algorithm is applied in a new reduced feature space to search an optimal syndrome subset. Based on the result of feature selection, the causal relationships of symptoms and syndromes are inferred via Bayesian networks. In our experiment, 147 symptoms were aggregated into 27 groups and 27 syndrome features were extracted. The proposed approach discovered 24 syndromes which obviously improved the diagnosis accuracy. Finally, the Bayesian approach was applied to represent the causal relationships both at symptom and syndrome levels. The results show that our computational model can facilitate the clinical diagnosis of HCC.
    03/2014; 2014:127572. DOI:10.1155/2014/127572
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