Current trends and recent advances in diagnosis, therapy, and prevention of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has been one of the most fatal malignant tumors worldwide and its associated morbidity and mortality remain of significant concern. Based on in-depth reviews of serological diagnosis of HCC, in addition to AFP, there are other biomarkers: Lens culinaris agglutinin-reactive AFP (AFP-L3), des- carboxyprothrombin (DCP), tyrosine kinase with Ig and eprdermal growth factor (EGF) homology domains 2 (TIE2)-espressing monocytes (TEMs), glypican-3 (GPC3), Golgi protein 73 (GP73), interleukin-6 (IL-6), and squamous cell carcinoma antigen (SCCA) have been proposed as biomarkers for the early detection of HCC. The diagnosis of HCC is primarily based on noninvasive standard imaging methods, such as ultrasound (US), dynamic multiphasic multidetector-row CT (MDCT) and magnetic resonance imaging (MRI). Some experts advocate gadolinium diethyl-enetriamine pentaacetic acid (Gd-EOB-DTPA) MRI and contrast-enhanced US as the promising imaging madalities of choice. With regard to recent advancements in tissue markers, many cuting-edge technologies using genome-wide DNA microarrays, qRT-PCR, and proteomic and inmunostaining studies have been implemented in an attempt to identify markers for early diagnosis of HCC. Only less than half of HCC patients at initial diagnosis are at an early stage treatable with curative options: local ablation, surgical resection, or liver transplant. Transarterial chemoembolization (TACE) is considered the standard of care with palliation for intermediate stage HCC. Recent innovative procedures using drug-eluting-beads and radioembolization using Yttrium-90 may exhibit beneficial effects in HCC treatment. During the past few years, several molecular targeted agents have been evaluated in clinical trials in advanced HCC. Sorafenib is currently the only approved systemic treatment for HCC. It has been approved for the therapy of asymptomatic HCC patients with well-preserved liver function who are not candidates for potentially curative treatments, such as surgical resection or liver transplantation. In the USA, Europe and particularly Japan, hepatitis C virus (HCV) related HCC accounts for most liver cancer, as compared with Asia-Pacific regions, where hepatitis B virus (HBV) may play a more important role in HCC development. HBV vaccination, while a vaccine is not yet available against HCV, has been recognized as a best primary prevention method for HBV-related HCC, although in patients already infected with HBV or HCV, secondary prevention with antiviral therapy is still a reasonable strategy. In addition to HBV and HCV, attention should be paid to other relevant HCC risk factors, including nonalcoholic fatty liver disease due to obesity and diabetes, heavy alcohol consumption, and prolonged aflatoxin exposure. Interestingly, coffee and vitamin K2 have been proven to provide protective effects against HCC. Regarding tertiary prevention of HCC recurrence after surgical resection, addition of antiviral treatment has proven to be a rational strategy.

A cohort study to investigate hepatocellular carcinoma risk in hepatitis C patients.

BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) frequently occurs with chronic hepatitis C (HCV) infection. This study tried to identify clinical and laboratory factors affecting development of HCC in a longitudinal follow-up of chronic HCV patients. METHODOLOGY: A total of 373 patients with CHC who were HCV RNA-seropositive were recruited during 2000-2003. The remaining 164 patients after application of exclusion criteria (90 males; 74 females; mean age: 58.2 +/- 14y/o) were prospectively recruited and followed-up with periodic liver function tests, alfa-fetoprotein and abdominal ultrasound examinations. RESULTS: During follow-up between January 2000 and May 2008, HCC was identified in 19 (11.6%) patients. The incidence rate of HCC was 14.5/1,000 person-years. Fifteen patients (9.1%) developed a cirrhotic liver. Male gender (p=0.018), genotype 1b (p=0.034), cirrhosis (p<0.001) and older age (> or = 65y/o) (p=0.02) are significant risk factors for HCC. Overall, there was 2.7-fold increased risk in patients with HCV RNA > or = 1 million copies/mL to develop HCC. The incidence rate of HCC was 8.8% for pegIFNa/RBV-treated patients with sustained viral response and 14.3% for untreated patients (p=0.352). CONCLUSIONS: This cohort study highlights the roles of male gender, older age and genotype 1b in the progression from chronic HCV to HCC in an area endemic for hepatitis B.

Artificial neural network model is superior to logistic regression model in predicting treatment outcomes of interferon-based combination therapy in patients with chronic hepatitis C.

BACKGROUND/AIMS: Patients with chronic hepatitis C (CHC) can achieve a sustained virologic response if they received pegylated interferon plus ribavirin therapy; however, some of them do not respond or relapse after treatment. The aim of this study was to compare the ability of two statistical models to predict treatment outcomes. METHODS: Clinical data, biochemical values, and liver histological features of 107 patients with CHC were collected and assessed using a logistic regression (LR) model and an artificial neural network (ANN) model. Both the LR and ANN models were compared by receiver-operating characteristics curves. RESULTS: Aspartate aminotransferase (p = 0.017), prothrombin time (p = 0.002), body mass index (BMI; p = 0.003), and fibrosis score of liver histology (p = 0.002) were found to be significant predictive factors by univariate analysis. The independent significant predicting factor was BMI by multivariate LR analysis (p = 0.0095). The area under receiver-operating characteristics of the ANN model was larger than that of the LR model (85 vs. 58.4%). CONCLUSIONS: It was found that BMI is an independent factor for identifying patients with favorable treatment response. A useful ANN model in predicting outcomes of standard treatment for CHC infection was developed and showed greater accuracy than the LR model.

A survival predictive model in patients undergoing radical resection of ampullary adenocarcinoma.

BACKGROUND/AIMS: Radical resection with either pancreaticoduodenectomy or pylorus-preserving pancreaticoduodenectomy is considered to be the standard treatment for most ampullary carcinomas, but the prognostic predictive model has not yet been developed. METHODOLOGY: The pretreatment, treatment, and follow-up variables of data of 47 patients undergoing radical resection for the ampullary carcinoma were analyzed to determine the favorable prognostic variables. Employing the Kaplan-Meier method, the cumulative survival rates of the ampullary carcinoma were calculated. By Cox regression model, a stepwise multivariate analysis was performed to analyze the contributing factors of the survival rate, and a predictive survival equation was obtained. RESULTS: With the results of the univariate analysis, the variables significantly associated with favorable prognosis were younger age (<63 years), TNM stage (stage I or II or III), and the degree of tumor differentiation (well or moderately differentiated). When the above three variables were examined as covariates by Cox regression in multivariate analysis, the TNM stage and the degree of tumor differentiation were independently correlated with the survival. A predictive survival equation obtained with the beta-coefficients of the above three variables was as follows: S (t) = [So (t)] P, P = exp (0.0234 x age - 1.8744 x tumor differentiation + 1.1576 x TNM stage) CONCLUSIONS: This predictive survival equation can predict the survival and the favorable outcome of patients treated with radical resection of ampullary carcinoma.