Lifestyle and Environmental Approaches for the Primary Prevention of Hepatocellular Carcinoma

Screening and interventions to prevent nonalcoholic fatty liver disease/nonalcoholic steatohepatitis-associated hepatocellular carcinoma

Liver cancer is the sixth most commonly diagnosed cancer worldwide, with hepatocellular carcinoma (HCC) comprising most cases. Besides hepatitis B and C viral infections, heavy alcohol use, and nonalcoholic steatohepatitis (NASH)-associated advanced fibrosis/cirrhosis, several other risk factors for HCC have been identified (i.e. old age, obesity, insulin resistance, type 2 diabetes). These might in fact partially explain the occurrence of HCC in non-cirrhotic patients without viral infection. HCC surveillance through effective screening programs is still an unmet need for many nonalcoholic fatty liver disease (NAFLD) patients, and identification of pre-cirrhotic individuals who progress to HCC represents a substantial challenge in clinical practice at the moment. Patients with NASH-cirrhosis should undergo systematic HCC surveillance, while this might be considered in patients with advanced fibrosis based on individual risk assessment. In this context, interventions that potentially prevent NAFLD/ NASH-associated HCC are needed. This paper provided an overview of evidence related to lifestyle changes (i.e. weight loss, physical exercise, adherence to healthy dietary patterns, intake of certain dietary components, etc.) and pharmacological interventions that might play a protective role by targeting the underlying causative factors and pathogenetic mechanisms. However, well-designed prospective studies specifically dedicated to NAFLD/NASH patients are still needed to clarify the relationship with HCC risk.

Liver cancer risk-predictive molecular biomarkers specific to clinico-epidemiological contexts

Hepatocellular carcinoma (HCC) risk prediction is increasingly important because of the low annual HCC incidence in patients with the rapidly emerging non-alcoholic fatty liver disease or cured HCV infection. To date, numerous clinical HCC risk biomarkers and scores have been reported in literature. However, heterogeneity in clinico-epidemiological context, e.g., liver disease etiology, patient race/ethnicity, regional environmental exposure, and lifestyle-related factors, obscure their real clinical utility and applicability. Proper characterization of these factors will help refine HCC risk prediction according to certain clinical context/scenarios and contribute to improved early HCC detection. Molecular factors underlying the clinical heterogeneity encompass various features in host genetics, hepatic and systemic molecular dysregulations, and cross-organ interactions, which may serve as clinical-context-specific biomarkers and/or therapeutic targets. Toward the goal to enable individual-risk-based HCC screening by incorporating the HCC risk biomarkers/scores, their assessment in patient with well-defined clinical context/scenario is critical to gauge their real value and to maximize benefit of the tailored patient management for substantial improvement of the poor HCC prognosis.

Statins Reduce Hepatocellular Carcinoma Risk in Patients with Chronic Kidney Disease and End-Stage Renal Disease: A 17-Year Longitudinal Study

Simple Summary

Statins are medicines used to treat patients with high lipid levels (hyperlipidemia). Studies have reported that patients undergoing statin therapy are at reduced risk of developing liver cancer. In this study, we compared the risk of developing liver cancer among hyperlipidemic patients with and without statin therapy in three patient groups classified by renal function: normal renal function (NRF) group, chronic kidney disease (CKD) not requiring dialysis, and dialysis-dependent end stage of real disease (ESRD). Our results showed that the risk of developing liver cancer increased progressively from NRF group to CKD and ESRD groups, but was lower for patients receiving statins treatment than non-treated patients. We also found that the statin therapy effectiveness was better in patients taking hydrophilic statins than in those taking lipophilic statins, and in patients taking statin-ezetimibe combination than in those taking statin alone, particularly in the NRF group. Ezetimibe is also an effective option of treating hyperlipidemia.

Abstract

Hepatocellular carcinoma (HCC) is the most common cancer in end-stage renal disease (ESRD) patients in Taiwan. Whether statin therapy associated with the HCC risk in hyperlipidemic patients with chronic kidney disease (CKD) and ESRD is unclear. Using population-based insurance claim data from Taiwan, we identified from hyperlipidemic patients taking statins or not (677,364 versus 867,707) in 1999–2015. Among them, three pairs of propensity score matched statin and non-statin cohorts were established by renal function: 413,867 pairs with normal renal function (NRF), 46,851 pairs with CKD and 6372 pairs with ESRD. Incidence rates of HCC were compared, by the end of 2016, between statin and non-statin cohorts, between hydrophilic statins (HS) and lipophilic statins (LS) users, and between statin-ezetimibe combination therapy (SECT) and statin monotherapy (SM) users. The HCC incidence increased progressively from NRF to CKD and ESRD groups, was lower in the statin cohort than in the non-statin cohort, with the differences of incidence per 10,000 person-years increased from (7.77 vs. 21.4) in NRF group to (15.8 vs. 37.1) in CKD group to (19.1 vs. 47.8) in ESRD group. The incidence increased with age, but the Cox method estimated hazard ratios showed a greater statin effectiveness in older patients. Among statin users, the HCC incidence was lower in HS users than in LS users, and lower in SECT users than in SM users, but the difference was significant only in the NRF group. Hyperlipidemic patients with CKD and ESRD receiving statins are at reduced HCC risks; the treatment effectiveness is superior for HS users than for LS users, and for SECT users than for SM users, but not significant.

Risk Factors and Prevention of Viral Hepatitis-Related Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common cancer in the world, and its incidence is increasing yearly. Hepatitis B virus (HBV) infection and hepatitis C virus (HCV) infection are important causes of HCC. Liver cirrhosis, age, sex, smoking and drinking, and metabolic risk factors will increase the risk of cancer in HBV/HCV patients. And viral load, APRI, FIB-4, and liver stiffness can all predict the risk of HCC in patients with viral infection. In addition, effective prevention strategies are essential in reducing the risk of HCC. The prevention of HCC involves mainly tertiary prevention strategies, while the primary prevention is based on standardized vaccine injections to prevent the occurrence of HBV/HCV. Eliminating the route of transmission and vaccination will lead to a decrease in the incidence of HCC. Secondary prevention involves effective antiviral treatment of HBV/HCV to prevent the disease from progressing to HCC, and tertiary prevention is actively treating HCC to prevent its recurrence.

Application of Risk Scores for Hepatocellular Carcinoma in Patients with Chronic Hepatitis B: Current Status and Future Perspective

Accurate risk prediction for hepatocellular carcinoma (HCC) among patients with chronic hepatitis B (CHB) may guide treatment strategies including initiation of antiviral therapy and also inform implementation of HCC surveillance. There have been 26 risk scores developed to predict HCC in CHB patients with (n = 14) or without (n = 12) receiving antiviral treatment; all of them invariably include age in the scoring formula. Virological biomarkers of replicative activities (i.e., hepatitis B virus DNA level or hepatitis B envelope antigen status) are frequently included in the scores derived from patients with untreated CHB, whereas measurements that gauge severity of liver fibrosis and/or reserve of hepatic function (i.e., cirrhosis diagnosis, liver stiffness measurement, platelet count, or albumin) are essential components in the scores developed from treated patients. External validation is a prerequisite for clinical application but not yet performed for all scores. For the future, higher predictive accuracy may be achieved with machine learning based on more comprehensive data.

Distinguishing Hepatocellular Carcinoma From Hepatic Inflammatory Pseudotumor Using a Nomogram Based on Contrast-Enhanced Ultrasound

BACKGROUND

Hepatocellular carcinoma (HCC) and hepatic iflammatory pseudotumor (IPT) share similar symptoms and imaging features, which makes it challenging to distinguish from each other in clinical practice. This study aims to develop a predictive model based on contrast-enhanced ultrasound (CEUS) and clinical features to discriminate HCC from IPT.

METHODS

Sixty-two IPT and 146 HCC patients were enrolled in this study, where pathological diagnosis served as the reference standard for diagnosis. Clinical and ultrasound imaging data including CEUS features: enhancement degree during arterial phase, portal phase and delayed phase, enhancement pattern, early washout within 60 s, feeding artery, peritumoral vessels, peritumoral enhancement, and margin of nonenhanced area were retrospectively collected. Imaging data were reviewed by two experienced ultrasound doctors. Patients were randomly assigned to training and validation sets. Chi-squared test followed by LASSO regression was performed on ultrasonographic features in the training set to identify the most valuable features that distinguish HCC from IPT, based on which the sonographic score formula was generated. With the significant clinical and ultrasonographic indicators, a nomogram was developed. The performance of the nomogram was verified by ROC curve and decision curve analysis (DCA) with the comparison with sonographic score and the ultrasound doctor's diagnosis.

RESULTS

The most valuable ultrasonographic features that distinguish between HCC and IPT were enhancement degree during arterial phase, early washout, peritumoral vessels, peritumoral enhancement, and liver background. The sonographic score based on these features was verified to be an independent factor that predicts the diagnosis (p = 0.003). Among the clinical indicators, AFP (p = 0.009) and viral hepatitis infection (p = 0.004) were significant. Sonographic score, AFP, and viral hepatitis were used to construct a predictive nomogram. The AUC of the nomogram was 0.989 and 0.984 in training and validation sets, respectively, which were higher than those of sonographic score alone (0.938 and 0.958) or the ultrasound doctor's diagnosis (0.794 and 0.832). DCA showed the nomogram provided the greatest clinical usefulness.

CONCLUSION

A predictive nomogram based on a sonographic signature improved the diagnostic performance in distinguishing HCC and IPT, which may help with individualized diagnosis and treatment in clinical practice.