Development and validation of a clinical scoring system for predicting risk of HCC in asymptomatic individuals seropositive for anti-HCV antibodies

SIMarker: Cellular similarity detection and its application to diagnosis and prognosis of liver cancer

BACKGROUND

The emergence of single-cell technology offers a unique opportunity to explore cellular similarity and heterogeneity between precancerous diseases and solid tumors. However, there is lacking a systematic study for identifying and characterizing similarities at single-cell resolution.

METHODS

We developed SIMarker, a computational framework to detect cellular similarities between precancerous diseases and solid tumors based on gene expression at single-cell resolution. Taking hepatocellular carcinoma (HCC) as a case study, we quantified the cellular and molecular connections between HCC and cirrhosis. Core analysis modules of SIMarker is publicly available at https://github.com/xmuhuanglab/SIMarker ("SIM" means "similarity" and "Marker" means "biomarkers).

RESULTS

We found PGA5+ hepatocytes in HCC showed cirrhosis-like characteristics, including similar transcriptional programs and gene regulatory networks. Consequently, the genes constituting the gene expression program of these cirrhosis-like subpopulations were designated as cirrhosis-like signatures (CLS). Strikingly, our utilization of CLS enabled the development of diagnosis and prognosis biomarkers based on within-sample relative expression orderings of gene pairs. These biomarkers achieved high precision and concordance compared with previous studies.

CONCLUSIONS

Our work provides a systematic method to investigate the clinical translational significance of cellular similarities between HCC and cirrhosis, which opens avenues for identifying similar paradigms in other categories of cancers and diseases.

Risk-stratified approach by aMAP score for community population infected with hepatitis B and C to guide subsequent liver cancer screening practice: A cohort study with 10-year follow-up

The aim of this study was to determine whether the age-Male-ALBI-Platelet (aMAP) score is applicable in community settings and how to maximise its role in risk stratification. A total of thousand five hundred and three participants had an aMAP score calculated at baseline and were followed up for about 10 years to obtain information on liver cancer incidence and death. After assessing the ability of aMAP to predict liver cancer incidence and death in terms of differentiation and calibration, the optimal risk stratification threshold of the aMAP score was explored, based on absolute and relative risks. The aMAP score achieved higher area under curves (AUCs) (almost all above 0.8) within 10 years and exhibited a better calibration within 5 years. Regarding absolute risk, the risk of incidence of and death from liver cancer showed a rapid increase after an aMAP score of 55. The cumulative incidence (5-year: 8.3% vs. 1.3% and 10-year: 20.9% vs. 3.6%) and mortality (5-year: 6.7% vs. 1.1% and 10-year: 17.5% vs. 3.1%) of liver cancer in individuals with an aMAP score of ≥55 were significantly higher than in those with a score of <55 (Grey's test p  < .001). In terms of relative risk, the risk of death from liver cancer surpassed that from other causes after an aMAP score of ≥55 [HR = 1.38(1.02-1.87)]. Notably, the two types of death risk had opposite trends between the subpopulation with an aMAP score of ≥55 and < 55. To conclude, this study showed the value of the aMAP score in community settings and recommends using 55 as a new risk stratification threshold to guide subsequent liver cancer screening.

Risk stratification and early detection biomarkers for precision HCC screening

Hepatocellular carcinoma (HCC) mortality remains high primarily due to late diagnosis as a consequence of failed early detection. Professional societies recommend semi-annual HCC screening in at-risk patients with chronic liver disease to increase the likelihood of curative treatment receipt and improve survival. However, recent dynamic shift of HCC etiologies from viral to metabolic liver diseases has significantly increased the potential target population for the screening, whereas annual incidence rate has become substantially lower. Thus, with the contemporary HCC etiologies, the traditional screening approach might not be practical and cost-effective. HCC screening consists of (i) definition of rational at-risk population, and subsequent (ii) repeated application of early detection tests to the population at regular intervals. The suboptimal performance of the currently available HCC screening tests highlights an urgent need for new modalities and strategies to improve early HCC detection. In this review, we overview recent developments of clinical, molecular, and imaging-based tools to address the current challenge, and discuss conceptual framework and approaches of their clinical translation and implementation. These encouraging progresses are expected to transform the current "one-size-fits-all" HCC screening into individualized precision approaches to early HCC detection and ultimately improve the poor HCC prognosis in the foreseeable future.

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.

Computed Tomography-Measured Liver Volume Predicts the Risk of Hepatocellular Carcinoma Development in Chronic Hepatitis C Patients

AIM

In this retrospective cohort study, we evaluated the significance of liver volume in the prediction of hepatocellular carcinoma (HCC) in 277 chronic hepatitis C (CHC) patients who received dynamic computed tomography (CT) during surveillance.

METHODS

Liver volumes were measured on portal venous phase of CT images by using ImageJ software. Liver volume index, a ratio of the standard liver volume expected by weight and height to the measured liver volume, was calculated to adjust for normal variations. The cohort was randomly divided to derivation (n = 100) and validation sets (n = 177) for the generation of a liver volume-based Cox prediction model and validation of a liver volume-based nomogram, respectively.

RESULTS

The liver volume index was independent of weight or height, and it predicted further development of HCC (hazard ratio [HR] 16.30, 95% CI 6.70-39.62; p < 0.001). Liver cirrhosis, gamma-glutamyl transferase, and liver volume index were independent predictors of HCC, and nomogram-based prediction score from these three parameters identified high-risk patients at the cutoff of 110 in both derivation (p < 0.001) and validation cohort (p < 0.001).

CONCLUSION

Liver volume-based prediction model stratifies the risk of developing HCC in CHC patients whose initial dynamic CT study gave negative results.

Evaluation of ethnic influence in the application of a hepatocellular carcinoma predictive model for chronic hepatitis C

Currently, there is no well-established algorithm predicting hepatocellular carcinoma (HCC) development in untreated hepatitis C virus (HCV) patients. We aimed to validate an algorithm (risk evaluation of viral load elevation and associated liver disease/HCV [REVEAL-HCV]: age, AST, ALT, HCV RNA, HCV genotype, and cirrhosis) developed in Taiwanese patients. We analyzed 1381 (50.1% White, 14.7% Hispanic, 13.8% Asian of diverse origin, and 7.8% African American) adult treatment-naïve HCV patients (no viral co-infection, no HCC within 6 months) at 4 U.S. and one Hong Kong centers (11/1994-10/2017). Compared to the non-Asian cohort, the Asian cohort had a higher percentage of patients in the low-risk group (46.1% vs. 26.1%) and a lower percentage in the high-risk group (12.0% vs. 20.3%, p < 0.01). Overall, 5-year HCC incidence were 1.75%, 4.71%, and 24.4% for low, medium, and high-risk patients, respectively (p < 0.0001). For the overall cohort, area under receiving operating characteristic curve (AUROC) for HCC prediction were 0.83 (95% confidence interval [CI]: 0.72-0.93), 0.82 (95% CI: 0.75-0.88), and 0.84 (95% CI: 0.77-0.89) for 1-, 3-, and 5-year HCC risk, respectively. There was a slightly lower AUROC for Asians compared to the non-Asian cohort at 3 years (0.75 vs. 0.83) and 5 years (0.78 vs. 0.84), though this was not statistically significant. In multivariable analysis, we found male sex, presence of metabolic syndrome as well as the risk score categories to be independently associated with HCC but not ethnicity. The REVEAL-HCV risk score has good validity for both Asian and non-Asian populations. Further studies should consider additional factors, such as sex, metabolic syndrome, and treatment status.

Epidemiology of Virus Infection and Human Cancer

Seven viruses including the Epstein-Barr virus (EBV), hepatitis B virus (HBV), hepatitis C virus (HCV), Kaposi's sarcoma herpes virus (KSHV), human immunodeficiency virus, type-1 (HIV-1), human T cell lymphotrophic virus, type-1 (HTLV-1), and human papillomavirus (HPV) have been classified as Group 1 human carcinogens by the International Agency for Research on Cancer (IARC). The conclusions are based on the findings of epidemiological and mechanistic studies. EBV, HPV, HTLV-1, and KSHV are direct carcinogens; HBV and HCV are indirect carcinogens through chronic inflammation; and HIV-1 is an indirect carcinogen through immune suppression. Some viruses may cause more than one cancer, while some cancers may be caused by more than one virus. However, only a proportion of persons infected by these oncogenic viruses will develop specific cancers. A series of studies have been carried out to assess the viral, host, and environmental cofactors of EBV-associated nasopharyngeal carcinoma, HBV/HCV-associated hepatocellular carcinoma, and HPV-associated cervical carcinoma. Persistent infection, high viral load, and viral genotype are important risk predictors of these virus-caused cancers. Risk calculators incorporating host and viral risk predictors have been developed for the prediction of long-term risk of hepatocellular carcinoma, nasopharyngeal carcinoma and cervical cancer. These risk calculators are useful for the triage and clinical management of infected patients. Both clinical trials and national programs of immunization, antiviral therapy and screening have demonstrated a significant reduction in the incidence of cancers caused by HBV, HCV, and HPV. Future research on gene-gene and gene-environment interactions of oncogenic viruses and the human host using large-scale longitudinal studies with serial measurements of biosignatures are in urgent need.

Clinical and Molecular Prediction of Hepatocellular Carcinoma Risk

Prediction of hepatocellular carcinoma (HCC) risk becomes increasingly important with recently emerging HCC-predisposing conditions, namely non-alcoholic fatty liver disease and cured hepatitis C virus infection. These etiologies are accompanied with a relatively low HCC incidence rate (~1% per year or less), while affecting a large patient population. Hepatitis B virus infection remains a major HCC risk factor, but a majority of the patients are now on antiviral therapy, which substantially lowers, but does not eliminate, HCC risk. Thus, it is critically important to identify a small subset of patients who have elevated likelihood of developing HCC, to optimize the allocation of limited HCC screening resources to those who need it most and enable cost-effective early HCC diagnosis to prolong patient survival. To date, numerous clinical-variable-based HCC risk scores have been developed for specific clinical contexts defined by liver disease etiology, severity, and other factors. In parallel, various molecular features have been reported as potential HCC risk biomarkers, utilizing both tissue and body-fluid specimens. Deep-learning-based risk modeling is an emerging strategy. Although none of them has been widely incorporated in clinical care of liver disease patients yet, some have been undergoing the process of validation and clinical development. In this review, these risk scores and biomarker candidates are overviewed, and strategic issues in their validation and clinical translation are discussed.

Development and Validation of a Risk Scoring System for Cephamycin-Associated Hemorrhagic Events

Cephamycin-associated hemorrhages have been reported since their launch. This research aimed to determine risk factors for cephamycin-associated hemorrhagic events and produce a risk scoring system using National Taiwan University Hospital (NTUH) database. Patients who were older than 20 years old and consecutively used study antibiotics for more than 48 hours (epidode) at NTUH between January 1^st, 2009 and December 31^st, 2015 were included. The population was divided into two cohorts for evaluation of risk factors and validation of the scoring system. Multivariate logistic regression was used for the assessment of the adjusted association between factors and the outcome of interest. Results of the multivariate logistic regression were treated as the foundation to develop the risk scoring system. There were 46402 and 22681 episodes identified in 2009–2013 and 2014–2015 cohorts with 356 and 204 hemorrhagic events among respective cohorts. Use of cephamycins was associated with a higher risk for hemorrhagic outcomes (aOR 2.03, 95% CI 1.60–2.58). Other risk factors included chronic hepatic disease, at least 65 years old, prominent bleeding tendency, and bleeding history. A nine-score risk scoring system (AUROC = 0.8035, 95% CI 0.7794–0.8275; Hosmer-Lemeshow goodness-of-fit test p = 0.1044) was developed based on the identified risk factors, with higher scores indicating higher risk for bleeding. Use of cephamycins was associated with more hemorrhagic events compared with commonly used penicillins and cephalosporins. The established scoring system, CHABB, may help pharmacists identify high-risk patients and provide recommendations according to the predictive risk, and eventually enhance the overall quality of care.

Risk score system for the prediction of hepatocellular carcinoma in patients with type 2 diabetes: Taiwan Diabetes Study

This study aims to develop a risk score system for hepatocellular carcinoma (HCC) in patients with type 2 diabetes using the Taiwan National Diabetes Care Management Program database. This retrospective cohort study included 31,723 Chinese patients who had type 2 diabetes, aged 30-84 years. Participants were randomly grouped into derivation and validation sets in 2:1 ratio. Cox proportional hazard regression models were used to identify the risk factors of HCC in the derivation set. Discrimination ability of the model was assessed by means of a receiver operating characteristic curve and performance was expressed as the c statistic, assessed internally on validation data sets. The average follow-up was 8.33 years with 748 HCC incident cases in the derivation set. The final HCC risk score system included age (-2 to 8 points), gender (0-2 points), smoking (0-2 points), variation in hemoglobin A1c (0-1 point), serum glutamic-pyruvic transaminase (0-6 points), liver cirrhosis (9 points), hepatitis B (4 points), hepatitis C (3 points), antidiabetes medications (0-3 points), and antihyperlipidemia medications and total/high-density lipoprotein cholesterol ratio (-4 to 2 points). The HCC risk score was the sum of these individual scores (range -6 to 40). The area under the receiver operating characteristic curve for 3-, 5-, and 10-year HCC risks was 0.81, 0.80, and 0.77 for the derivation set, respectively. This HCC risk score system has good prediction accuracy and discriminatory ability, and serves a simple tool for HCC risk prediction.

Risk factors and prevention of hepatocellular carcinoma in the era of precision medicine

Patients who develop chronic fibrotic liver disease, caused by viral or metabolic aetiologies, are at a high risk of developing hepatocellular carcinoma (HCC). Even after complete HCC tumour resection or ablation, the carcinogenic tissue microenvironment in the remnant liver can give rise to recurrent de novo HCC tumours, which progress into incurable, advanced-stage disease in most patients. Thus, early detection and prevention of HCC development is, in principle, the most impactful strategy to improve patient prognosis. However, a "one-size-fits-all" approach to HCC screening for early tumour detection, as recommended by clinical practice guidelines, is utilised in less than 20% of the target population, and the performance of screening modalities, including ultrasound and alpha-fetoprotein, is suboptimal. Furthermore, optimal screening strategies for emerging at-risk patient populations, such as those with chronic hepatitis C after viral cure, or those with non-cirrhotic, non-alcoholic fatty liver disease remain controversial. New HCC biomarkers and imaging modalities may improve the sensitivity and specificity of HCC detection. Clinical and molecular HCC risk scores will enable precise HCC risk prediction followed by tailoured HCC screening of individual patients, maximising cost-effectiveness and optimising allocation of limited medical resources. Several aetiology-specific and generic HCC chemoprevention strategies are evolving. Epidemiological and experimental studies have identified candidate chemoprevention targets and therapies, including statins, anti-diabetic drugs, and selective molecular targeted agents, although their clinical testing has been limited by the lengthy process of cancer development that requires long-term, costly studies. Individual HCC risk prediction is expected to overcome the challenge by enabling personalised chemoprevention, targeting high-risk patients for precision HCC prevention and substantially improving the dismal prognosis of HCC.

Diabetes, hepatocellular carcinoma, and mortality in hepatitis C-infected patients: A population-based cohort study

BACKGROUND AND AIM

The effect of diabetes mellitus (DM) on the development of hepatocellular carcinoma (HCC) and all-cause mortality after HCC development in chronic hepatitis C virus (HCV)-infected patients remains inconclusive. This cohort study aimed to investigate these issues using the Taiwanese National Health Insurance Research Database.

METHODS

We retrieved and enrolled newly diagnosed DM patients with HCV from the Longitudinal Cohort of Diabetes Patients database. Propensity score matching-including age, sex, alcohol-related liver disease, and baseline liver cirrhosis-was used to identify and enroll HCV patients without DM from the Longitudinal Health Insurance Database (n = 1686). A multi-state model was used to investigate transitions from "start-to-HCC," "start-to-death," and "HCC-to-death."

RESULTS

The multi-state model showed higher cumulative hazards for "start-to-HCC," "start-to-death," and "HCC-to-death" transitions in the DM (vs non-DM) cohort. The cumulative probability of death with or without HCC after 10 years of follow-up was higher in the DM cohort than in the non-DM cohort. Multivariable transition-specific Cox models demonstrated that DM significantly increased the risk for transition from "start-to-HCC" (adjusted hazard ratio [aHR] 1.36; 95% confidence interval [CI] 1.16-1.59; P < 0.001), "start-to-death" (aHR 2.61; 95% CI: 2.05-3.33; P < 0.001), and "HCC-to-death" (aHR 1.36; 95% CI 1.10-1.68; P = 0.005). The effect of liver cirrhosis on "start-to-HCC" and "start-to-death" transitions decreased over time, particularly within 2 years.

CONCLUSIONS

Diabetes mellitus increased the risk of HCC development in HCV-infected patients and the risk of all-cause mortality in patients with or without HCC.

Time-Degenerative Factors and the Risk of Hepatocellular Carcinoma after Antiviral Therapy among Hepatitis C Virus Patients: A Model for Prioritization of Treatment

Purpose: Age and hepatic fibrosis are the factors that increase the risk of hepatocellular carcinoma over time. We aimed to explore their impact at the initiation of antiviral therapy on hepatocellular carcinoma among chronic hepatitis C (CHC) patients.Experimental Design: A total of 1,281 biopsy-proven CHC patients receiving IFN-based therapy were followed for a mean period of 5.5 years.Results: The 5-year cumulative incidence of hepatocellular carcinoma did not differ between non-sustained virological response (SVR) and SVR patients who were <40 years old (7.7% vs. 0.5%, P = 0.1) but was significantly higher in non-SVR patients between 40 and 55 years old (18.0% vs. 1.3%, P < 0.001) and >55 years old (15.1% vs. 7.9%, P = 0.03). Compared with SVR, non-SVR was independently predictive of hepatocellular carcinoma in patients 40 to 55 years old [HR/95% confidence intervals (CI), 10.92/3.78-31.56; P < 0.001] and >55 years old (HR/CI, 1.96/1.06-3.63; P = 0.03) but not in patients <40 years old (HR/CI, 2.76/0.41-18.84; P = 0.3). The 5-year cumulative incidence of hepatocellular carcinoma did not differ between non-SVR and SVR patients whose fibrosis stage was F0-1 (4.6% vs. 1.9%, P = 0.25) but was higher in non-SVR patients with F2-3 (21.4% vs. 4.3%, P < 0.001) or F4 (33.5% vs. 8.4%, P = 0.002). Compared with SVR, non-SVR was independently predictive of hepatocellular carcinoma in patients with F2-3 (HR/CI, 4.36/2.10-9.03; P < 0.001) and F4 (HR/CI, 3.84/1.59-9.30; P = 0.03) but not in those with F0-1 (HR/CI, 1.53/0.49-4.74; P = 0.47).Conclusions: Delayed hepatitis C virus clearance for patients with CHC >40 years old or with a fibrosis stage >2 increases the risk of hepatocellular carcinoma over time. Clin Cancer Res; 23(7); 1690-7. ©2016 AACR.

Tailored algorithms for hepatocellular carcinoma surveillance: Is one-size-fits-all strategy outdated?

PURPOSE OF REVIEW

Current clinical practice guidelines recommend regular hepatocellular carcinoma (HCC) surveillance with biannual ultrasound with or without serum alpha-fetoprotein uniformly applied to all patients with cirrhosis. However, clinical implementation of this one-size-fits-all strategy has been challenging as evidenced by very low application rate below 20% due to various reasons, including suboptimal performance of the surveillance modalities.

RECENT FINDINGS

Newly emerging imaging techniques such as abbreviated MRI (AMRI) and molecular HCC risk biomarkers have increasingly become available for clinical evaluation and implementation. These technologies may have a potential to reshape HCC surveillance by enabling tailored strategies. This would involve performing optimized surveillance tests according to individual HCC risk, and allocating limited medical resources for HCC surveillance based on cost-effectiveness.

SUMMARY

Tailored HCC surveillance could lead to achievement of precision HCC care and substantial improvement of the current dismal patient prognosis.

Genetics Variants and Serum Levels of MHC Class I Chain-related A in Predicting Hepatocellular Carcinoma Development in Chronic Hepatitis C Patients Post Antiviral Treatment

Background/aims

The genome-wide association study has shown that MHC class I chain-related A (MICA) genetic variants were associated with hepatitis C virus (HCC) related hepatocellular carcinoma. The impact of the genetic variants and its serum levels on post-treatment cohort is elusive.

Methods

MICA rs2596542 genotype and serum MICA (sMICA) levels were evaluated in 705 patients receiving antiviral therapy.

Results

Fifty-eight (8·2%) patients developed HCC, with a median follow-up period of 48·2 months (range: 6–129 months). The MICA A allele was associated with a significantly increased risk of HCC development in cirrhotic non-SVR patients but not in patients of non-cirrhotic and/or with SVR. For cirrhotic non-SVR patients, high sMICA levels (HR/CI: 5·93/1·86–26.38·61, P = 0·002) and the MICA rs2596542 A allele (HR/CI: 4·37/1·52–12·07, P = 0·002) were independently associated with HCC development. The risk A allele or GG genotype with sMICA > 175 ng/mL provided the best accuracy (79%) and a negative predictive value of 100% in predicting HCC.

Conclusions

Cirrhotic patients who carry MICA risk alleles and those without risk alleles but with high sMICA levels possessed the highest risk of HCC development once they failed antiviral therapy.

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MICA rs2596542 SNP predicts HCC development in LC patients with persistent viremia.

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High sMICA levels predicts HCC occurrence in LC patients without SVR

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Combining the 2 surrogate markers enhance the predicting power of HCC.

The genome-wide association study has shown that MHC class I chain-related A (MICA) genetic variants were associated with hepatitis C virus (HCC) related hepatocellular carcinoma. The impact of the genetic variants and its serum levels on post-treatment cohort is elusive. We demonstrated that cirrhotic patients who carry MICA risk alleles and those without risk alleles but with high sMICA levels possessed the highest risk of HCC development once they failed antiviral therapy. Combining the host genetic variants of MICA gene and serum levels of MICA proteins greatly enhanced the predictive power in the high-risk population, which provides insight for closer follow-up strategies and re-treatment priority in the era of direct antiviral agents.

Nomogram for individualized prediction of hepatocellular carcinoma occurrence in hepatitis C virus cirrhosis (ANRS CO12 CirVir)

The aim of this work was to develop an individualized score for predicting hepatocellular carcinoma (HCC) in patients with hepatitis C (HCV)-compensated cirrhosis. Among 1,323 patients with HCV cirrhosis enrolled in the French prospective ANRS CO12 CirVir cohort, 720 and 360 were randomly assigned to training and validation sets, respectively. Cox's multivariate model was used to predict HCC, after which a nomogram was computed to assess individualized risk. During follow-up (median, 51.0 months), 103 and 39 patients developed HCC in the training and validation sets, respectively. Five variables were independently associated with occurrence of HCC: age > 50 years (hazard ratio [HR], 1.94; 95% confidence interval [CI], 1.16; 3.25; P = 0.012); past excessive alcohol intake (HR, 1.55; 95% CI, 1.02; 2.36; P = 0.041); low platelet count (<100 Giga/mm(3) : HR, 2.70; 95% CI, 1.62; 4.51; P < 0.001; [100; 150] Giga/mm(3) : HR, 1.87; 95% CI, 1.10; 3.18; P = 0.021); gamma-glutamyl transpeptidase above the upper limit of normal (HR, 1.96; 95% CI, 1.11; 3.47; P = 0.021); and absence of a sustained virological response during follow-up (HR, 3.02; 95% CI, 1.67; 5.48; P < 0.001). An 11-point risk score was derived from the training cohort and validated in the validation set. Based on this score, the population was stratified into three groups, in which HCC development gradually increased, from 0% to 30.1% at 5 years for patients with the lowest (≤3) and highest (≥8) scores (P < 0.001). Using this score, a nomogram was built enabling individualized prediction of HCC occurrence at 1, 3, and 5 years.

CONCLUSION

This HCC score can accurately predict HCC at an individual level in French patients with HCV cirrhosis. (Hepatology 2016;64:1136-1147).

APASL consensus statements and recommendations for hepatitis C prevention, epidemiology, and laboratory testing

The Asian Pacific Association for the Study of the Liver (APASL) convened an international working party on "APASL consensus statements and recommendations for management of hepatitis C" in March 2015 to revise the "APASL consensus statements and management algorithms for hepatitis C virus infection" (Hepatol Int 6:409-435, 2012). The working party consisted of expert hepatologists from the Asian-Pacific region gathered at the Istanbul Congress Center, Istanbul, Turkey on 13 March 2015. New data were presented, discussed, and debated during the course of drafting a revision. Participants of the consensus meeting assessed the quality of the cited studies. The finalized recommendations for hepatitis C prevention, epidemiology, and laboratory testing are presented in this review.

Circulating Osteopontin and Prediction of Hepatocellular Carcinoma Development in a Large European Population

We previously identified osteopontin (OPN) as a promising marker for the early detection of hepatocellular carcinoma (HCC). In this study, we investigated the association between prediagnostic circulating OPN levels and HCC incidence in a large population-based cohort. A nested case-control study was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. During a mean follow-up of 4.8 years, 100 HCC cases were identified. Each case was matched to two controls and OPN levels were measured in baseline plasma samples. Viral hepatitis, liver function, and α-fetoprotein (AFP) tests were also conducted. Conditional logistic regression models were used to calculate multivariable odds ratio (OR) and 95% confidence intervals (95% CI) for OPN levels in relation to HCC. Receiver operating characteristics curves were constructed to determine the discriminatory accuracy of OPN alone or in combination with other liver biomarkers in the prediction of HCC. OPN levels were positively associated with HCC risk (per 10% increment, ORmultivariable = 1.30; 95% CI, 1.14-1.48). The association was stronger among cases diagnosed within 2 years of follow-up. Adding liver function tests to OPN improved the discriminatory performance for subjects who developed HCC (AUC = 0.86). For cases diagnosed within 2 years, the combination of OPN and AFP was best able to predict HCC risk (AUC = 0.88). The best predictive model for HCC in this low-risk population is OPN in combination with liver function tests. Within 2 years of diagnosis, the combination of OPN and AFP best predicted HCC development, suggesting that measuring OPN and AFP could identify high-risk groups independently of a liver disease diagnosis. Cancer Prev Res; 9(9); 758-65. ©2016 AACR.

Dynamic prediction of risk of liver-related outcomes in chronic hepatitis C using routinely collected data

Accuracy of risk assessments for clinical outcomes in patients with chronic liver disease has been limited given the nonlinear nature of disease progression. Longitudinal prediction models may more accurately capture this dynamic risk. The aim of this study was to construct accurate models of short- and long-term risk of disease progression in patients with chronic hepatitis C by incorporating longitudinal clinical data. Data from the Hepatitis C Antiviral Long-term Treatment Against Cirrhosis trial were analysed (n = 533 training cohort; n = 517 validation cohort). Outcomes included a composite liver outcome (liver-related death, decompensation, hepatocellular carcinoma (HCC) or liver transplant), decompensation, HCC and overall mortality. Longitudinal models were constructed for risk of outcomes at 1, 3 and 5 years and compared with models using data at baseline only or baseline and a single follow-up time point. A total of 25.1% of patients in the training and 20.8% in the validation cohort had an outcome during a median follow-up of 6.5 years (range 0.5-9.2). The most important predictors were as follows: albumin, aspartate aminotransferase/alanine aminotransferase ratio, bilirubin, alpha-fetoprotein and platelets. Longitudinal models outperformed baseline models with higher true-positive rates and negative predictive values. The areas under the receiver-operating characteristic curve for the composite longitudinal model were 0.89 (0.80-0.96), 0.83 (0.76-0.88) and 0.81 (0.75-0.87) for 1-, 3-, and 5-year risk prediction, respectively. Model performance was retained for decompensation and overall mortality but not HCC. Longitudinal prediction models provide accurate risk assessments and identify patients in need of intensive monitoring and care.

The Hepatitis Viral Status in Patients With Hepatocellular Carcinoma: a Study of 3843 Patients From Taiwan Liver Cancer Network

Hepatocellular carcinoma (HCC) is the leading cancer death in Taiwan. Chronic viral hepatitis infections have long been considered as the most important risk factors for HCC in Taiwan. The previously published reports were either carried out by individual investigators with small patient numbers or by large endemic studies with limited viral marker data. Through collaboration with 5 medical centers across Taiwan, Taiwan liver cancer network (TLCN) was established in 2005. All participating centers followed a standard protocol to recruit liver cancer patients along with their biosamples and clinical data. In addition, detailed viral marker analysis for hepatitis B virus (HBV) and hepatitis C virus (HCV) were also performed. This study included 3843 HCC patients with available blood samples in TLCN (recruited from November 2005 to April 2011). There were 2153 (56.02%) patients associated with HBV (HBV group); 969 (25.21%) with HCV (HCV group); 310 (8.07%) with both HBV and HCV (HBV+HCV group); and 411 (10.69%) were negative for both HBV and HCV (non-B non-C group). Two hundred two of the 2463 HBV patients (8.20%) were HBsAg(-), but HBV DNA (+). The age, gender, cirrhosis, viral titers, and viral genotypes were all significantly different between the above 4 groups of patients. The median age of the HBV group was the youngest, and the cirrhotic rate was lowest in the non-B non-C group (only 25%). This is the largest detailed viral hepatitis marker study for HCC patients in the English literatures. Our study provided novel data on the interaction of HBV and HCV in the HCC patients and also confirmed that the HCC database of TLCN is highly representative for Taiwan and an important resource for HCC research.

Hepatitis C viral infection increases the risk of lymphoid-neoplasms: A population-based cohort study

Chronic hepatitis C viral (HCV) infection has been associated with non-Hodgkin's lymphoma (NHL); however, the results are inconsistent among regions with different HCV prevalence rates. The temporal relationship, risk estimates, and association between HCV and lymphoid-neoplasms remain unclear. This study investigated the temporal relationship between HCV infection and lymphoid-neoplasms using a nationwide population-based cohort. Patients with chronic HCV infection were retrieved from the Taiwan National Health Insurance Research Database during 2001-2005 and designated as the HCV cohort. Those with prior malignancies or coinfected with hepatitis B or human immunodeficiency virus were excluded. The age, sex, and comorbidities, including rheumatological disorders and diabetes, were matched by propensity scores to another non-HCV cohort. Both cohorts were followed longitudinally until 2009 for a new diagnosis of any lymphoid-neoplasms or NHL. A total of 11,679 HCV and 46,716 non-HCV patients were included and followed for 8 years. The incidence rates of any lymphoid-neoplasms and NHL were significantly greater in the HCV cohort than the non-HCV cohort (48.4 versus 22.1, and 37.0 versus 17.5 per 100,000 person-years, respectively, both P < 0.001), even after we excluded lymphoid-neoplasms developed within the first year of follow-up. Cox proportional hazards regression analysis (after adjustment for age, sex, numbers of annual medical visits during follow-up, and comorbidities) indicated that HCV infection was associated with an increased risk of either any lymphoid-neoplasms (hazard ratio = 2.30, 95% confidence interval 1.55-3.43, P < 0.0001) or NHL (hazard ratio = 2.00, 95% confidence interval 1.27-3.16, P = 0.003).

CONCLUSION

After adjustment for confounders and biases, chronic HCV infection is temporally associated with a two-fold increased risk of lymphoid-neoplasms, especially NHL, in Asian patients; additional large studies are needed to explore whether HCV eradication can reduce the incidence of lymphoid-neoplasms.

Molecular prognostic prediction in liver cirrhosis

The natural history of cirrhosis varies and therefore prognostic prediction is critical given the sizable patient population. A variety of clinical prognostic indicators have been developed and enable patient risk stratification although their performance is somewhat limited especially within relatively earlier stage of disease. Molecular prognostic indicators are expected to refine the prediction, and potentially link a subset of patients with molecular targeted interventions that counteract poor prognosis. Here we overview clinical and molecular prognostic indicators in the literature, and discuss critical issues to successfully define, evaluate, and deploy prognostic indicators as clinical scores or tests. The use of liver biopsy has been diminishing due to sampling variability on fibrosis assessment and emergence of imaging- or lab test-based fibrosis assessment methods. However, recent rapid developments of genomics technologies and selective molecular targeted agents has highlighted the need for biopsy tissue specimen to explore and establish molecular information-guided personalized/stratified clinical care, and eventually achieve “precision medicine”.

Association of diabetes and PNPLA3 genetic variants with disease severity of patients with chronic hepatitis C virus infection

BACKGROUND & AIMS

Genetic variants of patatin-like phospholipase domain-containing 3 (PNPLA3) and diabetes are associated with liver disease severity, in patients with chronic hepatitis C (CHC) infection. We aimed at exploring their interaction in determining hepatitis C virus (HCV)-related liver fibrosis.

METHODS

The PNPLA3 genetic polymorphism at rs738409 was verified in 1077 biopsy-proven CHC patients. Other clinical variables, including diabetes status, were analysed for factors associated with bridging fibrosis.

RESULTS

Patients with advanced liver fibrosis had higher proportions of the GG genotype (14.5% vs. 10.4%, p=0.06 in recessive model) and GG/GC genotype carriage (64.0% vs. 56.8%, p=0.03 in dominant model). Stepwise logistic regression analysis revealed that factors predictive of advanced liver fibrosis included age (odds ratio [OR]: 1.02, 95% confidence intervals [CI]: 1.008-1.037, p=0.002), diabetes (OR: 1.81, CI: 1.236-2.653, p=0.002), α-fetoprotein (OR: 1.006, CI: 1.001-1.01, p=0.01), platelet counts (OR: 1.009, CI: 1.006-1.012, p<0.001), and PNPLA3 rs738409 CG/GG genotype (OR: 1.34, CI: 1.006-1.785, p=0.046). When patients were grouped according to their diabetes status, the PNPLA3 genetic variants were associated with advanced liver fibrosis in diabetic patients only, but not in non-diabetic patients. The PNPLA3 gene was the most important predictive factor of bridging fibrosis in diabetic patients, using the recessive model (OR: 4.53, CI: 1.356-15.106, p=0.014) or the dominant model (OR: 2.20, CI: 1.026-4.734, p=0.04). Compared to non-diabetic patients, patients with the diabetes/GG genotype were more likely to have advanced liver fibrosis (OR: 8.79, CI: 2.889-26.719, p<0.001), followed by those with diabetes/non-GG genotype (OR: 1.55, CI: 1.048-2.286, p=0.03).

CONCLUSIONS

The effect of PNPLA3 genetic variants in HCV-related advanced liver fibrosis was enhanced in diabetic patients. The strong genetic-environmental interaction contributed to the high risk of advanced liver disease in CHC patients.