Article Search
검색
검색 팝업 닫기

Metrics

Help

  • 1. Aims and Scope

    Gut and Liver is an international journal of gastroenterology, focusing on the gastrointestinal tract, liver, biliary tree, pancreas, motility, and neurogastroenterology. Gut atnd Liver delivers up-to-date, authoritative papers on both clinical and research-based topics in gastroenterology. The Journal publishes original articles, case reports, brief communications, letters to the editor and invited review articles in the field of gastroenterology. The Journal is operated by internationally renowned editorial boards and designed to provide a global opportunity to promote academic developments in the field of gastroenterology and hepatology. +MORE

  • 2. Editorial Board

    Editor-in-Chief + MORE

    Editor-in-Chief
    Yong Chan Lee Professor of Medicine
    Director, Gastrointestinal Research Laboratory
    Veterans Affairs Medical Center, Univ. California San Francisco
    San Francisco, USA

    Deputy Editor

    Deputy Editor
    Jong Pil Im Seoul National University College of Medicine, Seoul, Korea
    Robert S. Bresalier University of Texas M. D. Anderson Cancer Center, Houston, USA
    Steven H. Itzkowitz Mount Sinai Medical Center, NY, USA
  • 3. Editorial Office
  • 4. Articles
  • 5. Instructions for Authors
  • 6. File Download (PDF version)
  • 7. Ethical Standards
  • 8. Peer Review

    All papers submitted to Gut and Liver are reviewed by the editorial team before being sent out for an external peer review to rule out papers that have low priority, insufficient originality, scientific flaws, or the absence of a message of importance to the readers of the Journal. A decision about these papers will usually be made within two or three weeks.
    The remaining articles are usually sent to two reviewers. It would be very helpful if you could suggest a selection of reviewers and include their contact details. We may not always use the reviewers you recommend, but suggesting reviewers will make our reviewer database much richer; in the end, everyone will benefit. We reserve the right to return manuscripts in which no reviewers are suggested.

    The final responsibility for the decision to accept or reject lies with the editors. In many cases, papers may be rejected despite favorable reviews because of editorial policy or a lack of space. The editor retains the right to determine publication priorities, the style of the paper, and to request, if necessary, that the material submitted be shortened for publication.

Search

Search

Year

to

Article Type

Original Article

Split Viewer

Prediction of Hepatocellular Carcinoma Development in Korean Patients after Hepatitis C Cure with Direct-Acting Antivirals

Hyeyeon Hong , Won-Mook Choi , Danbi Lee , Ju Hyun Shim , Kang Mo Kim , Young-Suk Lim , Han Chu Lee , Jonggi Choi

Department of Gastroenterology, Liver Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

Correspondence to: Jonggi Choi
ORCID https://orcid.org/0000-0002-7470-5850
E-mail j.choi@amc.seoul.kr

Received: September 3, 2022; Revised: December 30, 2022; Accepted: January 17, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Gut Liver 2024;18(1):147-155. https://doi.org/10.5009/gnl220386

Published online April 20, 2023, Published date January 15, 2024

Copyright © Gut and Liver.

Background/Aims: With the wide application of direct-acting antivirals (DAAs) for hepatitis C virus infection, the number of patients achieving a sustained virologic response (SVR) will continue to increase. However, no consensus has been achieved on exempting SVR-achieving patients from hepatocellular carcinoma (HCC) surveillance.
Methods: Between 2013 and 2021, 873 Korean patients who achieved SVR following DAA treatment were analyzed. We evaluated the predictive performance of seven noninvasive scores (PAGE-B, modified PAGE-B, Toronto HCC risk index, fibrosis-4, aspartate aminotransferase-to-platelet ratio index, albumin-bilirubin, and age male albumin-bilirubin platelet [aMAP]) at baseline and after SVR.
Results: The mean age of the 873 patients (39.3% males) was 59.1 years, and 224 patients (25.7%) had cirrhosis. During 3,542 person-years of follow-up, 44 patients developed HCC, with an annual incidence of 1.24/100 person-years. Male sex (adjusted hazard ratio [AHR], 2.21), cirrhosis (AHR, 7.93), and older age (AHR, 1.05) were associated with a significantly higher HCC risk in multivariate analysis. The performance of all scores at the time of SVR were numerically better than those at baseline as determined by the integrated area under the curve. Time-dependent area under the curves for predicting the 3-, 5-, and 7-year risk of HCC after SVR were higher in mPAGE-B (0.778, 0.746, and 0.812, respectively) and aMAP (0.776, 0.747, and 0.790, respectively) systems than others. No patients predicted as low-risk by the aMAP or mPAGE-B systems developed HCC.
Conclusions: aMAP and mPAGE-B scores demonstrated the highest predictive performance for de novo HCC in DAA-treated, SVR-achieving patients. Hence, these two systems may be used to identify low-risk patients that can be exempted from HCC surveillance.

Keywords: Hepacivirus, Sustained virologic response, Direct-acting antivirals, Risk stratification, Carcinoma, hepatocellular

Hepatitis C virus (HCV) infection is a major cause of chronic liver disease, resulting in liver cirrhosis and hepatocellular carcinoma (HCC).1 Highly effective and well-tolerated oral direct-acting antiviral (DAA) therapies for HCV infection have been available and widely used since the mid-2010s.2,3 DAA treatment often results in a sustained virologic response (SVR), which can be considered a cured HCV infection. Therefore, the number of patients who have been cured of HCV infection has been increasing rapidly and is predicted to continue increasing in the near future.4 However, despite achieving SVR, some patients may remain at risk of liver disease progression, and subsequently, develop HCC.5,6 International guidelines have different recommendations regarding ongoing HCC surveillance in patients who have achieved SVR. For example, the European Association for the Study of the Liver recommends HCC surveillance in patients with pretreatment stage 3 fibrosis and cirrhosis.7 The American Association for the Study of Liver Disease recommends HCC surveillance in patients with pretreatment cirrhosis, whereas the Asian Pacific Association for the Study of the Liver recommends universal HCC surveillance in patients with SVR, regardless of fibrosis stage or the presence of cirrhosis.8,9 The aim of HCC surveillance is in line with the broad goal of cancer surveillance, that is decreasing cancer-specific mortality at cost-effective terms. As the benefits of HCC surveillance have already been proved, the cost-effectiveness of HCC surveillance in patients with SVR has recently gained attention. Given that the cost-effectiveness of HCC surveillance is primarily determined by the incidence of HCC, accurate estimation of HCC incidence in a given population is crucial. Stratification of patients based on the incidence of HCC should guide whether a patient should be surveilled or not following SVR against HCV infection. Several studies, most using noninvasive methods, have attempted to stratify patients who are cured of HCV to identify optimal candidates for HCC surveillance.10,11 In the present study, we examined the performance of various noninvasive scoring systems to predict HCC development in Korean patients who achieved SVR. We aimed to identify which patients can be safely exempted from HCC surveillance based on these scoring systems; this could ensure that healthcare resources are directed toward patients with the highest risk of developing HCC.

1. Study design and study population

The study was designed as a retrospective one using electronic medical records from Asan Medical Center, Seoul, Republic of Korea. The source population consisted of patients with HCV infection at Asan Medical Center from January 2001 to June 2020 (Fig. 1). The inclusion criteria for this study were (1) diagnosis of HCV infection; (2) no previous diagnosis of HCC before DAA treatment; and (3) age over 18 years at the time of DAA treatment. We excluded (1) 2,983 patients who did not achieve SVR; (2) 102 patients coinfected with hepatitis B virus or human immunodeficiency virus; (3) eight patients <18 years old; (4) 30 patients diagnosed with HCC before achieving SVR; (5) 1,232 patients with SVR following interferon-based treatment; and (6) 74 patients who followed up for less than 6 months. This study was approved by the Institutional Review Board of Asan Medical Center (IRB number: 2020-1639), and the need for informed consent was waived due to the retrospective nature of the evaluations.

Figure 1.Flowchart for the study. SVR, sustained virologic response; HBV, hepatitis B virus; HIV, human immunodeficiency virus; HCC, hepatocellular carcinoma; DAA, direct-acting antivirals.

2. Clinical and laboratory variables

Demographic variables for the enrolled study population included age and sex. Cirrhosis was defined as the presence of any of the following findings: coarse liver echotexture and nodular liver surface by ultrasonography, clinical features of portal hypertension (e.g., ascites, splenomegaly, or varices), or thrombocytopenia (<150,000/mm3).

Laboratory data included platelet count, aspartate aminotransferase, alanine aminotransferase, total bilirubin, serum albumin, and prothrombin time. All patients were positive for anti-HCV by real-time polymerase chain reaction with a single strand linear probe (Abbott Real Time kit; Abbott, Chicago, IL, USA). Serum HCV RNA levels were measured in all patients pre- and post-DAA treatment (AMPLICOR HCV Test v2.0; Roche, Basel, Switzerland). The HCV genotype was determined using a restriction fragment mass polymorphism assay.

3. Outcomes

The primary outcome of interest in the study was the development of HCC, which was diagnosed histologically or using noninvasive diagnostic criteria based on corresponding international guidelines for HCC at the time of HCC diagnosis.7,8,12,13 The index date for the present analysis was the first date of confirmed SVR after DAA treatment. To prevent the inclusion of pre-clinical HCC at the time of SVR, patients who developed HCC within 6 months of achieving SVR were excluded. All patients were followed up until one of the following conditions was met: last hospital visit, a diagnosis of HCC, receipt of liver transplant, death, or the end of the study, which was March 31, 2022. During the follow-up period, patients were regularly surveilled for HCC via ultrasonography, and their serum alpha-fetoprotein levels were measured at least once every 6 months.

4. Statistical analysis

Data are expressed as counts and percentages for categorical variables and as the mean and standard deviation for continuous variables. The cumulative incidence of HCC was estimated using the Kaplan-Meier method and compared using the log-rank test according to the stratified risk groups. HCC development was predicted in each participant using various scoring systems. We calculated PAGE-B, modified PAGE-B (mPAGE-B), Toronto HCC risk index, aspartate aminotransferase-to-platelet ratio index (APRI), fibrosis-4 (FIB-4), albumin-bilirubin, and age male albumin-bilirubin platelet (aMAP) scores at the baseline and at the time of SVR.14-20 The predictive performances of each scoring system were assessed by Harrell’s concordance index,21 Heagerty’s integrated area under the curve (iAUC), and Heagerty’s AUC at 3, 5, and 7 years as time-dependent receiver operating characteristic analysis.22 Difference and 95% confidence intervals (CIs) of Heagerty’s iAUC and AUC among each scoring system were calculated using a bootstrapping method. All statistical analyses were performed using R software (http://www.r-project.org) with “survAUC,” and “timeROC” packages. All reported p-values are two-sided, and p-values <0.05 were considered statistically significant.

1. Baseline characteristics of the study population

Data of a total of 873 patients who achieved SVR following DAA treatment were analyzed in the present study. The mean patient age at the time of SVR was 59.1 years, and 39.3% of the study population was male (Table 1). Cirrhosis was evident in 25.7% of the patients, and HCV 1b (52.1%) and 2 (38.3%) were the most prevalent genotypes. Patients who were treated with interferon prior to DAA treatment comprised 13.9% of the study population. After obtaining SVR by DAA treatment, 15 patients (1.7%) had rescue DAA treatment for relapsed HCV infection.

Table 1. Demographic and Laboratory Characteristics of Patients Diagnosed with Chronic Hepatitis C at the Time of SVR Achieved by DAA Treatment

VariableOverall (n=873)No HCC (n=829)De novo HCC (n=44)p-value
Demographics
Age, yr59.1±11.958.7±11.965.1±10.0<0.001
Sex
Male343 (39.3)320 (38.6)23 (52.3)0.099
Female530 (60.7)509 (61.4)21 (47.7)
HCV genotype0.007
1a/others22 (2.5)21 (2.5)1 (2.3)
1b455 (52.1)427 (51.5)28 (63.6)
2334 (38.3)323 (39.0)11 (25.0)
36 (0.7)4 (0.5)2 (4.5)
43 (0.3)3 (0.4)0
68 (0.9)8 (1.0)0
Mixed3 (0.4)2 (0.2)1 (2.3)
Not available42 (4.8)41 (4.9)1 (2.3)
Liver cirrhosis224 (25.7)187 (22.6)37 (84.1)<0.001
Treatment experience
DAA752 (86.1)723 (87.2)29 (65.9)<0.001
DAA after interferon121 (13.9)106 (12.8)15 (34.1)
Laboratory parameter
Platelet, × 103/µL175.2±73.3178.6±72.7111.2±52.2<0.001
AST, U/L24 (20–31)23 (20–30)33 (28–49)<0.001
ALT, U/L17 (12–27)16 (12–26)25 (20–42)<0.001
Albumin, g/L3.8±0.43.8±0.43.5±0.4<0.001
Total bilirubin, mg/dL0.9±0.80.9±0.91.0±0.50.097
Prothrombin time, %88.4±15.489.3±15.377.7±12.0<0.001
Prothrombin time, INR1.1±0.11.1±0.11.2±0.1<0.001

Data are presented as mean±SD, number (%), or median (interquartile range).

SVR, sustained virologic response; DAA, direct-acting antivirals; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; AST, aspartate aminotransferase; ALT, alanine aminotransferase; INR, international normalized ratio.



2. HCC development

Of the 873 patients in the study population, 44 developed HCC, with an annual incidence rate of 1.24 per 100 person-years (PYs) during the median follow-up period of 3.7 years. The 2-, 3-, 5-, and 7-year cumulative HCC risks were 2.6%, 3.2%, 6.0%, and 8.3%, respectively.

Patients who developed HCC were generally older than patients who did not, and a higher proportion was male (52.3%). The development of HCC was also associated with cirrhosis, treatment-experience, and infection with HCV genotype 1b. Patients who did not develop HCC during the follow-up period had a higher platelet count, lower aminotransferase, higher albumin levels, and lower prothrombin time at the time of achieving SVR than did those who developed HCC.

The annual HCC incidence in patients with cirrhosis was significantly higher than that in patients without cirrhosis (3.33/100 PYs vs 0.29/100 PYs, p<0.001). Male patients tended to have a higher incidence of HCC compared with female patients (1.69/100 PYs vs 0.96/100 PYs), but this was not statistically significant (p=0.07). The risk of HCC development did not differ significantly between treatment-experienced (1.52/100 PYs) and treatment-naïve patients (1.13/100 PYs).

3. Predictors for HCC development

Male sex, liver cirrhosis, older age, lower platelet count and albumin, and increased aspartate aminotransferase or alanine aminotransferase were independently associated with an increased risk of HCC by univariate analysis. The multivariate Cox regression analysis indicated that male sex (adjusted hazard ratio, 2.21; 95% CI, 1.21 to 4.06; p=0.01), liver cirrhosis diagnosis (adjusted hazard ratio, 7.93; 95% CI, 3.39 to 18.60; p<0.001), and older age (adjusted hazard ratio, 1.05; 95% CI, 1.02 to 1.08; p<0.001) were independently and significantly associated with HCC development (Table 2).

Table 2. Predictive Factors for Hepatocellular Carcinoma Development

VariableUnivariate analysisMultivariable analysis
HR (95% CI)p-valueAHR (95% CI)p-value
Sex, male1.73 (0.96–3.13)0.072.21 (1.21–4.06)0.01
Liver cirrhosis11.9 (5.27–26.80)<0.0017.93 (3.39–18.60)<0.001
History of interferon–use1.26 (0.60–2.64)0.50
Age, per 1 yr increase*1.06 (1.03–1.09)<0.0011.05 (1.02–1.08)<0.001
Platelet*0.99 (0.89–0.99)<0.001
ALT*1.01 (1.00–1.01)<0.001
Albumin*0.26 (0.14–0.47)<0.0010.84 (0.38–1.86)0.70
Total bilirubin*1.12 (0.85–1.47)0.40
Prothrombin time*0.96 (0.94–0.97)<0.0010.98 (0.95–1.00)0.07

HR, hazard ratio; CI, confidence interval; AHR, adjusted HR; ALT, alanine aminotransferase.

*All variables were included the values at the time of sustained virologic response.



4. Prediction of de novo HCC development using scoring systems

All seven noninvasive scores at baseline were significantly higher in patients with de novo HCC than those in patients without HCC (Fig. 2A). In addition, all scores at the time of SVR were significantly higher in patients with de novo HCC than without HCC (Fig. 2B).

Figure 2.Distribution of the seven scores (A) at baseline and (B) after achievement of sustained virologic response. HCC, hepatocellular carcinoma; mPAGE, modified PAGE; THRI, Toronto HCC risk index; APRI, aspartate aminotransferase-to-platelet ratio index; FIB-4, fibrosis-4; ALBI, albumin-bilirubin; aMAP, age male albumin-bilirubin platelet.

Table 3 summarizes the cumulative incidence of HCC according to the risk groups determined by the most widely-used cutoffs for each score. Notably, no patients in the low-risk groups predicted by the mPAGE-B (score ≤8) or aMAP (score ≤50) systems developed HCC (Fig. 3). Patients in high-risk groups according to PAGE-B, mPAGE-B, Toronto HCC risk index, APRI, and aMAP scores showed a cumulative incidence of HCC of over 1.5/100 PYs. With the exception of the albumin-bilirubin grade, the noninvasive scores stratified the groups for the risk of developing HCC.

Figure 3.Kaplan-Meier survival estimates of patients with SVR after direct-acting antiviral treatment for the risk of de novo HCC according to the (A) modified PAGE-B score and (B) aMAP score. SVR, sustained virologic response; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; aMAP, albumin-bilirubin, and age male albumin-bilirubin platelet.

Table 3. Cumulative Incidence of De Novo HCC According to Various Risk Scoring Systems at the Time of Sustained Virologic Response

NSSCutoffPatients, nPerson-yearsHCC, nHCC incidencep-value
Total8733,542.0441.24
PAGE-B11High (≥18)208860.6212.44<0.001
Intermediate (10–17)4832,039.9221.08
Low (≤9)182641.610.16
mPAGE-B16High (≥13)4331,851.5392.11<0.001
Intermediate (9–12)3221,319.650.38
Low (≤8)118370.900.00
THRI12High (>240)52197.8105.06<0.001
Intermediate (120–240)7792,208.8321.45
Low (<120)421,135.520.18
APRI13≥1.5155739.3192.57<0.001
0.5–1.56062,395.1220.92
≤0.5112407.730.74
FIB-414>3.252191,065.2353.29<0.001
≤3.256542,476.990.36
>1.456612,823.0431.52<0.001
≤1.45212719.010.14
ALBI17Grade 3 (≥–1.39)7182,991.3411.370.12
Grade 2 (–2.60 to –1.39)155550.830.54
Grade 1 (≤–2.60)000NA
aMAP8High (≥60)4792,083.8401.92<0.001
Intermediate (50–60)2851,086.240.37
Low (≤50)109372.100.00

HCC, hepatocellular carcinoma; NSS, noninvasive scoring system; mPAGE-B, modified PAGE-B; THRI, Toronto HCC risk index; APRI, aspartate aminotransferase-to-platelet ratio index; FIB-4, fibrosis-4; ALBI, albumin-bilirubin; aMAP, age male albumin-bilirubin platelet; NA, not available.



The performances of all scoring systems at the time of SVR were better than those at baseline as determined by iAUC, despite not reaching statistical significance (Table 4). However, aMAP score at the time of SVR showed significantly higher AUC than its score at baseline in predicting 5- and 7-year risk of HCC.

Table 4. Time-Dependent AUC According to Various Risk Scoring Systems for Predicting the Development of HCC

ScoreHeagerty’s integrated AUCTime-dependent AUC at 3 yrTime-dependent AUC at 5 yrTime-dependent AUC at 7 yr
PAGE-B at baseline0.738 (0.661–0.814)0.713 (0.609–0.817)0.667 (0.578–0.757)0.760 (0.657–0.864)
PAGE-B at SVR0.749 (0.668–0.829)0.725 (0.628–0.821)0.690 (0.607–0.773)0.743 (0.642–0.844)
p-value0.6620.3830.2470.307
mPAGE-B at baseline0.752 (0.671–0.833)0.723 (0.620–0.826)0.698 (0.607–0.789)0.755 (0.658–0.852)
mPAGE-B at SVR0.795 (0.716–0.874)0.778 (0.685–0.870)0.746 (0.670–0.822)0.812 (0.730–0.893)
p-value0.9530.1220.1080.072
THRI at baseline0.760 (0.677–0.843)0.724 (0.614–0.835)0.721 (0.640–0.802)0.781 (0.688–0.873)
THRI at SVR0.778 (0.702–0.855)0.758 (0.668–0.848)0.729 (0.655–0.802)0.783 (0.693–0.872)
p-value0.7830.1760.4070.478
APRI at baseline0.694 (0.600–0.788)0.687 (0.575–0.799)0.682 (0.569–0.795)0.659 (0.536–0.781)
APRI at SVR0.688 (0.604–0.771)0.649 (0.544–0.755)0.659 (0.550–0.767)0.555 (0.421–0.689)
p-value0.4420.2820.3500.067
FIB-4 at baseline0.762 (0.700–0.824)0.750 (0.676–0.823)0.745 (0.657–0.833)0.717 (0.607–0.828)
FIB-4 at SVR0.778 (0.714–0.843)0.760 (0.680–0.839)0.736 (0.643–0.829)0.624 (0.478–0.770)
p-value0.7400.4120.4230.058
ALBI at baseline0.542 (0.439–0.646)0.513 (0.388–0.638)0.478 (0.383–0.574)0.382 (0.246–0.518)
ALBI at SVR0.632 (0.543–0.720)0.600 (0.487–0.713)0.601 (0.514–0.688)0.517 (0.377–0.656)
p-value0.9610.0300.0010.109
aMAP at baseline0.733 (0.657–0.809)0.716 (0.616–0.816)0.694 (0.612–0.777)0.722 (0.623–0.821)
aMAP at SVR0.781 (0.706–0.855)0.776 (0.682–0.869)0.747 (0.676–0.818)0.790 (0.700–0.880)
p-value0.9840.0660.0490.046

AUC, area under the curve; HCC, hepatocellular carcinoma; SVR, sustained virologic response; mPAGE, modified PAGE; THRI, Toronto HCC risk index; APRI, aspartate aminotransferase-to-platelet ratio index; FIB-4, fibrosis-4; ALBI, albumin-bilirubin; aMAP, age male albumin-bilirubin platelet.



Regarding the performance of the seven scoring systems at the time of SVR, mPAGE-B score showed the highest iAUC in predicting the risk of HCC (iAUC=0.795), followed by aMAP (iAUC=0.781), FIB-4 (iAUC=0.778), and Toronto HCC risk index (iAUC=0.778) (Table 4). A single scoring system that significantly predicted HCC risk with better performance metrics than all other systems at the time of SVR could not be identified. However, mPAGE-B, and aMAP tended to have good predictive performance than others (Supplementary Fig. 1).

In the present study, we evaluated 873 HCV-infected Korean patients who achieved SVR following DAA therapy and identified an annual HCC incidence of 1.24/100 PYs. We compared the predictive performance of noninvasive scoring systems that are used to stratify patients into risk groups for developing HCC. All noninvasive scores were significantly higher in patients with de novo HCC than in those without HCC. Patients classified as low-risk by aMAP and mPAGE-B scores did not develop HCC during study period. Among these noninvasive scoring systems, aMAP and mPAGE-B scores demonstrated better predictive performance for HCC development after achieving SVR.

Since the advent of the extremely successful DAA treatment for HCV, the number of HCV-infected patients achieving SVR has increased dramatically in Korea and around the world. Given that HCC is the most common liver-related event in patients who have achieved SVR, it is important that these patients undergo HCC surveillance. The fact that 44 patients in the study group (5.0%) developed HCC even after achieving SVR further highlights this need. However, some disagreements exist regarding the identification of candidates for HCC surveillance in HCV-infected patients who have achieved SVR. As the success of HCC surveillance is influenced by both efficacy and cost-generation of HCC surveillance tools, it is crucial to determine who pose the greatest risk of developing HCC and who may be safely exempted from HCC surveillance owing to very high negative predictive scores.

In the present study, HCC surveillance of patients with confirmed cirrhosis at baseline after achieving SVR was continued, based on international guidelines, and such patients exhibited a high incidence of HCC (3.33/100 PYs). By contrast, HCC surveillance may not be necessary for patients without advanced or significant fibrosis. However, as clinical diagnosis of cirrhosis or evaluation of fibrosis could be inaccurate, individualization and stratification of the HCC risk using noninvasive scoring systems could be more useful to determine participants for the HCC surveillance program. A recent study showed that HCC surveillance could be cost-effective when the incidence of HCC is more than 1.32/year.23 This suggests that some patients without cirrhosis are still candidates for HCC surveillance, based on the threshold of cost-effectiveness. Patients classified as high-risk by all noninvasive scores in the present study should continue HCC surveillance even after achieving SVR. However, the majority of intermediate- or low-risk groups may be exempted form HCC surveillance.

Many scoring systems have been developed and validated to predict the risk of developing HCC and the degree of fibrosis without the need for invasive procedures, such as liver biopsies. These noninvasive scores can be easily calculated using data obtained from routine blood tests, are readily available in daily practice, and are inexpensive. Although the present study was an observational study and not a clinical trial, all noninvasive scores could easily be calculated from the blood work results of the patients obtained during routine follow-up. Therefore, it is anticipated that these scores could be used more frequently with increasing HCC surveillance.

A recent large-scale observational study from Japan revealed that the aMAP score was better than APRI and FIB-4 at predicting HCC development.11 According to a study in Italy, albumin-bilirubin demonstrated better performance than APRI, FIB-4, and aMAP.24 Other studies have focused on the dynamic changes of these noninvasive scores before and after SVR to predict the risk of HCC.25,26 In the present study, the aMAP and mPAGE-B scores showed numerically better predictive performance for HCC risk. Notably, the aMAP score could clearly stratify low-, intermediate-, and high-risk groups, with an annual incidence of HCC of 0.0, 0.37, and 1.92/100 PYs, respectively. The mPAGE-B score was initially developed to predict HCC risk using parameters associated with chronic hepatitis B patients. However, mPAGE-B components, such as platelet count, age, sex, and serum albumin concentration, are known to be associated with HCC risk. Therefore, the application of the mPAGE-B score in the present study is supported, and this score may be applicable to predict HCC risk regardless of the underlying cause of liver disease. In the present study, the mPAGE-B score performance was similar to that of aMAP score for predicting HCC.

The current study has some limitations. First, only a small number of patients is included. Nevertheless, our cohort of 873 patients who achieved SVR following DAA treatment is the largest Korean study to-date. Second, based on previous studies, noninvasive imaging techniques, such as Fibroscan, may be a superior technique for stratifying HCC risk.27 However, results of these noninvasive imaging studies were not available for some patients in the cohort. Hence, we were unable to compare the noninvasive scores to imaging techniques in the present study. Third, our study’s median follow-up period of 3.7 years is relatively short compared to those of similar studies. Nevertheless, considering that DAA treatment has been available in Korea since the middle of 2010 and that HCC risk can be determined a few years later after DAA treatment, composing the study population as done by us is the best possible at this time. Lastly, we did not include established risk factors from previous studies, such as heavy drinking, family history of HCC, and diabetes.

In conclusion, aMAP and mPAGE-B scores demonstrated the highest predictive performance for HCC development in HCV-infected Korean patients who achieved SVR after DAA treatment. Low-risk patients, as determined by aMAP or mPAGE-B scores, may be safely exempted from HCC surveillance after achieving SVR. However, HCC surveillance should be continued in high-risk patients based on these two scores, regardless of SVR achievement. Using these noninvasive scores will aid in stratifying patients to identify who are eligible for continued HCC surveillance in routine clinical practice.

This study was supported by the National Research Foundation of Korea (NRF) grant, funded by the Korea government (Ministry of Science and ICT) (No. 2021R1G1A1009506).

Study concept and design: H.H., J.C. Data acquisition: W.M.C., D.L., J.H.S., K.M.K., Y.S.L., H.C.L. Data analysis and interpretation: H.H., J.C. Drafting of the manuscript: H.H., J.C. Critical revision of the manuscript for important intellectual content: J.C. Statistical analysis: H.H., J.C. Obtained funding: J.C. Administrative, technical, or material support; study supervision: J.C. Approval of final manuscript: all authors.

  1. Axley P, Ahmed Z, Ravi S, Singal AK. Hepatitis C virus and hepatocellular carcinoma: a narrative review. J Clin Transl Hepatol 2018;6:79-84.
    Pubmed KoreaMed CrossRef
  2. Park YJ, Woo HY, Heo J, et al. Real-life effectiveness and safety of glecaprevir/pibrentasvir for Korean patients with chronic hepatitis C at a single institution. Gut Liver 2021;15:440-450.
    Pubmed KoreaMed CrossRef
  3. Heo J, Kim YJ, Lee JW, et al. Efficacy and safety of glecaprevir/pibrentasvir in Korean patients with chronic hepatitis C: a pooled analysis of five phase II/III trials. Gut Liver 2021;15:895-903.
    Pubmed KoreaMed CrossRef
  4. Semmler G, Meyer EL, Kozbial K, et al. HCC risk stratification after cure of hepatitis C in patients with compensated advanced chronic liver disease. J Hepatol 2022;76:812-821.
    Pubmed CrossRef
  5. D'Ambrosio R, Degasperi E, Anolli MP, et al. Incidence of liver- and non-liver-related outcomes in patients with HCV-cirrhosis after SVR. J Hepatol 2022;76:302-310.
    Pubmed CrossRef
  6. Ahn YH, Lee H, Kim DY, et al. Independent risk factors for hepatocellular carcinoma recurrence after direct-acting antiviral therapy in patients with chronic hepatitis C. Gut Liver 2021;15:410-419.
    Pubmed KoreaMed CrossRef
  7. European Association for the Study of the Liver. EASL clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 2018;69:182-236.
    Pubmed CrossRef
  8. Marrero JA, Kulik LM, Sirlin CB, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases. Hepatology 2018;68:723-750.
    Pubmed CrossRef
  9. Kanda T, Lau GK, Wei L, et al. APASL HCV guidelines of virus-eradicated patients by DAA on how to monitor HCC occurrence and HBV reactivation. Hepatol Int 2019;13:649-661.
    Pubmed KoreaMed CrossRef
  10. Luna-Cuadros MA, Chen HW, Hanif H, Ali MJ, Khan MM, Lau DT. Risk of hepatocellular carcinoma after hepatitis C virus cure. World J Gastroenterol 2022;28:96-107.
    Pubmed KoreaMed CrossRef
  11. Yamashita Y, Joshita S, Sugiura A, et al. aMAP score prediction of hepatocellular carcinoma occurrence and incidence-free rate after a sustained virologic response in chronic hepatitis C. Hepatol Res 2021;51:933-942.
    Pubmed CrossRef
  12. Omata M, Cheng AL, Kokudo N, et al. Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma: a 2017 update. Hepatol Int 2017;11:317-370.
    Pubmed KoreaMed CrossRef
  13. Korean Liver Cancer AssociationNational Cancer Center. 2018 Korean Liver Cancer Association-National Cancer Center Korea practice guidelines for the management of hepatocellular carcinoma. Gut Liver 2019;13:227-299.
    Pubmed KoreaMed CrossRef
  14. Papatheodoridis G, Dalekos G, Sypsa V, et al. PAGE-B predicts the risk of developing hepatocellular carcinoma in Caucasians with chronic hepatitis B on 5-year antiviral therapy. J Hepatol 2016;64:800-806.
    Pubmed CrossRef
  15. Sharma SA, Kowgier M, Hansen BE, et al. Toronto HCC risk index: a validated scoring system to predict 10-year risk of HCC in patients with cirrhosis. J Hepatol 2018;68:92-99.
    Pubmed CrossRef
  16. Lin ZH, Xin YN, Dong QJ, et al. Performance of the aspartate aminotransferase-to-platelet ratio index for the staging of hepatitis C-related fibrosis: an updated meta-analysis. Hepatology 2011;53:726-736.
    Pubmed CrossRef
  17. Sterling RK, Lissen E, Clumeck N, et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology 2006;43:1317-1325.
    Pubmed CrossRef
  18. Fan R, Papatheodoridis G, Sun J, et al. aMAP risk score predicts hepatocellular carcinoma development in patients with chronic hepatitis. J Hepatol 2020;73:1368-1378.
    Pubmed CrossRef
  19. Kim JH, Kim YD, Lee M, et al. Modified PAGE-B score predicts the risk of hepatocellular carcinoma in Asians with chronic hepatitis B on antiviral therapy. J Hepatol 2018;69:1066-1073.
    Pubmed CrossRef
  20. Johnson PJ, Berhane S, Kagebayashi C, et al. Assessment of liver function in patients with hepatocellular carcinoma: a new evidence-based approach-the ALBI grade. J Clin Oncol 2015;33:550-558.
    Pubmed KoreaMed CrossRef
  21. Harrell FE, Lee KL, Matchar DB, Reichert TA. Regression models for prognostic prediction: advantages, problems, and suggested solutions. Cancer Treat Rep 1985;69:1071-1077.
    Pubmed
  22. Heagerty PJ, Zheng Y. Survival model predictive accuracy and ROC curves. Biometrics 2005;61:92-105.
    Pubmed CrossRef
  23. Ioannou GN. HCC surveillance after SVR in patients with F3/F4 fibrosis. J Hepatol 2021;74:458-465.
    Pubmed CrossRef
  24. Caviglia GP, Troshina G, Santaniello U, et al. Long-term hepatocellular carcinoma development and predictive ability of non-invasive scoring systems in patients with HCV-related cirrhosis treated with direct-acting antivirals. Cancers (Basel) 2022;14:828.
    Pubmed KoreaMed CrossRef
  25. Tamaki N, Kurosaki M, Yasui Y, et al. Change in fibrosis 4 index as predictor of high risk of incident hepatocellular carcinoma after eradication of hepatitis C virus. Clin Infect Dis 2021;73:e3349-e3354.
    Pubmed KoreaMed CrossRef
  26. Alonso López S, Manzano ML, Gea F, et al. A model based on noninvasive markers predicts very low hepatocellular carcinoma risk after viral response in hepatitis C virus-advanced fibrosis. Hepatology 2020;72:1924-1934.
    Pubmed CrossRef
  27. Lee HW, Chon YE, Kim SU, et al. Predicting liver-related events using transient elastography in chronic hepatitis C patients with sustained virological response. Gut Liver 2016;10:429-436.
    Pubmed KoreaMed CrossRef

Article

Original Article

Gut and Liver 2024; 18(1): 147-155

Published online January 15, 2024 https://doi.org/10.5009/gnl220386

Copyright © Gut and Liver.

Prediction of Hepatocellular Carcinoma Development in Korean Patients after Hepatitis C Cure with Direct-Acting Antivirals

Hyeyeon Hong , Won-Mook Choi , Danbi Lee , Ju Hyun Shim , Kang Mo Kim , Young-Suk Lim , Han Chu Lee , Jonggi Choi

Department of Gastroenterology, Liver Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

Correspondence to:Jonggi Choi
ORCID https://orcid.org/0000-0002-7470-5850
E-mail j.choi@amc.seoul.kr

Received: September 3, 2022; Revised: December 30, 2022; Accepted: January 17, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background/Aims: With the wide application of direct-acting antivirals (DAAs) for hepatitis C virus infection, the number of patients achieving a sustained virologic response (SVR) will continue to increase. However, no consensus has been achieved on exempting SVR-achieving patients from hepatocellular carcinoma (HCC) surveillance.
Methods: Between 2013 and 2021, 873 Korean patients who achieved SVR following DAA treatment were analyzed. We evaluated the predictive performance of seven noninvasive scores (PAGE-B, modified PAGE-B, Toronto HCC risk index, fibrosis-4, aspartate aminotransferase-to-platelet ratio index, albumin-bilirubin, and age male albumin-bilirubin platelet [aMAP]) at baseline and after SVR.
Results: The mean age of the 873 patients (39.3% males) was 59.1 years, and 224 patients (25.7%) had cirrhosis. During 3,542 person-years of follow-up, 44 patients developed HCC, with an annual incidence of 1.24/100 person-years. Male sex (adjusted hazard ratio [AHR], 2.21), cirrhosis (AHR, 7.93), and older age (AHR, 1.05) were associated with a significantly higher HCC risk in multivariate analysis. The performance of all scores at the time of SVR were numerically better than those at baseline as determined by the integrated area under the curve. Time-dependent area under the curves for predicting the 3-, 5-, and 7-year risk of HCC after SVR were higher in mPAGE-B (0.778, 0.746, and 0.812, respectively) and aMAP (0.776, 0.747, and 0.790, respectively) systems than others. No patients predicted as low-risk by the aMAP or mPAGE-B systems developed HCC.
Conclusions: aMAP and mPAGE-B scores demonstrated the highest predictive performance for de novo HCC in DAA-treated, SVR-achieving patients. Hence, these two systems may be used to identify low-risk patients that can be exempted from HCC surveillance.

Keywords: Hepacivirus, Sustained virologic response, Direct-acting antivirals, Risk stratification, Carcinoma, hepatocellular

INTRODUCTION

Hepatitis C virus (HCV) infection is a major cause of chronic liver disease, resulting in liver cirrhosis and hepatocellular carcinoma (HCC).1 Highly effective and well-tolerated oral direct-acting antiviral (DAA) therapies for HCV infection have been available and widely used since the mid-2010s.2,3 DAA treatment often results in a sustained virologic response (SVR), which can be considered a cured HCV infection. Therefore, the number of patients who have been cured of HCV infection has been increasing rapidly and is predicted to continue increasing in the near future.4 However, despite achieving SVR, some patients may remain at risk of liver disease progression, and subsequently, develop HCC.5,6 International guidelines have different recommendations regarding ongoing HCC surveillance in patients who have achieved SVR. For example, the European Association for the Study of the Liver recommends HCC surveillance in patients with pretreatment stage 3 fibrosis and cirrhosis.7 The American Association for the Study of Liver Disease recommends HCC surveillance in patients with pretreatment cirrhosis, whereas the Asian Pacific Association for the Study of the Liver recommends universal HCC surveillance in patients with SVR, regardless of fibrosis stage or the presence of cirrhosis.8,9 The aim of HCC surveillance is in line with the broad goal of cancer surveillance, that is decreasing cancer-specific mortality at cost-effective terms. As the benefits of HCC surveillance have already been proved, the cost-effectiveness of HCC surveillance in patients with SVR has recently gained attention. Given that the cost-effectiveness of HCC surveillance is primarily determined by the incidence of HCC, accurate estimation of HCC incidence in a given population is crucial. Stratification of patients based on the incidence of HCC should guide whether a patient should be surveilled or not following SVR against HCV infection. Several studies, most using noninvasive methods, have attempted to stratify patients who are cured of HCV to identify optimal candidates for HCC surveillance.10,11 In the present study, we examined the performance of various noninvasive scoring systems to predict HCC development in Korean patients who achieved SVR. We aimed to identify which patients can be safely exempted from HCC surveillance based on these scoring systems; this could ensure that healthcare resources are directed toward patients with the highest risk of developing HCC.

MATERIALS AND METHODS

1. Study design and study population

The study was designed as a retrospective one using electronic medical records from Asan Medical Center, Seoul, Republic of Korea. The source population consisted of patients with HCV infection at Asan Medical Center from January 2001 to June 2020 (Fig. 1). The inclusion criteria for this study were (1) diagnosis of HCV infection; (2) no previous diagnosis of HCC before DAA treatment; and (3) age over 18 years at the time of DAA treatment. We excluded (1) 2,983 patients who did not achieve SVR; (2) 102 patients coinfected with hepatitis B virus or human immunodeficiency virus; (3) eight patients <18 years old; (4) 30 patients diagnosed with HCC before achieving SVR; (5) 1,232 patients with SVR following interferon-based treatment; and (6) 74 patients who followed up for less than 6 months. This study was approved by the Institutional Review Board of Asan Medical Center (IRB number: 2020-1639), and the need for informed consent was waived due to the retrospective nature of the evaluations.

Figure 1. Flowchart for the study. SVR, sustained virologic response; HBV, hepatitis B virus; HIV, human immunodeficiency virus; HCC, hepatocellular carcinoma; DAA, direct-acting antivirals.

2. Clinical and laboratory variables

Demographic variables for the enrolled study population included age and sex. Cirrhosis was defined as the presence of any of the following findings: coarse liver echotexture and nodular liver surface by ultrasonography, clinical features of portal hypertension (e.g., ascites, splenomegaly, or varices), or thrombocytopenia (<150,000/mm3).

Laboratory data included platelet count, aspartate aminotransferase, alanine aminotransferase, total bilirubin, serum albumin, and prothrombin time. All patients were positive for anti-HCV by real-time polymerase chain reaction with a single strand linear probe (Abbott Real Time kit; Abbott, Chicago, IL, USA). Serum HCV RNA levels were measured in all patients pre- and post-DAA treatment (AMPLICOR HCV Test v2.0; Roche, Basel, Switzerland). The HCV genotype was determined using a restriction fragment mass polymorphism assay.

3. Outcomes

The primary outcome of interest in the study was the development of HCC, which was diagnosed histologically or using noninvasive diagnostic criteria based on corresponding international guidelines for HCC at the time of HCC diagnosis.7,8,12,13 The index date for the present analysis was the first date of confirmed SVR after DAA treatment. To prevent the inclusion of pre-clinical HCC at the time of SVR, patients who developed HCC within 6 months of achieving SVR were excluded. All patients were followed up until one of the following conditions was met: last hospital visit, a diagnosis of HCC, receipt of liver transplant, death, or the end of the study, which was March 31, 2022. During the follow-up period, patients were regularly surveilled for HCC via ultrasonography, and their serum alpha-fetoprotein levels were measured at least once every 6 months.

4. Statistical analysis

Data are expressed as counts and percentages for categorical variables and as the mean and standard deviation for continuous variables. The cumulative incidence of HCC was estimated using the Kaplan-Meier method and compared using the log-rank test according to the stratified risk groups. HCC development was predicted in each participant using various scoring systems. We calculated PAGE-B, modified PAGE-B (mPAGE-B), Toronto HCC risk index, aspartate aminotransferase-to-platelet ratio index (APRI), fibrosis-4 (FIB-4), albumin-bilirubin, and age male albumin-bilirubin platelet (aMAP) scores at the baseline and at the time of SVR.14-20 The predictive performances of each scoring system were assessed by Harrell’s concordance index,21 Heagerty’s integrated area under the curve (iAUC), and Heagerty’s AUC at 3, 5, and 7 years as time-dependent receiver operating characteristic analysis.22 Difference and 95% confidence intervals (CIs) of Heagerty’s iAUC and AUC among each scoring system were calculated using a bootstrapping method. All statistical analyses were performed using R software (http://www.r-project.org) with “survAUC,” and “timeROC” packages. All reported p-values are two-sided, and p-values <0.05 were considered statistically significant.

RESULTS

1. Baseline characteristics of the study population

Data of a total of 873 patients who achieved SVR following DAA treatment were analyzed in the present study. The mean patient age at the time of SVR was 59.1 years, and 39.3% of the study population was male (Table 1). Cirrhosis was evident in 25.7% of the patients, and HCV 1b (52.1%) and 2 (38.3%) were the most prevalent genotypes. Patients who were treated with interferon prior to DAA treatment comprised 13.9% of the study population. After obtaining SVR by DAA treatment, 15 patients (1.7%) had rescue DAA treatment for relapsed HCV infection.

Table 1 . Demographic and Laboratory Characteristics of Patients Diagnosed with Chronic Hepatitis C at the Time of SVR Achieved by DAA Treatment.

VariableOverall (n=873)No HCC (n=829)De novo HCC (n=44)p-value
Demographics
Age, yr59.1±11.958.7±11.965.1±10.0<0.001
Sex
Male343 (39.3)320 (38.6)23 (52.3)0.099
Female530 (60.7)509 (61.4)21 (47.7)
HCV genotype0.007
1a/others22 (2.5)21 (2.5)1 (2.3)
1b455 (52.1)427 (51.5)28 (63.6)
2334 (38.3)323 (39.0)11 (25.0)
36 (0.7)4 (0.5)2 (4.5)
43 (0.3)3 (0.4)0
68 (0.9)8 (1.0)0
Mixed3 (0.4)2 (0.2)1 (2.3)
Not available42 (4.8)41 (4.9)1 (2.3)
Liver cirrhosis224 (25.7)187 (22.6)37 (84.1)<0.001
Treatment experience
DAA752 (86.1)723 (87.2)29 (65.9)<0.001
DAA after interferon121 (13.9)106 (12.8)15 (34.1)
Laboratory parameter
Platelet, × 103/µL175.2±73.3178.6±72.7111.2±52.2<0.001
AST, U/L24 (20–31)23 (20–30)33 (28–49)<0.001
ALT, U/L17 (12–27)16 (12–26)25 (20–42)<0.001
Albumin, g/L3.8±0.43.8±0.43.5±0.4<0.001
Total bilirubin, mg/dL0.9±0.80.9±0.91.0±0.50.097
Prothrombin time, %88.4±15.489.3±15.377.7±12.0<0.001
Prothrombin time, INR1.1±0.11.1±0.11.2±0.1<0.001

Data are presented as mean±SD, number (%), or median (interquartile range)..

SVR, sustained virologic response; DAA, direct-acting antivirals; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; AST, aspartate aminotransferase; ALT, alanine aminotransferase; INR, international normalized ratio..



2. HCC development

Of the 873 patients in the study population, 44 developed HCC, with an annual incidence rate of 1.24 per 100 person-years (PYs) during the median follow-up period of 3.7 years. The 2-, 3-, 5-, and 7-year cumulative HCC risks were 2.6%, 3.2%, 6.0%, and 8.3%, respectively.

Patients who developed HCC were generally older than patients who did not, and a higher proportion was male (52.3%). The development of HCC was also associated with cirrhosis, treatment-experience, and infection with HCV genotype 1b. Patients who did not develop HCC during the follow-up period had a higher platelet count, lower aminotransferase, higher albumin levels, and lower prothrombin time at the time of achieving SVR than did those who developed HCC.

The annual HCC incidence in patients with cirrhosis was significantly higher than that in patients without cirrhosis (3.33/100 PYs vs 0.29/100 PYs, p<0.001). Male patients tended to have a higher incidence of HCC compared with female patients (1.69/100 PYs vs 0.96/100 PYs), but this was not statistically significant (p=0.07). The risk of HCC development did not differ significantly between treatment-experienced (1.52/100 PYs) and treatment-naïve patients (1.13/100 PYs).

3. Predictors for HCC development

Male sex, liver cirrhosis, older age, lower platelet count and albumin, and increased aspartate aminotransferase or alanine aminotransferase were independently associated with an increased risk of HCC by univariate analysis. The multivariate Cox regression analysis indicated that male sex (adjusted hazard ratio, 2.21; 95% CI, 1.21 to 4.06; p=0.01), liver cirrhosis diagnosis (adjusted hazard ratio, 7.93; 95% CI, 3.39 to 18.60; p<0.001), and older age (adjusted hazard ratio, 1.05; 95% CI, 1.02 to 1.08; p<0.001) were independently and significantly associated with HCC development (Table 2).

Table 2 . Predictive Factors for Hepatocellular Carcinoma Development.

VariableUnivariate analysisMultivariable analysis
HR (95% CI)p-valueAHR (95% CI)p-value
Sex, male1.73 (0.96–3.13)0.072.21 (1.21–4.06)0.01
Liver cirrhosis11.9 (5.27–26.80)<0.0017.93 (3.39–18.60)<0.001
History of interferon–use1.26 (0.60–2.64)0.50
Age, per 1 yr increase*1.06 (1.03–1.09)<0.0011.05 (1.02–1.08)<0.001
Platelet*0.99 (0.89–0.99)<0.001
ALT*1.01 (1.00–1.01)<0.001
Albumin*0.26 (0.14–0.47)<0.0010.84 (0.38–1.86)0.70
Total bilirubin*1.12 (0.85–1.47)0.40
Prothrombin time*0.96 (0.94–0.97)<0.0010.98 (0.95–1.00)0.07

HR, hazard ratio; CI, confidence interval; AHR, adjusted HR; ALT, alanine aminotransferase..

*All variables were included the values at the time of sustained virologic response..



4. Prediction of de novo HCC development using scoring systems

All seven noninvasive scores at baseline were significantly higher in patients with de novo HCC than those in patients without HCC (Fig. 2A). In addition, all scores at the time of SVR were significantly higher in patients with de novo HCC than without HCC (Fig. 2B).

Figure 2. Distribution of the seven scores (A) at baseline and (B) after achievement of sustained virologic response. HCC, hepatocellular carcinoma; mPAGE, modified PAGE; THRI, Toronto HCC risk index; APRI, aspartate aminotransferase-to-platelet ratio index; FIB-4, fibrosis-4; ALBI, albumin-bilirubin; aMAP, age male albumin-bilirubin platelet.

Table 3 summarizes the cumulative incidence of HCC according to the risk groups determined by the most widely-used cutoffs for each score. Notably, no patients in the low-risk groups predicted by the mPAGE-B (score ≤8) or aMAP (score ≤50) systems developed HCC (Fig. 3). Patients in high-risk groups according to PAGE-B, mPAGE-B, Toronto HCC risk index, APRI, and aMAP scores showed a cumulative incidence of HCC of over 1.5/100 PYs. With the exception of the albumin-bilirubin grade, the noninvasive scores stratified the groups for the risk of developing HCC.

Figure 3. Kaplan-Meier survival estimates of patients with SVR after direct-acting antiviral treatment for the risk of de novo HCC according to the (A) modified PAGE-B score and (B) aMAP score. SVR, sustained virologic response; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; aMAP, albumin-bilirubin, and age male albumin-bilirubin platelet.

Table 3 . Cumulative Incidence of De Novo HCC According to Various Risk Scoring Systems at the Time of Sustained Virologic Response.

NSSCutoffPatients, nPerson-yearsHCC, nHCC incidencep-value
Total8733,542.0441.24
PAGE-B11High (≥18)208860.6212.44<0.001
Intermediate (10–17)4832,039.9221.08
Low (≤9)182641.610.16
mPAGE-B16High (≥13)4331,851.5392.11<0.001
Intermediate (9–12)3221,319.650.38
Low (≤8)118370.900.00
THRI12High (>240)52197.8105.06<0.001
Intermediate (120–240)7792,208.8321.45
Low (<120)421,135.520.18
APRI13≥1.5155739.3192.57<0.001
0.5–1.56062,395.1220.92
≤0.5112407.730.74
FIB-414>3.252191,065.2353.29<0.001
≤3.256542,476.990.36
>1.456612,823.0431.52<0.001
≤1.45212719.010.14
ALBI17Grade 3 (≥–1.39)7182,991.3411.370.12
Grade 2 (–2.60 to –1.39)155550.830.54
Grade 1 (≤–2.60)000NA
aMAP8High (≥60)4792,083.8401.92<0.001
Intermediate (50–60)2851,086.240.37
Low (≤50)109372.100.00

HCC, hepatocellular carcinoma; NSS, noninvasive scoring system; mPAGE-B, modified PAGE-B; THRI, Toronto HCC risk index; APRI, aspartate aminotransferase-to-platelet ratio index; FIB-4, fibrosis-4; ALBI, albumin-bilirubin; aMAP, age male albumin-bilirubin platelet; NA, not available..



The performances of all scoring systems at the time of SVR were better than those at baseline as determined by iAUC, despite not reaching statistical significance (Table 4). However, aMAP score at the time of SVR showed significantly higher AUC than its score at baseline in predicting 5- and 7-year risk of HCC.

Table 4 . Time-Dependent AUC According to Various Risk Scoring Systems for Predicting the Development of HCC.

ScoreHeagerty’s integrated AUCTime-dependent AUC at 3 yrTime-dependent AUC at 5 yrTime-dependent AUC at 7 yr
PAGE-B at baseline0.738 (0.661–0.814)0.713 (0.609–0.817)0.667 (0.578–0.757)0.760 (0.657–0.864)
PAGE-B at SVR0.749 (0.668–0.829)0.725 (0.628–0.821)0.690 (0.607–0.773)0.743 (0.642–0.844)
p-value0.6620.3830.2470.307
mPAGE-B at baseline0.752 (0.671–0.833)0.723 (0.620–0.826)0.698 (0.607–0.789)0.755 (0.658–0.852)
mPAGE-B at SVR0.795 (0.716–0.874)0.778 (0.685–0.870)0.746 (0.670–0.822)0.812 (0.730–0.893)
p-value0.9530.1220.1080.072
THRI at baseline0.760 (0.677–0.843)0.724 (0.614–0.835)0.721 (0.640–0.802)0.781 (0.688–0.873)
THRI at SVR0.778 (0.702–0.855)0.758 (0.668–0.848)0.729 (0.655–0.802)0.783 (0.693–0.872)
p-value0.7830.1760.4070.478
APRI at baseline0.694 (0.600–0.788)0.687 (0.575–0.799)0.682 (0.569–0.795)0.659 (0.536–0.781)
APRI at SVR0.688 (0.604–0.771)0.649 (0.544–0.755)0.659 (0.550–0.767)0.555 (0.421–0.689)
p-value0.4420.2820.3500.067
FIB-4 at baseline0.762 (0.700–0.824)0.750 (0.676–0.823)0.745 (0.657–0.833)0.717 (0.607–0.828)
FIB-4 at SVR0.778 (0.714–0.843)0.760 (0.680–0.839)0.736 (0.643–0.829)0.624 (0.478–0.770)
p-value0.7400.4120.4230.058
ALBI at baseline0.542 (0.439–0.646)0.513 (0.388–0.638)0.478 (0.383–0.574)0.382 (0.246–0.518)
ALBI at SVR0.632 (0.543–0.720)0.600 (0.487–0.713)0.601 (0.514–0.688)0.517 (0.377–0.656)
p-value0.9610.0300.0010.109
aMAP at baseline0.733 (0.657–0.809)0.716 (0.616–0.816)0.694 (0.612–0.777)0.722 (0.623–0.821)
aMAP at SVR0.781 (0.706–0.855)0.776 (0.682–0.869)0.747 (0.676–0.818)0.790 (0.700–0.880)
p-value0.9840.0660.0490.046

AUC, area under the curve; HCC, hepatocellular carcinoma; SVR, sustained virologic response; mPAGE, modified PAGE; THRI, Toronto HCC risk index; APRI, aspartate aminotransferase-to-platelet ratio index; FIB-4, fibrosis-4; ALBI, albumin-bilirubin; aMAP, age male albumin-bilirubin platelet..



Regarding the performance of the seven scoring systems at the time of SVR, mPAGE-B score showed the highest iAUC in predicting the risk of HCC (iAUC=0.795), followed by aMAP (iAUC=0.781), FIB-4 (iAUC=0.778), and Toronto HCC risk index (iAUC=0.778) (Table 4). A single scoring system that significantly predicted HCC risk with better performance metrics than all other systems at the time of SVR could not be identified. However, mPAGE-B, and aMAP tended to have good predictive performance than others (Supplementary Fig. 1).

DISCUSSION

In the present study, we evaluated 873 HCV-infected Korean patients who achieved SVR following DAA therapy and identified an annual HCC incidence of 1.24/100 PYs. We compared the predictive performance of noninvasive scoring systems that are used to stratify patients into risk groups for developing HCC. All noninvasive scores were significantly higher in patients with de novo HCC than in those without HCC. Patients classified as low-risk by aMAP and mPAGE-B scores did not develop HCC during study period. Among these noninvasive scoring systems, aMAP and mPAGE-B scores demonstrated better predictive performance for HCC development after achieving SVR.

Since the advent of the extremely successful DAA treatment for HCV, the number of HCV-infected patients achieving SVR has increased dramatically in Korea and around the world. Given that HCC is the most common liver-related event in patients who have achieved SVR, it is important that these patients undergo HCC surveillance. The fact that 44 patients in the study group (5.0%) developed HCC even after achieving SVR further highlights this need. However, some disagreements exist regarding the identification of candidates for HCC surveillance in HCV-infected patients who have achieved SVR. As the success of HCC surveillance is influenced by both efficacy and cost-generation of HCC surveillance tools, it is crucial to determine who pose the greatest risk of developing HCC and who may be safely exempted from HCC surveillance owing to very high negative predictive scores.

In the present study, HCC surveillance of patients with confirmed cirrhosis at baseline after achieving SVR was continued, based on international guidelines, and such patients exhibited a high incidence of HCC (3.33/100 PYs). By contrast, HCC surveillance may not be necessary for patients without advanced or significant fibrosis. However, as clinical diagnosis of cirrhosis or evaluation of fibrosis could be inaccurate, individualization and stratification of the HCC risk using noninvasive scoring systems could be more useful to determine participants for the HCC surveillance program. A recent study showed that HCC surveillance could be cost-effective when the incidence of HCC is more than 1.32/year.23 This suggests that some patients without cirrhosis are still candidates for HCC surveillance, based on the threshold of cost-effectiveness. Patients classified as high-risk by all noninvasive scores in the present study should continue HCC surveillance even after achieving SVR. However, the majority of intermediate- or low-risk groups may be exempted form HCC surveillance.

Many scoring systems have been developed and validated to predict the risk of developing HCC and the degree of fibrosis without the need for invasive procedures, such as liver biopsies. These noninvasive scores can be easily calculated using data obtained from routine blood tests, are readily available in daily practice, and are inexpensive. Although the present study was an observational study and not a clinical trial, all noninvasive scores could easily be calculated from the blood work results of the patients obtained during routine follow-up. Therefore, it is anticipated that these scores could be used more frequently with increasing HCC surveillance.

A recent large-scale observational study from Japan revealed that the aMAP score was better than APRI and FIB-4 at predicting HCC development.11 According to a study in Italy, albumin-bilirubin demonstrated better performance than APRI, FIB-4, and aMAP.24 Other studies have focused on the dynamic changes of these noninvasive scores before and after SVR to predict the risk of HCC.25,26 In the present study, the aMAP and mPAGE-B scores showed numerically better predictive performance for HCC risk. Notably, the aMAP score could clearly stratify low-, intermediate-, and high-risk groups, with an annual incidence of HCC of 0.0, 0.37, and 1.92/100 PYs, respectively. The mPAGE-B score was initially developed to predict HCC risk using parameters associated with chronic hepatitis B patients. However, mPAGE-B components, such as platelet count, age, sex, and serum albumin concentration, are known to be associated with HCC risk. Therefore, the application of the mPAGE-B score in the present study is supported, and this score may be applicable to predict HCC risk regardless of the underlying cause of liver disease. In the present study, the mPAGE-B score performance was similar to that of aMAP score for predicting HCC.

The current study has some limitations. First, only a small number of patients is included. Nevertheless, our cohort of 873 patients who achieved SVR following DAA treatment is the largest Korean study to-date. Second, based on previous studies, noninvasive imaging techniques, such as Fibroscan, may be a superior technique for stratifying HCC risk.27 However, results of these noninvasive imaging studies were not available for some patients in the cohort. Hence, we were unable to compare the noninvasive scores to imaging techniques in the present study. Third, our study’s median follow-up period of 3.7 years is relatively short compared to those of similar studies. Nevertheless, considering that DAA treatment has been available in Korea since the middle of 2010 and that HCC risk can be determined a few years later after DAA treatment, composing the study population as done by us is the best possible at this time. Lastly, we did not include established risk factors from previous studies, such as heavy drinking, family history of HCC, and diabetes.

In conclusion, aMAP and mPAGE-B scores demonstrated the highest predictive performance for HCC development in HCV-infected Korean patients who achieved SVR after DAA treatment. Low-risk patients, as determined by aMAP or mPAGE-B scores, may be safely exempted from HCC surveillance after achieving SVR. However, HCC surveillance should be continued in high-risk patients based on these two scores, regardless of SVR achievement. Using these noninvasive scores will aid in stratifying patients to identify who are eligible for continued HCC surveillance in routine clinical practice.

SUPPLEMENTARY MATERIALS

Supplementary materials can be accessed at https://doi.org/10.5009/gnl220386

ACKNOWLEDGEMENTS

This study was supported by the National Research Foundation of Korea (NRF) grant, funded by the Korea government (Ministry of Science and ICT) (No. 2021R1G1A1009506).

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

AUTHOR CONTRIBUTIONS

Study concept and design: H.H., J.C. Data acquisition: W.M.C., D.L., J.H.S., K.M.K., Y.S.L., H.C.L. Data analysis and interpretation: H.H., J.C. Drafting of the manuscript: H.H., J.C. Critical revision of the manuscript for important intellectual content: J.C. Statistical analysis: H.H., J.C. Obtained funding: J.C. Administrative, technical, or material support; study supervision: J.C. Approval of final manuscript: all authors.

Fig 1.

Figure 1.Flowchart for the study. SVR, sustained virologic response; HBV, hepatitis B virus; HIV, human immunodeficiency virus; HCC, hepatocellular carcinoma; DAA, direct-acting antivirals.
Gut and Liver 2024; 18: 147-155https://doi.org/10.5009/gnl220386

Fig 2.

Figure 2.Distribution of the seven scores (A) at baseline and (B) after achievement of sustained virologic response. HCC, hepatocellular carcinoma; mPAGE, modified PAGE; THRI, Toronto HCC risk index; APRI, aspartate aminotransferase-to-platelet ratio index; FIB-4, fibrosis-4; ALBI, albumin-bilirubin; aMAP, age male albumin-bilirubin platelet.
Gut and Liver 2024; 18: 147-155https://doi.org/10.5009/gnl220386

Fig 3.

Figure 3.Kaplan-Meier survival estimates of patients with SVR after direct-acting antiviral treatment for the risk of de novo HCC according to the (A) modified PAGE-B score and (B) aMAP score. SVR, sustained virologic response; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; aMAP, albumin-bilirubin, and age male albumin-bilirubin platelet.
Gut and Liver 2024; 18: 147-155https://doi.org/10.5009/gnl220386

Table 1 Demographic and Laboratory Characteristics of Patients Diagnosed with Chronic Hepatitis C at the Time of SVR Achieved by DAA Treatment

VariableOverall (n=873)No HCC (n=829)De novo HCC (n=44)p-value
Demographics
Age, yr59.1±11.958.7±11.965.1±10.0<0.001
Sex
Male343 (39.3)320 (38.6)23 (52.3)0.099
Female530 (60.7)509 (61.4)21 (47.7)
HCV genotype0.007
1a/others22 (2.5)21 (2.5)1 (2.3)
1b455 (52.1)427 (51.5)28 (63.6)
2334 (38.3)323 (39.0)11 (25.0)
36 (0.7)4 (0.5)2 (4.5)
43 (0.3)3 (0.4)0
68 (0.9)8 (1.0)0
Mixed3 (0.4)2 (0.2)1 (2.3)
Not available42 (4.8)41 (4.9)1 (2.3)
Liver cirrhosis224 (25.7)187 (22.6)37 (84.1)<0.001
Treatment experience
DAA752 (86.1)723 (87.2)29 (65.9)<0.001
DAA after interferon121 (13.9)106 (12.8)15 (34.1)
Laboratory parameter
Platelet, × 103/µL175.2±73.3178.6±72.7111.2±52.2<0.001
AST, U/L24 (20–31)23 (20–30)33 (28–49)<0.001
ALT, U/L17 (12–27)16 (12–26)25 (20–42)<0.001
Albumin, g/L3.8±0.43.8±0.43.5±0.4<0.001
Total bilirubin, mg/dL0.9±0.80.9±0.91.0±0.50.097
Prothrombin time, %88.4±15.489.3±15.377.7±12.0<0.001
Prothrombin time, INR1.1±0.11.1±0.11.2±0.1<0.001

Data are presented as mean±SD, number (%), or median (interquartile range).

SVR, sustained virologic response; DAA, direct-acting antivirals; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; AST, aspartate aminotransferase; ALT, alanine aminotransferase; INR, international normalized ratio.


Table 2 Predictive Factors for Hepatocellular Carcinoma Development

VariableUnivariate analysisMultivariable analysis
HR (95% CI)p-valueAHR (95% CI)p-value
Sex, male1.73 (0.96–3.13)0.072.21 (1.21–4.06)0.01
Liver cirrhosis11.9 (5.27–26.80)<0.0017.93 (3.39–18.60)<0.001
History of interferon–use1.26 (0.60–2.64)0.50
Age, per 1 yr increase*1.06 (1.03–1.09)<0.0011.05 (1.02–1.08)<0.001
Platelet*0.99 (0.89–0.99)<0.001
ALT*1.01 (1.00–1.01)<0.001
Albumin*0.26 (0.14–0.47)<0.0010.84 (0.38–1.86)0.70
Total bilirubin*1.12 (0.85–1.47)0.40
Prothrombin time*0.96 (0.94–0.97)<0.0010.98 (0.95–1.00)0.07

HR, hazard ratio; CI, confidence interval; AHR, adjusted HR; ALT, alanine aminotransferase.

*All variables were included the values at the time of sustained virologic response.


Table 3 Cumulative Incidence of De Novo HCC According to Various Risk Scoring Systems at the Time of Sustained Virologic Response

NSSCutoffPatients, nPerson-yearsHCC, nHCC incidencep-value
Total8733,542.0441.24
PAGE-B11High (≥18)208860.6212.44<0.001
Intermediate (10–17)4832,039.9221.08
Low (≤9)182641.610.16
mPAGE-B16High (≥13)4331,851.5392.11<0.001
Intermediate (9–12)3221,319.650.38
Low (≤8)118370.900.00
THRI12High (>240)52197.8105.06<0.001
Intermediate (120–240)7792,208.8321.45
Low (<120)421,135.520.18
APRI13≥1.5155739.3192.57<0.001
0.5–1.56062,395.1220.92
≤0.5112407.730.74
FIB-414>3.252191,065.2353.29<0.001
≤3.256542,476.990.36
>1.456612,823.0431.52<0.001
≤1.45212719.010.14
ALBI17Grade 3 (≥–1.39)7182,991.3411.370.12
Grade 2 (–2.60 to –1.39)155550.830.54
Grade 1 (≤–2.60)000NA
aMAP8High (≥60)4792,083.8401.92<0.001
Intermediate (50–60)2851,086.240.37
Low (≤50)109372.100.00

HCC, hepatocellular carcinoma; NSS, noninvasive scoring system; mPAGE-B, modified PAGE-B; THRI, Toronto HCC risk index; APRI, aspartate aminotransferase-to-platelet ratio index; FIB-4, fibrosis-4; ALBI, albumin-bilirubin; aMAP, age male albumin-bilirubin platelet; NA, not available.


Table 4 Time-Dependent AUC According to Various Risk Scoring Systems for Predicting the Development of HCC

ScoreHeagerty’s integrated AUCTime-dependent AUC at 3 yrTime-dependent AUC at 5 yrTime-dependent AUC at 7 yr
PAGE-B at baseline0.738 (0.661–0.814)0.713 (0.609–0.817)0.667 (0.578–0.757)0.760 (0.657–0.864)
PAGE-B at SVR0.749 (0.668–0.829)0.725 (0.628–0.821)0.690 (0.607–0.773)0.743 (0.642–0.844)
p-value0.6620.3830.2470.307
mPAGE-B at baseline0.752 (0.671–0.833)0.723 (0.620–0.826)0.698 (0.607–0.789)0.755 (0.658–0.852)
mPAGE-B at SVR0.795 (0.716–0.874)0.778 (0.685–0.870)0.746 (0.670–0.822)0.812 (0.730–0.893)
p-value0.9530.1220.1080.072
THRI at baseline0.760 (0.677–0.843)0.724 (0.614–0.835)0.721 (0.640–0.802)0.781 (0.688–0.873)
THRI at SVR0.778 (0.702–0.855)0.758 (0.668–0.848)0.729 (0.655–0.802)0.783 (0.693–0.872)
p-value0.7830.1760.4070.478
APRI at baseline0.694 (0.600–0.788)0.687 (0.575–0.799)0.682 (0.569–0.795)0.659 (0.536–0.781)
APRI at SVR0.688 (0.604–0.771)0.649 (0.544–0.755)0.659 (0.550–0.767)0.555 (0.421–0.689)
p-value0.4420.2820.3500.067
FIB-4 at baseline0.762 (0.700–0.824)0.750 (0.676–0.823)0.745 (0.657–0.833)0.717 (0.607–0.828)
FIB-4 at SVR0.778 (0.714–0.843)0.760 (0.680–0.839)0.736 (0.643–0.829)0.624 (0.478–0.770)
p-value0.7400.4120.4230.058
ALBI at baseline0.542 (0.439–0.646)0.513 (0.388–0.638)0.478 (0.383–0.574)0.382 (0.246–0.518)
ALBI at SVR0.632 (0.543–0.720)0.600 (0.487–0.713)0.601 (0.514–0.688)0.517 (0.377–0.656)
p-value0.9610.0300.0010.109
aMAP at baseline0.733 (0.657–0.809)0.716 (0.616–0.816)0.694 (0.612–0.777)0.722 (0.623–0.821)
aMAP at SVR0.781 (0.706–0.855)0.776 (0.682–0.869)0.747 (0.676–0.818)0.790 (0.700–0.880)
p-value0.9840.0660.0490.046

AUC, area under the curve; HCC, hepatocellular carcinoma; SVR, sustained virologic response; mPAGE, modified PAGE; THRI, Toronto HCC risk index; APRI, aspartate aminotransferase-to-platelet ratio index; FIB-4, fibrosis-4; ALBI, albumin-bilirubin; aMAP, age male albumin-bilirubin platelet.


References

  1. Axley P, Ahmed Z, Ravi S, Singal AK. Hepatitis C virus and hepatocellular carcinoma: a narrative review. J Clin Transl Hepatol 2018;6:79-84.
    Pubmed KoreaMed CrossRef
  2. Park YJ, Woo HY, Heo J, et al. Real-life effectiveness and safety of glecaprevir/pibrentasvir for Korean patients with chronic hepatitis C at a single institution. Gut Liver 2021;15:440-450.
    Pubmed KoreaMed CrossRef
  3. Heo J, Kim YJ, Lee JW, et al. Efficacy and safety of glecaprevir/pibrentasvir in Korean patients with chronic hepatitis C: a pooled analysis of five phase II/III trials. Gut Liver 2021;15:895-903.
    Pubmed KoreaMed CrossRef
  4. Semmler G, Meyer EL, Kozbial K, et al. HCC risk stratification after cure of hepatitis C in patients with compensated advanced chronic liver disease. J Hepatol 2022;76:812-821.
    Pubmed CrossRef
  5. D'Ambrosio R, Degasperi E, Anolli MP, et al. Incidence of liver- and non-liver-related outcomes in patients with HCV-cirrhosis after SVR. J Hepatol 2022;76:302-310.
    Pubmed CrossRef
  6. Ahn YH, Lee H, Kim DY, et al. Independent risk factors for hepatocellular carcinoma recurrence after direct-acting antiviral therapy in patients with chronic hepatitis C. Gut Liver 2021;15:410-419.
    Pubmed KoreaMed CrossRef
  7. European Association for the Study of the Liver. EASL clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 2018;69:182-236.
    Pubmed CrossRef
  8. Marrero JA, Kulik LM, Sirlin CB, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases. Hepatology 2018;68:723-750.
    Pubmed CrossRef
  9. Kanda T, Lau GK, Wei L, et al. APASL HCV guidelines of virus-eradicated patients by DAA on how to monitor HCC occurrence and HBV reactivation. Hepatol Int 2019;13:649-661.
    Pubmed KoreaMed CrossRef
  10. Luna-Cuadros MA, Chen HW, Hanif H, Ali MJ, Khan MM, Lau DT. Risk of hepatocellular carcinoma after hepatitis C virus cure. World J Gastroenterol 2022;28:96-107.
    Pubmed KoreaMed CrossRef
  11. Yamashita Y, Joshita S, Sugiura A, et al. aMAP score prediction of hepatocellular carcinoma occurrence and incidence-free rate after a sustained virologic response in chronic hepatitis C. Hepatol Res 2021;51:933-942.
    Pubmed CrossRef
  12. Omata M, Cheng AL, Kokudo N, et al. Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma: a 2017 update. Hepatol Int 2017;11:317-370.
    Pubmed KoreaMed CrossRef
  13. Korean Liver Cancer AssociationNational Cancer Center. 2018 Korean Liver Cancer Association-National Cancer Center Korea practice guidelines for the management of hepatocellular carcinoma. Gut Liver 2019;13:227-299.
    Pubmed KoreaMed CrossRef
  14. Papatheodoridis G, Dalekos G, Sypsa V, et al. PAGE-B predicts the risk of developing hepatocellular carcinoma in Caucasians with chronic hepatitis B on 5-year antiviral therapy. J Hepatol 2016;64:800-806.
    Pubmed CrossRef
  15. Sharma SA, Kowgier M, Hansen BE, et al. Toronto HCC risk index: a validated scoring system to predict 10-year risk of HCC in patients with cirrhosis. J Hepatol 2018;68:92-99.
    Pubmed CrossRef
  16. Lin ZH, Xin YN, Dong QJ, et al. Performance of the aspartate aminotransferase-to-platelet ratio index for the staging of hepatitis C-related fibrosis: an updated meta-analysis. Hepatology 2011;53:726-736.
    Pubmed CrossRef
  17. Sterling RK, Lissen E, Clumeck N, et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology 2006;43:1317-1325.
    Pubmed CrossRef
  18. Fan R, Papatheodoridis G, Sun J, et al. aMAP risk score predicts hepatocellular carcinoma development in patients with chronic hepatitis. J Hepatol 2020;73:1368-1378.
    Pubmed CrossRef
  19. Kim JH, Kim YD, Lee M, et al. Modified PAGE-B score predicts the risk of hepatocellular carcinoma in Asians with chronic hepatitis B on antiviral therapy. J Hepatol 2018;69:1066-1073.
    Pubmed CrossRef
  20. Johnson PJ, Berhane S, Kagebayashi C, et al. Assessment of liver function in patients with hepatocellular carcinoma: a new evidence-based approach-the ALBI grade. J Clin Oncol 2015;33:550-558.
    Pubmed KoreaMed CrossRef
  21. Harrell FE, Lee KL, Matchar DB, Reichert TA. Regression models for prognostic prediction: advantages, problems, and suggested solutions. Cancer Treat Rep 1985;69:1071-1077.
    Pubmed
  22. Heagerty PJ, Zheng Y. Survival model predictive accuracy and ROC curves. Biometrics 2005;61:92-105.
    Pubmed CrossRef
  23. Ioannou GN. HCC surveillance after SVR in patients with F3/F4 fibrosis. J Hepatol 2021;74:458-465.
    Pubmed CrossRef
  24. Caviglia GP, Troshina G, Santaniello U, et al. Long-term hepatocellular carcinoma development and predictive ability of non-invasive scoring systems in patients with HCV-related cirrhosis treated with direct-acting antivirals. Cancers (Basel) 2022;14:828.
    Pubmed KoreaMed CrossRef
  25. Tamaki N, Kurosaki M, Yasui Y, et al. Change in fibrosis 4 index as predictor of high risk of incident hepatocellular carcinoma after eradication of hepatitis C virus. Clin Infect Dis 2021;73:e3349-e3354.
    Pubmed KoreaMed CrossRef
  26. Alonso López S, Manzano ML, Gea F, et al. A model based on noninvasive markers predicts very low hepatocellular carcinoma risk after viral response in hepatitis C virus-advanced fibrosis. Hepatology 2020;72:1924-1934.
    Pubmed CrossRef
  27. Lee HW, Chon YE, Kim SU, et al. Predicting liver-related events using transient elastography in chronic hepatitis C patients with sustained virological response. Gut Liver 2016;10:429-436.
    Pubmed KoreaMed CrossRef
Gut and Liver

Vol.18 No.2
March, 2024

pISSN 1976-2283
eISSN 2005-1212

qrcode
qrcode

Supplementary

Share this article on :

  • line

Popular Keywords

Gut and LiverQR code Download
qr-code

Editorial Office