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Wu Y, Wang M, Zhang Z, Chen G, Zhang B. A Novel Nomogram Model for Predicting the Risk of Hepatocellular Carcinoma in Patients with Chronic Hepatitis B Infection. J Hepatocell Carcinoma 2025; 12:765-775. [PMID: 40255900 PMCID: PMC12009588 DOI: 10.2147/jhc.s512471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2024] [Accepted: 04/05/2025] [Indexed: 04/22/2025] Open
Abstract
Purpose Hepatitis B virus (HBV) infection is a major cause of hepatocellular carcinoma (HCC). This study aimed to construct a novel nomogram model for predicting the risk of HCC in patients with HBV infection. Patients and Methods This retrospective study analyzed clinical data from healthcare databases in Xiamen, encompassing 5161 adults with HBV infection without HCC and 2819 adults with HBV-related HCC between January 2016 and December 2020. Subsequently, the patients were randomly divided into a training set (n=5586) and testing set (n=2394). The training set was used to identify the risk factors for HCC development and to construct an HCC risk prediction nomogram model. The predictive accuracy of the model was assessed using the receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) in both sets. Furthermore, the performance of the nomogram model was compared with that of the existing models. Results Multivariate analysis revealed that age, sex, liver cirrhosis, neutrophil/platelet count ratio (NLR), serum bilirubin (TBIL), aspartate aminotransferase (AST), serum albumin (ALB), serum alpha-fetoprotein (AFP), and HBV DNA were independently associated with HCC. A nomogram model was developed by incorporating these risk factors. The the receiver operating characteristic curve (AUC) of the nomogram model were 0.897 and 0.902 for the training and testing sets, respectively. Analysis of the AUC demonstrated that the nomogram model exhibited significantly enhanced predictive performance for HCC compared to the alternative risk scores in both sets. Furthermore, DCA indicated that the nomogram model provided a broad range of threshold probabilities related to the net clinical benefits. A web-based calculator was developed(https://nomogram-model-hcc.shinyapps.io/DynNomapp/). Conclusion The novel nomogram model, which includes age, sex, liver cirrhosis, NLR, TBIL, AST, ALB, AFP, and HBV DNA as factors, precisely predicts the risk of HCC in patients with chronic hepatitis B(CHB) and outperforms the existing models.
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Affiliation(s)
- Yanfang Wu
- Department of Hepatic Oncology, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen Clinical Research Center for Cancer Therapy, Clinical Research Center for Precision medicine of abdominal tumor of Fujian Province, Xiamen, 361015, People’s Republic of China
| | - Meixia Wang
- Department of Hospital Infection Management, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen, Fujian, 361015, People’s Republic of China
| | - Zhenzhen Zhang
- Department of Hepatic Oncology, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen Clinical Research Center for Cancer Therapy, Clinical Research Center for Precision medicine of abdominal tumor of Fujian Province, Xiamen, 361015, People’s Republic of China
| | - Guobin Chen
- Department of Hepatic Oncology, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen Clinical Research Center for Cancer Therapy, Clinical Research Center for Precision medicine of abdominal tumor of Fujian Province, Xiamen, 361015, People’s Republic of China
| | - Boheng Zhang
- Department of Hepatic Oncology, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen Clinical Research Center for Cancer Therapy, Clinical Research Center for Precision medicine of abdominal tumor of Fujian Province, Xiamen, 361015, People’s Republic of China
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Inoue J, Minami S, Abe K, Kida M, Haga H, Iino C, Numao H, Kuroda H, Ninomiya M, Tsuruoka M, Sato K, Onuki M, Sawahashi S, Ouchi K, Watanabe K, Akahane T, Kobayashi T, Ohira H, Ueno Y, Masamune A. Validation Study of Scores Predicting Hepatocellular Carcinoma Risk in Chronic Hepatitis B Patients Treated With Nucleos(t)ide Analogues. J Viral Hepat 2025; 32:e70021. [PMID: 40052685 PMCID: PMC11887419 DOI: 10.1111/jvh.70021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2024] [Revised: 02/02/2025] [Accepted: 02/23/2025] [Indexed: 03/10/2025]
Abstract
Chronic hepatitis B virus (HBV) infection is a leading cause of hepatocellular carcinoma (HCC) worldwide. Nucleos(t)ide analogues (NAs) are widely used in chronically HBV-infected patients, but the risk of HCC still remains in NA-treated patients. In this study, we aimed to validate the HCC risk scores for HBV-infected patients treated with nucleos(t)ide analogues (NAs). Among a total of 360 chronically HBV-infected patients who were treated with NAs, 253 patients without a history of HCC were used to validate the PAGE-B, mPAGE-B, PAGED-B, APA-B, and aMAP scores, as well as a recently developed score, the FAL-1 score, which consists of the FIB-4 index and ALT at 1 year of NA. In this cohort, the cumulative incidence of HCC at 5, 10, and 15 years was 2.9%, 7.8% and 11.0%, respectively. Most scores significantly stratified the HCC incidence and, for the FAL-1 score, the cumulative incidence of HCC at 10 years was 0%, 11.3% and 17.2% for the score-0 (n = 91), score-1 (n = 129) and score-2 (n = 30) groups, respectively. Compared with the other scores, the FAL-1 score was shown to efficiently identify patients at very low risk of HCC. An analysis using both this validation and the previously reported derivation cohorts demonstrated the utility in patients with either HBV genotype B or C. In conclusion, the utility of the FAL-1 score was reproduced in this validation study as well as other scores. In particular, the FAL-1 score may be useful to efficiently identify patients with a low risk of HCC.
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Affiliation(s)
- Jun Inoue
- Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
- Institute for Excellence in Higher EducationTohoku UniversitySendaiJapan
| | - Shinichiro Minami
- Department of GastroenterologyAkita University Graduate School of MedicineAkitaJapan
| | - Kazumichi Abe
- Department of GastroenterologyFukushima Medical University School of MedicineFukushimaJapan
| | - Mami Kida
- Department of Internal MedicineKurihara Central HospitalKuriharaJapan
| | - Hiroaki Haga
- Department of Gastroenterology, Faculty of MedicineYamagata UniversityYamagataJapan
| | - Chikara Iino
- Department of Gastroenterology, Hematology and Clinical ImmunologyHirosaki University Graduate School of MedicineHirosakiJapan
| | - Hiroshi Numao
- Department of GastroenterologyAomori Prefectural Central HospitalAomoriJapan
| | - Hidekatsu Kuroda
- Division of Gastroenterology and Hepatology, Department of Internal MedicineIwate Medical University School of MedicineYahabaJapan
| | - Masashi Ninomiya
- Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
- Institute for Excellence in Higher EducationTohoku UniversitySendaiJapan
| | - Mio Tsuruoka
- Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
| | - Kosuke Sato
- Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
| | - Masazumi Onuki
- Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
| | - Satoko Sawahashi
- Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
| | - Keishi Ouchi
- Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
| | - Kengo Watanabe
- Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
| | - Takehiro Akahane
- Department of GastroenterologyJapanese Red Cross Ishinomaki HospitalIshinomakiJapan
| | - Tomoo Kobayashi
- Department of GastroenterologyTohoku Rosai HospitalSendaiJapan
| | - Hiromasa Ohira
- Department of GastroenterologyFukushima Medical University School of MedicineFukushimaJapan
| | - Yoshiyuki Ueno
- Department of Gastroenterology, Faculty of MedicineYamagata UniversityYamagataJapan
| | - Atsushi Masamune
- Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
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Ramier C, Protopopescu C, Di Beo V, Parlati L, Marcellin F, Carrat F, Asselah T, Bourlière M, Carrieri P. Behaviour-Based Predictive Scores of Hepatocellular Carcinoma in People With Chronic Hepatitis B (ANRS CO22 HEPATHER). Liver Int 2025; 45:e70065. [PMID: 40087922 PMCID: PMC11909585 DOI: 10.1111/liv.70065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Revised: 01/21/2025] [Accepted: 03/05/2025] [Indexed: 03/17/2025]
Abstract
BACKGROUND AND AIMS Early assessment of hepatocellular carcinoma (HCC) risk could improve long-term outcomes in people with chronic hepatitis B virus (HBV) infection. Some existing HCC predictive scores are not easily implementable. We developed easy-to-use HCC predictive scores based on behavioural and routine bio-clinical data in people with chronic HBV infection. METHODS Eight-year follow-up data was analysed from people with chronic HBV infection enrolled in the French ANRS CO22 HEPATHER cohort. Patients were randomly split into two samples (training/testing). A multivariable Cox model for time to HCC was estimated on the training sample. The HCC predictive score was computed by summing the points assigned to model predictors, normalising their coefficients over a 10-year age increment, and rounding to the nearest integer. The Youden index identified the score's optimal risk threshold. Comparisons with existing predictive scores were performed on the testing sample. RESULTS In the study population (N = 4370; 63% of men; 65% of < 50 years old), 56 HCC cases occurred during 25,900 follow-up person-years. Two HCC predictive scores were defined: SADAPTT (daily soft drink consumption, age, hepatitis Delta infection, unhealthy alcohol use, platelet count, heavy tobacco smoking, and HBV treatment) and ADAPTT (the same predictors except for daily soft drink consumption), with ranges 0-13 and 0-14, respectively, and values ≥ 3 indicating a high HCC risk. Their performances were similar to existing scores. CONCLUSIONS We developed two effective behaviour-based HCC predictive scores, implementable in many settings, including primary care and decentralised areas. Further studies are needed to validate these scores in other datasets.
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Affiliation(s)
- Clémence Ramier
- Aix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information MédicaleMarseilleFrance
| | - Camelia Protopopescu
- Aix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information MédicaleMarseilleFrance
| | - Vincent Di Beo
- Aix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information MédicaleMarseilleFrance
| | - Lucia Parlati
- Département d'Hépatologie/AddictologieUniversité de Paris Cité; INSERM U1016, AP‐HP, Hôpital CochinParisFrance
| | - Fabienne Marcellin
- Aix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information MédicaleMarseilleFrance
| | - Fabrice Carrat
- Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pierre Louis d'Epidémiologie et de Santé Publique, Sorbonne UniversitéParisFrance
- Hôpital Saint‐Antoine, Unité de Santé Publique, Assistance Publique‐Hôpitaux de Paris (AP‐HP)ParisFrance
| | - Tarik Asselah
- Department of HepatologyCentre de Recherche Sur l'Inflammation, INSERM UMR 1149, Hôpital Beaujon, Université de Paris‐CitéClichyFrance
| | - Marc Bourlière
- Aix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information MédicaleMarseilleFrance
- Département d'hépatologie et GastroentérologieHôpital Saint JosephMarseilleFrance
| | - Patrizia Carrieri
- Aix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Économiques and Sociales de la Santé and Traitement de l'Information MédicaleMarseilleFrance
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Yu H, Huang Y, Li M, Jiang H, Yang B, Xi X, Smayi A, Wu B, Yang Y. Prognostic significance of dynamic changes in liver stiffness measurement in patients with chronic hepatitis B and compensated advanced chronic liver disease. J Gastroenterol Hepatol 2024; 39:2169-2181. [PMID: 38946401 DOI: 10.1111/jgh.16673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Revised: 06/07/2024] [Accepted: 06/16/2024] [Indexed: 07/02/2024]
Abstract
BACKGROUND AND AIM Liver stiffness measurements (LSMs) are promising for monitoring disease progression or regression. We assessed the prognostic significance of dynamic changes in LSM over time on liver-related events (LREs) and death in patients with chronic hepatitis B (CHB) and compensated advanced chronic liver disease (cACLD). METHODS This retrospective study included 1272 patients with CHB and cACLD who underwent at least two measurements, including LSM and fibrosis score based on four factors (FIB-4). ΔLSM was defined as [(follow-up LSM - baseline LSM)/baseline LSM × 100]. We recorded LREs and all-cause mortality during a median follow-up time of 46 months. Hazard ratios (HRs) and confidence intervals (CIs) for outcomes were calculated using Cox regression. RESULTS Baseline FIB-4, baseline LSM, ΔFIB-4, ΔLSM, and ΔLSM/year were independently and simultaneously associated with LREs (adjusted HR, 1.04, 95% CI, 1.00-1.07; 1.02, 95% CI, 1.01-1.03; 1.06, 95% CI, 1.03-1.09; 1.96, 95% CI, 1.63-2.35, 1.02, 95% CI, 1.01-1.04, respectively). The baseline LSM combined with the ΔLSM achieved the highest Harrell's C (0.751), integrated AUC (0.776), and time-dependent AUC (0.737) for LREs. Using baseline LSM and ΔLSM, we proposed a risk stratification method to improve clinical applications. The risk proposed stratification based on LSM performed well in terms of prognosis: low risk (n = 390; reference), intermediate risk (n = 446; HR = 3.38), high risk (n = 272; HR = 5.64), and extremely high risk (n = 164; HR = 11.11). CONCLUSIONS Baseline and repeated noninvasive tests measurement allow risk stratification of patients with CHB and cACLD. Combining baseline and dynamic changes in the LSM improves prognostic prediction.
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Affiliation(s)
- Hongsheng Yu
- Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, China
- Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China
| | - Yinan Huang
- Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, China
- Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China
| | - Mingkai Li
- Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, China
- Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China
| | - Hao Jiang
- Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, China
- Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China
| | - Bilan Yang
- Department of Gastrointestinal Endoscopy Center, The Eighth Affiliated Hospital, Sun Yat-sen University, 518033, Shenzhen, China
| | - Xiaoli Xi
- Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, China
- Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China
| | - Abdukyamu Smayi
- Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, China
- Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China
| | - Bin Wu
- Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, China
- Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China
| | - Yidong Yang
- Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, China
- Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China
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Mak LY. Disease modifiers and novel markers in hepatitis B virus-related hepatocellular carcinoma. JOURNAL OF LIVER CANCER 2024; 24:145-154. [PMID: 39099070 PMCID: PMC11449577 DOI: 10.17998/jlc.2024.08.03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Revised: 07/25/2024] [Accepted: 08/03/2024] [Indexed: 08/06/2024]
Abstract
Chronic hepatitis B (CHB) infection is responsible for 40% of the global burden of hepatocellular carcinoma (HCC) with a high case fatality rate. The risk of HCC differs among CHB subjects owing to differences in host and viral factors. Modifiable risk factors include viral load, use of antiviral therapy, co-infection with other hepatotropic viruses, concomitant metabolic dysfunctionassociated steatotic liver disease or diabetes mellitus, environmental exposure, and medication use. Detecting HCC at early stage improves survival, and current practice recommends HCC surveillance among individuals with cirrhosis, family history of HCC, or above an age cut-off. Ultrasonography with or without serum alpha feto-protein (AFP) every 6 months is widely accepted strategy for HCC surveillance. Novel tumor-specific markers, when combined with AFP, improve diagnostic accuracy than AFP alone to detect HCC at an early stage. To predict the risk of HCC, a number of clinical risk scores have been developed but none of them are clinically implemented nor endorsed by clinical practice guidelines. Biomarkers that reflect viral transcriptional activity and degree of liver fibrosis can potentially stratify the risk of HCC, especially among subjects who are already on antiviral therapy. Ongoing exploration of these novel biomarkers is required to confirm their performance characteristics, replicability and practicability.
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Affiliation(s)
- Lung-Yi Mak
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong SAR, China
- State Key Laboratory of Liver Research, The Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
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Chen J, Feng T, Xu Q, Yu X, Han Y, Yu D, Gong Q, Xue Y, Zhang X. Risk predictive model for the development of hepatocellular carcinoma before initiating long-term antiviral therapy in patients with chronic hepatitis B virus infection. J Med Virol 2024; 96:e29884. [PMID: 39206860 DOI: 10.1002/jmv.29884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 07/28/2024] [Accepted: 08/14/2024] [Indexed: 09/04/2024]
Abstract
It is generally acknowledged that antiviral therapy can reduce the incidence of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), there remains a subset of patients with chronic HBV infection who develop HCC despite receiving antiviral treatment. This study aimed to develop a model capable of predicting the long-term occurrence of HCC in patients with chronic HBV infection before initiating antiviral therapy. A total of 1450 patients with chronic HBV infection, who received initial antiviral therapy between April 2006 and March 2023 and completed long-term follow-ups, were nonselectively enrolled in this study. Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis was used to construct the model. The results were validated in an external cohort (n = 210) and compared with existing models. The median follow-up time for all patients was 60 months, with a maximum follow-up time of 144 months, during which, 32 cases of HCC occurred. The nomogram model for predicting HCC based on GGT, AFP, cirrhosis, gender, age, and hepatitis B e antibody (TARGET-HCC) was constructed, demonstrating a good predictive performance. In the derivation cohort, the C-index was 0.906 (95% CI = 0.869-0.944), and in the validation cohort, it was 0.780 (95% CI = 0.673-0.886). Compared with existing models, TARGET-HCC showed promising predictive performance. Additionally, the time-dependent feature importance curve indicated that gender consistently remained the most stable predictor for HCC throughout the initial decade of antiviral therapy. This simple predictive model based on noninvasive clinical features can assist clinicians in identifying high-risk patients with chronic HBV infection for HCC before the initiation of antiviral therapy.
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Affiliation(s)
- Junjie Chen
- Department of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tienan Feng
- Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qi Xu
- Department of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaoqi Yu
- Department of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yue Han
- Department of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Demin Yu
- Department of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiming Gong
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuan Xue
- Institute of Hepatology, The Third People's Hospital of Changzhou, Changzhou, Jiangsu, China
- Department of Liver Diseases, The Third People's Hospital of Changzhou, Changzhou, Jiangsu, China
| | - Xinxin Zhang
- Department of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Research Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Ray G. Applicability of Risk Scores to an Indian Cohort of Hepatitis B-Related Hepatocellular Carcinoma Patients. J Clin Exp Hepatol 2024; 14:101370. [PMID: 38495460 PMCID: PMC10940981 DOI: 10.1016/j.jceh.2024.101370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 02/14/2024] [Indexed: 03/19/2024] Open
Abstract
Image 1.
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Affiliation(s)
- Gautam Ray
- Gastroenterology Unit, Department of Medicine, B.R.Singh Hospital, Eastern Railway, Sealdah, Kolkata 700014, India
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Lin H, Li G, Delamarre A, Ahn SH, Zhang X, Kim BK, Liang LY, Lee HW, Wong GLH, Yuen PC, Chan HLY, Chan SL, Wong VWS, de Lédinghen V, Kim SU, Yip TCF. A Liver Stiffness-Based Etiology-Independent Machine Learning Algorithm to Predict Hepatocellular Carcinoma. Clin Gastroenterol Hepatol 2024; 22:602-610.e7. [PMID: 37993034 DOI: 10.1016/j.cgh.2023.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 10/30/2023] [Accepted: 11/01/2023] [Indexed: 11/24/2023]
Abstract
BACKGROUND & AIMS The existing hepatocellular carcinoma (HCC) risk scores have modest accuracy, and most are specific to chronic hepatitis B infection. In this study, we developed and validated a liver stiffness-based machine learning algorithm (ML) for prediction and risk stratification of HCC in various chronic liver diseases (CLDs). METHODS MLs were trained for prediction of HCC in 5155 adult patients with various CLDs in Korea and further tested in 2 prospective cohorts from Hong Kong (HK) (N = 2732) and Europe (N = 2384). Model performance was assessed according to Harrell's C-index and time-dependent receiver operating characteristic (ROC) curve. RESULTS We developed the SMART-HCC score, a liver stiffness-based ML HCC risk score, with liver stiffness measurement ranked as the most important among 9 clinical features. The Harrell's C-index of the SMART-HCC score in HK and Europe validation cohorts were 0.89 (95% confidence interval, 0.85-0.92) and 0.91 (95% confidence interval, 0.87-0.95), respectively. The area under ROC curves of the SMART-HCC score for HCC in 5 years was ≥0.89 in both validation cohorts. The performance of SMART-HCC score was significantly better than existing HCC risk scores including aMAP score, Toronto HCC risk index, and 7 hepatitis B-related risk scores. Using dual cutoffs of 0.043 and 0.080, the annual HCC incidence was 0.09%-0.11% for low-risk group and 2.54%-4.64% for high-risk group in the HK and Europe validation cohorts. CONCLUSIONS The SMART-HCC score is a useful machine learning-based tool for clinicians to stratify HCC risk in patients with CLDs.
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Affiliation(s)
- Huapeng Lin
- Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong; State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong
| | - Guanlin Li
- Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong; State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong
| | - Adèle Delamarre
- Hepatology Unit, Hôpital Haut Lévêque, Bordeaux University Hospital, Bordeaux, France; INSERM U1312, Bordeaux University, Bordeaux, France
| | - Sang Hoon Ahn
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea; Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Xinrong Zhang
- Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong; State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong
| | - Beom Kyung Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea; Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Lilian Yan Liang
- Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong; State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong
| | - Hye Won Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea; Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Grace Lai-Hung Wong
- Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong; State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong
| | - Pong-Chi Yuen
- Department of Computer Science, Hong Kong Baptist University, Hong Kong
| | - Henry Lik-Yuen Chan
- Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong; Union Hospital, Hong Kong
| | - Stephen Lam Chan
- Department of Clinical Oncology, Sir YK Pao Centre for Cancer, The Chinese University of Hong Kong, Hong Kong; State Key Laboratory of Translational Oncology, The Chinese University of Hong Kong, Hong Kong
| | - Vincent Wai-Sun Wong
- Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong; State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong
| | - Victor de Lédinghen
- Hepatology Unit, Hôpital Haut Lévêque, Bordeaux University Hospital, Bordeaux, France; INSERM U1312, Bordeaux University, Bordeaux, France.
| | - Seung Up Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea; Yonsei Liver Center, Severance Hospital, Seoul, Korea.
| | - Terry Cheuk-Fung Yip
- Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong; State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong.
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Yim HJ, Kang SH, Jung YK, Ahn SH, Kim W, Yang JM, Jang JY, Kweon YO, Cho YK, Kim YJ, Hong GY, Kim DJ, Sohn JH, Lee JW, Park SJ, Yim SY, Park JK, Um SH. Reduced Risk of Hepatocellular Carcinoma in Patients with Chronic Hepatitis B Receiving Long-Term Besifovir Therapy. Cancers (Basel) 2024; 16:887. [PMID: 38473248 DOI: 10.3390/cancers16050887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 02/14/2024] [Accepted: 02/20/2024] [Indexed: 03/14/2024] Open
Abstract
No information is available regarding the influence of besifovir (BSV), a new nucleotide analogue, on the occurrence of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). This study evaluated the reduced risk of HCC in patients undergoing BSV treatment. A total of 188 patients with CHB were treated with BSV for up to 8 years. We prospectively assessed the incidence of HCC compared with the risk from prediction models. During the follow-up, 5 patients developed HCC: 1 of 139 patients with non-cirrhotic CHB, and 4 of 49 patients with liver cirrhosis. We compared the HCC incidence in non-cirrhotic and cirrhotic patients with the predicted number derived from the REACH-B (risk estimation for HCC in CHB) model and GAG-HCC (guide with age, gender, HBV DNA, core promotor mutation, and cirrhosis) model, respectively. The standardized incidence ratio (SIR) was 0.128 (p = 0.039) at 7 years in non-cirrhotic CHB patients, and the SIR was 0.371 (p = 0.047) at 7.5 years in cirrhotic patients, suggesting a significantly decreased HCC incidence in both groups. HCC prediction was available for BSV-treated patients using existing models. In conclusion, BSV decreased the risk of HCC in patients with CHB, and prediction models were applicable. Clinical trial registry website and trial number: ClinicalTrials.gov no: NCT01937806.
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Affiliation(s)
- Hyung Joon Yim
- Department of Internal Medicine, Korea University Ansan Hospital, 123, Jeokgeum-ro, Danwon-gu, Ansan 15355, Republic of Korea
| | - Seong Hee Kang
- Department of Internal Medicine, Korea University Ansan Hospital, 123, Jeokgeum-ro, Danwon-gu, Ansan 15355, Republic of Korea
| | - Young Kul Jung
- Department of Internal Medicine, Korea University Ansan Hospital, 123, Jeokgeum-ro, Danwon-gu, Ansan 15355, Republic of Korea
| | - Sang Hoon Ahn
- Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, 50-1, Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Won Kim
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, 20 Boramae-ro 5-gil, Dongjak-gu, Seoul 07061, Republic of Korea
| | - Jin Mo Yang
- Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, 93 Jungbu-daero, Paldal-gu, Suwon 16247, Republic of Korea
| | - Jae Young Jang
- Department of Internal Medicine, Soonchunhyang University Seoul Hospital, 59, Daesagwan-ro, Yongsan-gu, Seoul 04401, Republic of Korea
| | - Yong Oh Kweon
- Department of Internal Medicine, Kyungpook National University Hospital, 680 gukchaebosang-ro, Jung-gu, Daegu 41944, Republic of Korea
| | - Yong Kyun Cho
- Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul 03181, Republic of Korea
| | - Yoon Jun Kim
- Department of Internal Medicine and Liver Research Institute, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea
| | - Gun Young Hong
- Department of Internal Medicine, Kwangju Christian Hospital, 37 Yangnim-ro, Nam-gu, Gwangju 61661, Republic of Korea
| | - Dong Joon Kim
- Department of Internal Medicine and Center for Liver and Digestive Diseases, Hallym University Chuncheon Sacred Heart Hospital, 77 Sakju-ro, Chuncheon 24253, Republic of Korea
| | - Joo Hyun Sohn
- Department of Internal Medicine, Hanyang University Guri Hospital, 153, Gyeongchun-ro, Guri-si 11923, Republic of Korea
| | - Jin Woo Lee
- Department of Internal Medicine, Inha University Hospital, 27 Inhang-ro, Jung-gu, Incheon 22332, Republic of Korea
| | - Sung Jae Park
- Department of Internal Medicine, Inje University Busan Paik Hospital, 75 Bokji-ro, Busanjin-gu, Busan 47392, Republic of Korea
| | - Sun Young Yim
- Department of Internal Medicine, Korea University Anam Hospital, 73 Goryeodae-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Jin Kyung Park
- Ildong Pharmaceutical Company, 2, Baumoe-ro 27-gil, Seocho-gu, Seoul 06752, Republic of Korea
| | - Soon Ho Um
- Department of Internal Medicine, Korea University Anam Hospital, 73 Goryeodae-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
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10
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Zhang Y, Wan G, Li H, Gao L, Liu N, Gao P, Liu Y, Gao X, Duan X. A prediction nomogram for hepatitis B virus-associated hepatocellular carcinoma. Scand J Gastroenterol 2024; 59:70-77. [PMID: 37647217 DOI: 10.1080/00365521.2023.2252546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 08/16/2023] [Accepted: 08/23/2023] [Indexed: 09/01/2023]
Abstract
BACKGROUND The present study aimed to develop and validate a new nomogram for predicting the incidence of hepatocellular carcinoma (HCC) among chronic hepatitis B (CHB) patients receiving antiviral therapy from real-world data. METHODS The nomogram was established based on a real-world retrospective study of 764 patients with HBV from October 2008 to July 2020. A predictive model for the incidence of HCC was developed by multivariable Cox regression, and a nomogram was constructed. The predictive accuracy and discriminative ability of the nomogram were assessed by the concordance index (C-index), calibration curves, and decision curve analysis (DCA). Risk group stratification was performed to assess the predictive capacity of the nomogram. The nomogram was compared to three current commonly used predictive models. RESULTS A total of 764 patients with HBV were recruited for this study. Age, family history of HCC, alcohol consumption, and Aspartate aminotransferase-to-Platelet Ratio Index (APRI) were all independent risk predictors of HCC in CHB patients. The constructed nomogram had good discrimination with a C-index of 0.811. The calibration curve and DCA also proved the reliability and accuracy of the nomogram. Three risk groups (low, moderate, and high) with significantly different prognoses were identified (p < 0.001). The model's performance was significantly better than that of other risk models. CONCLUSIONS The nomogram was superior in predicting HCC risk among CHB patients who received antiviral treatment. The model can be utilized in clinical practice to aid decision-making on the strategy of long-term HCC surveillance, especially for moderate- and high-risk patients.
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Affiliation(s)
- Yijin Zhang
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Gang Wan
- Department of Medical Record, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Hongjie Li
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Lili Gao
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Nan Liu
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Ping Gao
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Yaping Liu
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Xuesong Gao
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Xuefei Duan
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
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11
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Hao X, Fan R, Zeng HM, Hou JL. Hepatocellular Carcinoma Risk Scores from Modeling to Real Clinical Practice in Areas Highly Endemic for Hepatitis B Infection. J Clin Transl Hepatol 2023; 11:1508-1519. [PMID: 38161501 PMCID: PMC10752803 DOI: 10.14218/jcth.2023.00087] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 05/04/2023] [Accepted: 06/02/2023] [Indexed: 01/03/2024] Open
Abstract
Hepatocellular carcinoma (HCC) accounts for the majority of primary liver cancers and represents a global health challenge. Liver cancer ranks third in cancer-related mortality with 830,000 deaths and sixth in incidence with 906,000 new cases annually worldwide. HCC most commonly occurs in patients with underlying liver disease, especially chronic hepatitis B virus (HBV) infection in highly endemic areas. Predicting HCC risk based on scoring models for patients with chronic liver disease is a simple, effective strategy for identifying and stratifying patients to improve the early diagnosis rate and prognosis of HCC. We examined 23 HCC risk scores published worldwide in CHB patients with (n=10) or without (n=13) antiviral treatment. We also described the characteristics of the risk score's predictive performance and application status. In the future, higher predictive accuracy could be achieved by combining novel technologies and machine learning algorithms to develop and update HCC risk score models and integrated early warning and diagnosis systems for HCC in hospitals and communities.
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Affiliation(s)
- Xin Hao
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Guangdong Provincial Institute of Liver Diseases, Guangzhou, Guangdong, China
| | - Rong Fan
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Guangdong Provincial Institute of Liver Diseases, Guangzhou, Guangdong, China
| | - Hong-Mei Zeng
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jin-Lin Hou
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Guangdong Provincial Institute of Liver Diseases, Guangzhou, Guangdong, China
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12
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Kim BK, Ahn SH. Prediction model of hepatitis B virus-related hepatocellular carcinoma in patients receiving antiviral therapy. J Formos Med Assoc 2023; 122:1238-1246. [PMID: 37330305 DOI: 10.1016/j.jfma.2023.05.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 05/15/2023] [Accepted: 05/24/2023] [Indexed: 06/19/2023] Open
Abstract
Chronic hepatitis B virus (HBV) infection, which ultimately leads to liver cirrhosis, hepatic decompensation, and hepatocellular carcinoma (HCC), remains a significant disease burden worldwide. Despite the use of antiviral therapy (AVT) using oral nucleos(t)ide analogs (NUCs) with high genetic barriers, the risk of HCC development cannot be completely eliminated. Therefore, bi-annual surveillance of HCC using abdominal ultrasonography with or without tumor markers is recommended for at-risk populations. For a more precise assessment of future HCC risk at the individual level, many HCC prediction models have been proposed in the era of potent AVT with promising results. It allows prognostication according to the risk of HCC development, for example, low-vs. intermediate-vs. high-risk groups. Most of these models have the advantage of high negative predictive values for HCC development, allowing exemption from biannual HCC screening. Recently, non-invasive surrogate markers for liver fibrosis, such as vibration-controlled transient elastography, have been introduced as integral components of the equations, providing better predictive performance in general. Furthermore, beyond the conventional statistical methods that primarily depend on multi-variable Cox regression analyses based on the previous literature, newer techniques using artificial intelligence have also been applied in the design of HCC prediction models. Here, we aimed to review the HCC risk prediction models that were developed in the era of potent AVT and validated among independent cohorts to address the clinical unmet needs, as well as comment on future direction to establish the individual HCC risk more precisely.
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Affiliation(s)
- Beom Kyung Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea; Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Sang Hoon Ahn
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea; Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea.
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13
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Feng S, Wang J, Wang L, Qiu Q, Chen D, Su H, Li X, Xiao Y, Lin C. Current Status and Analysis of Machine Learning in Hepatocellular Carcinoma. J Clin Transl Hepatol 2023; 11:1184-1191. [PMID: 37577233 PMCID: PMC10412715 DOI: 10.14218/jcth.2022.00077s] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/11/2022] [Accepted: 02/21/2023] [Indexed: 07/03/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a common tumor. Although the diagnosis and treatment of HCC have made great progress, the overall prognosis remains poor. As the core component of artificial intelligence, machine learning (ML) has developed rapidly in the past decade. In particular, ML has become widely used in the medical field, and it has helped in the diagnosis and treatment of cancer. Different algorithms of ML have different roles in diagnosis, treatment, and prognosis. This article reviews recent research, explains the application of different ML models in HCC, and provides suggestions for follow-up research.
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Affiliation(s)
- Sijia Feng
- General Surgery, Central South University Xiangya Hospital, Changsha, Hunan, China
| | - Jianhua Wang
- General Surgery, Central South University Xiangya Hospital, Changsha, Hunan, China
| | - Liheng Wang
- General Surgery, Central South University Xiangya Hospital, Changsha, Hunan, China
| | - Qixuan Qiu
- General Surgery, Central South University Xiangya Hospital, Changsha, Hunan, China
| | - Dongdong Chen
- General Surgery, Central South University Xiangya Hospital, Changsha, Hunan, China
| | - Huo Su
- General Surgery, Central South University Xiangya Hospital, Changsha, Hunan, China
| | - Xiaoli Li
- General Surgery, Central South University Xiangya Hospital, Changsha, Hunan, China
| | - Yao Xiao
- General Surgery, Central South University Xiangya Hospital, Changsha, Hunan, China
| | - Chiayen Lin
- General Surgery, Central South University Xiangya Hospital, Changsha, Hunan, China
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14
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Xu X, Jiang L, Zeng Y, Pan L, Lou Z, Ruan B. HCC prediction models in chronic hepatitis B patients receiving entecavir or tenofovir: a systematic review and meta-analysis. Virol J 2023; 20:180. [PMID: 37582759 PMCID: PMC10428529 DOI: 10.1186/s12985-023-02145-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 07/28/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND Our study aimed to compare the predictive performance of different hepatocellular carcinoma (HCC) prediction models in chronic hepatitis B patients receiving entecavir or tenofovir, including discrimination, calibration, negative predictive value (NPV) in low-risk, and proportion of low-risk. METHODS We conducted a systematic literature research in PubMed, EMbase, the Cochrane Library, and Web of Science before January 13, 2022. The predictive performance was assessed by area under receiver operating characteristic curve (AUROC), calibration index, negative predictive value, and the proportion in low-risk. Subgroup and meta-regression analyses of discrimination and calibration were conducted. Sensitivity analysis was conducted to validate the stability of the results. RESULTS We identified ten prediction models in 23 studies. The pooled 3-, 5-, and 10-year AUROC varied from 0.72 to 0.84, 0.74 to 0.83, and 0.76 to 0.86, respectively. REAL-B, AASL-HCC, and HCC-RESCUE achieved the best discrimination. HCC-RESCUE, PAGE-B, and mPAGE-B overestimated HCC development, whereas mREACH-B, AASL-HCC, REAL-B, CAMD, CAGE-B, SAGE-B, and aMAP underestimated it. All models were able to identify people with a low risk of HCC accurately. HCC-RESCUE and aMAP recognized over half of the population as low-risk. Subgroup analysis and sensitivity analysis showed similar results. CONCLUSION Considering the predictive performance of all four aspects, we suggest that HCC-RESCUE was the best model to utilize in clinical practice, especially in primary care and low-income areas. To confirm our findings, further validation studies with the above four components were required.
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Affiliation(s)
- Xiaolan Xu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, National Medical Center for Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Road, Shangcheng District, Hangzhou, 310000, China
- Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310000, China
| | - Lushun Jiang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, National Medical Center for Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Road, Shangcheng District, Hangzhou, 310000, China
| | - Yifan Zeng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, National Medical Center for Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Road, Shangcheng District, Hangzhou, 310000, China
| | - Liya Pan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, National Medical Center for Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Road, Shangcheng District, Hangzhou, 310000, China
| | - Zhuoqi Lou
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, National Medical Center for Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Road, Shangcheng District, Hangzhou, 310000, China
| | - Bing Ruan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, National Medical Center for Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Road, Shangcheng District, Hangzhou, 310000, China.
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15
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Yip TCF, Yurdaydin C. Improving prediction of hepatocellular carcinoma in chronic hepatitis B by machine learning: Productive relationship of medicine with computer science. Liver Int 2023; 43:1626-1628. [PMID: 37452504 DOI: 10.1111/liv.15631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 05/22/2023] [Accepted: 05/24/2023] [Indexed: 07/18/2023]
Affiliation(s)
- Terry C F Yip
- Medical Data Analytics Centre, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong, China
| | - Cihan Yurdaydin
- Department of Gastroenterology & Hepatology, Koç University Medical School, Istanbul, Turkey
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16
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Lee HW, Kim H, Park T, Park SY, Chon YE, Seo YS, Lee JS, Park JY, Kim DY, Ahn SH, Kim BK, Kim SU. A machine learning model for predicting hepatocellular carcinoma risk in patients with chronic hepatitis B. Liver Int 2023; 43:1813-1821. [PMID: 37452503 DOI: 10.1111/liv.15597] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 04/17/2023] [Accepted: 04/19/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Machine learning (ML) algorithms can be used to overcome the prognostic performance limitations of conventional hepatocellular carcinoma (HCC) risk models. We established and validated an ML-based HCC predictive model optimized for patients with chronic hepatitis B (CHB) infections receiving antiviral therapy (AVT). METHODS Treatment-naïve CHB patients who were started entecavir (ETV) or tenofovir disoproxil fumarate (TDF) were enrolled. We used a training cohort (n = 960) to develop a novel ML model that predicted HCC development within 5 years and validated the model using an independent external cohort (n = 1937). ML algorithms consider all potential interactions and do not use predefined hypotheses. RESULTS The mean age of the patients in the training cohort was 48 years, and most patients (68.9%) were men. During the median 59.3 (interquartile range 45.8-72.3) months of follow-up, 69 (7.2%) patients developed HCC. Our ML-based HCC risk prediction model had an area under the receiver-operating characteristic curve (AUC) of 0.900, which was better than the AUCs of CAMD (0.778) and REAL B (0.772) (both p < .05). The better performance of our model was maintained (AUC = 0.872 vs. 0.788 for CAMD and 0.801 for REAL B) in the validation cohort. Using cut-off probabilities of 0.3 and 0.5, the cumulative incidence of HCC development differed significantly among the three risk groups (p < .001). CONCLUSIONS Our new ML model performed better than models in terms of predicting the risk of HCC development in CHB patients receiving AVT.
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Affiliation(s)
- Hye Won Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Hwiyoung Kim
- Department of Biomedical Systems Informatics, Center for Clinical Imaging Data Science (CCIDS), Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Artificial Intelligence, Yonsei University, College of Medicine, Seoul, Republic of Korea
| | - Taeyun Park
- Department of Artificial Intelligence, Yonsei University, College of Medicine, Seoul, Republic of Korea
| | - Soo Young Park
- Department of Internal medicine, Kyungpook National University School of Medicine, Daegu, Republic of Korea
| | - Young Eun Chon
- Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Bundang, Republic of Korea
| | - Yeon Seok Seo
- Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea
| | - Jae Seung Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Jun Yong Park
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Do Young Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Sang Hoon Ahn
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Beom Kyung Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Seung Up Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
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17
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Lee YT, Fujiwara N, Yang JD, Hoshida Y. Risk stratification and early detection biomarkers for precision HCC screening. Hepatology 2023; 78:319-362. [PMID: 36082510 PMCID: PMC9995677 DOI: 10.1002/hep.32779] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 08/25/2022] [Accepted: 08/28/2022] [Indexed: 12/08/2022]
Abstract
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.
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Affiliation(s)
- Yi-Te Lee
- California NanoSystems Institute, Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, University of California, Los Angeles, Los Angeles, California
| | - Naoto Fujiwara
- Liver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Ju Dong Yang
- Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, Los Angeles, California; Comprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, Los Angeles, California; Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Yujin Hoshida
- Liver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas
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18
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Li J, Dong XQ, Cao LH, Zhang ZQ, Zhao WF, Shang QH, Zhang DZ, Ma AL, Xie Q, Gui HL, Zhang G, Liu YX, Shang J, Xie SB, Liu YQ, Zhang C, Wang GQ, Zhao H, China HepB Related Fibrosis Assessment Research Group. Factors associated with persistent positive in HBV DNA level in patients with chronic Hepatitis B receiving entecavir treatment. Front Cell Infect Microbiol 2023; 13:1151899. [PMID: 37396307 PMCID: PMC10311917 DOI: 10.3389/fcimb.2023.1151899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/12/2023] [Indexed: 07/04/2023] Open
Abstract
Introduction The clinical significance of persistent positive in Hepatitis B Virus (HBV) DNA level in patients receiving antiviral therapy is not well known. We investigated factors associated with persistent viremia (PV) in patients with chronic hepatitis B (CHB) given 78-week entecavir. Methods A total of 394 treatment-naïve CHB patients who had undergone liver biopsy at baseline and week 78 of treatment were analyzed in this prospective multicentre study. We identified patients with PV (above the lower limit of quantification, 20 IU/ml) after 78 weeks of entecavir therapy. Stepwise, forward, multivariate regression analyses of specified baseline parameters were apllied to identify factors associated with PV. Futhermore, we assessed the incidence of hepatocellular carcinoma (HCC) in all patients using models of the risk of HCC development. Results Of the 394 patients, 90 (22.8%) still with PV after 78-week antiviral treatment. Factors associated significantly with PV (vs complete virological response, CVR) were HBV DNA level ≥8 log10 IU/mL (OR, 3.727; 95% CI, 1.851-7.505; P < 0.001), Anti-HBc level < 3 log10 IU/mL (OR, 2.384; 95% CI, 1.223-4.645; P=0.011), and HBeAg seropositivity (OR, 2.871; 95% CI, 1.563-5.272; P < 0.001). Patients with PV were less likely to have fibrosis progression and HCC development than those with the CVR. Of the 11 HBeAg-positive patients with HBV DNA level ≥8 log10 IU/mL and Anti-HBc level < 3 log10 IU/mL at baseline, 9 (81.8%) had persistent positivity in HBV DNA level and 0 had fibrosis progression at week 78 of treatment. Discussion In conclusion, HBV DNA level ≥8 log10 IU/mL, Anti-HBc level < 3 log10 IU/mL and HBeAg seropositivity at baseline contribute to PV in patients with CHB receiving 78-week antiviral treatment. In addition, the rate of fibrosis progression and the risk of HCC development in patients with PV were kept low. The complete protocol for the clinical trial has been registered at clinicaltrials.gov (NCT01962155 and NCT03568578).
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Affiliation(s)
- Jun Li
- Department of Infectious Disease, Center for Liver Disease, Peking University First Hospital, Beijing, China
| | - Xiao-Qin Dong
- Department and Institute of Infectious Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Li-Hua Cao
- Department of Hepatology, The Third Hospital of Qinhuangdao, Qinhuangdao, China
| | - Zhan-Qing Zhang
- Department of Infectious Disease, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Wei-Feng Zhao
- Department of Infectious Disease, Xinxiang Medical University Affiliated Third Hospital, Xinxiang, China
| | - Qing-Hua Shang
- Department of Hepatology, No.88 Hospital of Chinese People’s Liberation Army (PLA), Jinan, China
| | - Da-Zhi Zhang
- Department of Infectious Diseases, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - An-Lin Ma
- Department of Infectious Disease, China-Japan Friendship Hospital, Beijing, China
| | - Qing Xie
- Department of Infectious Diseases, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Hong-Lian Gui
- Department of Infectious Diseases, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Guo Zhang
- Department of Gastroenterology, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Ying-Xia Liu
- Department of Infectious Diseases, The Third People’s Hospital of Shenzhen, Shenzhen, China
| | - Jia Shang
- Department of Infectious Diseases, The People’s Hospital of Henan, Zhengzhou, China
| | - Shi-Bin Xie
- Department of Infectious Disease, The Third Affiliated Hospital of Sun-Yat Sen University, Guangzhou, China
| | - Yi-Qi Liu
- Department of Infectious Disease, Center for Liver Disease, Peking University First Hospital, Beijing, China
| | - Chi Zhang
- Department of Infectious Disease, Center for Liver Disease, Peking University First Hospital, Beijing, China
| | - Gui-Qiang Wang
- Department of Infectious Disease, Center for Liver Disease, Peking University First Hospital, Beijing, China
- The Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University, Hangzhou, Zhejiang, China
- Department of Hepatology, Peking University International Hospital, Beijing, China
| | - Hong Zhao
- Department of Infectious Disease, Center for Liver Disease, Peking University First Hospital, Beijing, China
- Department of Hepatology, Peking University International Hospital, Beijing, China
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Wang HW, Chen CY, Lai HC, Hu TH, Su WP, Lu SN, Hung CH, Chuang PH, Wang JH, Chen CH, Peng CY. Prediction model of hepatocellular carcinoma in patients with hepatitis B virus-related compensated cirrhosis receiving antiviral therapy. Am J Cancer Res 2023; 13:526-537. [PMID: 36895986 PMCID: PMC9989609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/15/2023] [Indexed: 03/11/2023] Open
Abstract
The feasibility and performance of predicting hepatocellular carcinoma (HCC) using a combined albumin-bilirubin (ALBI) and fibrosis-4 (FIB-4)-based model remain unclear in patients with compensated cirrhosis and chronic hepatitis B (CHB) receiving long-term nucleos(t)ide analog (NA) therapy. We enrolled 1158 NA-naïve patients with compensated cirrhosis and CHB treated with entecavir or tenofovir disoproxil fumarate. The patients' baseline characteristics, hepatic reserve, and fibrosis indices were analyzed. The combination of ALBI and FIB-4 was used to develop a prediction model of HCC. In this cohort, the cumulative incidence rates of HCC at 3, 5, and 10 years were 8.1%, 13.2%, and 24.1%, respectively. The combination of ALBI and FIB-4, Diabetes mellitus, and Alpha-fetoprotein (AFDA) were independent risk factors for HCC. The combined ALBI and FIB-4-based prediction model (i.e., AFDA) stratified the cumulative risk of HCC into three groups (with risk scores of 0, 1-3, 4-6) among all patients (P < 0.001). AFDA exhibited the highest area under the receiver operating characteristic (0.6812) for predicting HCC, which was higher than those of aMAP (0.6591), mPAGE-B (0.6465), CAMD (0.6379), and THRI (0.6356) and significantly higher than those of PAGE-B (0.6246), AASL-HCC (0.6242), and HCC-RESCUE (0.6242). Patients with a total score of 0 (n = 187, 16.1% of total patients) had the lowest cumulative HCC incidence of 3.4% at 5 years. The combined ALBI and FIB-4-based prediction model can stratify the risk of HCC in patients with compensated cirrhosis and CHB receiving NA therapy.
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Affiliation(s)
- Hung-Wei Wang
- Centre for Digestive Medicine, Department of Internal Medicine, China Medical University Hospital Taichung, Taiwan.,School of Medicine, China Medical University Taichung, Taiwan
| | - Chi-Yi Chen
- Division of Hepatogastroenterology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi, Taiwan
| | - Hsueh-Chou Lai
- Centre for Digestive Medicine, Department of Internal Medicine, China Medical University Hospital Taichung, Taiwan.,School of Chinese Medicine, China Medical University Taichung, Taiwan
| | - Tsung-Hui Hu
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Kaohsiung, Taiwan
| | - Wen-Pang Su
- Centre for Digestive Medicine, Department of Internal Medicine, China Medical University Hospital Taichung, Taiwan
| | - Sheng-Nan Lu
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Kaohsiung, Taiwan
| | - Chao-Hung Hung
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Kaohsiung, Taiwan
| | - Po-Heng Chuang
- Centre for Digestive Medicine, Department of Internal Medicine, China Medical University Hospital Taichung, Taiwan
| | - Jing-Houng Wang
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Kaohsiung, Taiwan
| | - Chien-Hung Chen
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Kaohsiung, Taiwan
| | - Cheng-Yuan Peng
- Centre for Digestive Medicine, Department of Internal Medicine, China Medical University Hospital Taichung, Taiwan.,School of Medicine, China Medical University Taichung, Taiwan
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Lee JS, Lim TS, Lee HW, Kim SU, Park JY, Kim DY, Ahn SH, Lee HW, Lee JI, Kim JK, Min IK, Kim BK. Suboptimal Performance of Hepatocellular Carcinoma Prediction Models in Patients with Hepatitis B Virus-Related Cirrhosis. Diagnostics (Basel) 2022; 13:3. [PMID: 36611295 PMCID: PMC9818663 DOI: 10.3390/diagnostics13010003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/14/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022] Open
Abstract
This study aimed to evaluate the predictive performance of pre-existing well-validated hepatocellular carcinoma (HCC) prediction models, established in patients with HBV-related cirrhosis who started potent antiviral therapy (AVT). We retrospectively reviewed the cases of 1339 treatment-naïve patients with HBV-related cirrhosis who started AVT (median period, 56.8 months). The scores of the pre-existing HCC risk prediction models were calculated at the time of AVT initiation. HCC developed in 211 patients (15.1%), and the cumulative probability of HCC development at 5 years was 14.6%. Multivariate Cox regression analysis revealed that older age (adjusted hazard ratio [aHR], 1.023), lower platelet count (aHR, 0.997), lower serum albumin level (aHR, 0.578), and greater LS value (aHR, 1.012) were associated with HCC development. Harrell’s c-indices of the PAGE-B, modified PAGE-B, modified REACH-B, CAMD, aMAP, HCC-RESCUE, AASL-HCC, Toronto HCC Risk Index, PLAN-B, APA-B, CAGE-B, and SAGE-B models were suboptimal in patients with HBV-related cirrhosis, ranging from 0.565 to 0.667. Nevertheless, almost all patients were well stratified into low-, intermediate-, or high-risk groups according to each model (all log-rank p < 0.05), except for HCC-RESCUE (p = 0.080). Since all low-risk patients had cirrhosis at baseline, they had unneglectable cumulative incidence of HCC development (5-year incidence, 4.9−7.5%). Pre-existing risk prediction models for patients with chronic hepatitis B showed suboptimal predictive performances for the assessment of HCC development in patients with HBV-related cirrhosis.
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Affiliation(s)
- Jae Seung Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul 03722, Republic of Korea
| | - Tae Seop Lim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Division of Gastroenterology, Department of Internal Medicine, Yongin Severance Hospital, Yonsei University Health System, Gyeonggi-do, Seoul 03722, Republic of Korea
| | - Hye Won Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul 03722, Republic of Korea
| | - Seung Up Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul 03722, Republic of Korea
| | - Jun Yong Park
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul 03722, Republic of Korea
| | - Do Young Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul 03722, Republic of Korea
| | - Sang Hoon Ahn
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul 03722, Republic of Korea
| | - Hyun Woong Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Division of Gastroenterology, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University Health System, Seoul 06273, Republic of Korea
| | - Jung Il Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Division of Gastroenterology, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University Health System, Seoul 06273, Republic of Korea
| | - Ja Kyung Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Division of Gastroenterology, Department of Internal Medicine, Yongin Severance Hospital, Yonsei University Health System, Gyeonggi-do, Seoul 03722, Republic of Korea
| | - In Kyung Min
- Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Beom Kyung Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
- Yonsei Liver Center, Severance Hospital, Seoul 03722, Republic of Korea
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21
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A Mac-2 Binding Protein Glycosylation Isomer-Based Risk Model Predicts Hepatocellular Carcinoma in HBV-Related Cirrhotic Patients on Antiviral Therapy. Cancers (Basel) 2022; 14:cancers14205063. [PMID: 36291847 PMCID: PMC9599873 DOI: 10.3390/cancers14205063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 10/13/2022] [Accepted: 10/14/2022] [Indexed: 11/17/2022] Open
Abstract
Mac-2 binding protein glycosylation isomer (M2BPGi) has not been used in a risk score to predict hepatocellular carcinoma (HCC). We enrolled 1003 patients with chronic hepatitis B and cirrhosis receiving entecavir or tenofovir therapy for more than12 months to construct an HCC risk score. In the development cohort, Cox regression analysis identified male gender, age, platelet count, AFP and M2BPGi levels at 12 months of treatment as independent risk factors of HCC. We developed the HCC risk prediction model, the ASPAM-B score, based on age, sex, platelet count, AFP and M2BPGi levels at 12 months of treatment, with the total scores ranging from 0 to 11.5. This risk model accurately classified patients into low (0−3.5), medium (4−7), and high (>7) risk in the development and validation groups (p < 0.001). The areas under the receiver operating characteristic curve (AUROC) of 3-, 5- and 9-year risks of HCC were 0.742, 0.728 and 0.719, respectively, in the development cohort. All AUROC between the ASPAM-B and APA-B, PAGE-B, RWS-HCC and THRI scores at 3−9 years were significantly different. The M2BPGi-based risk model exhibited good discriminant function in predicting HCC in cirrhotic patients who received long-term antiviral treatment.
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22
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Tony SM, Shaaban MEA, Mohamed AIM, Abdelrahim MEA. Effect of entecavir and tenofovir disoproxil fumarate on hepatocellular carcinoma in subjects with chronic hepatitis B: a meta-analysis. BENI-SUEF UNIVERSITY JOURNAL OF BASIC AND APPLIED SCIENCES 2022. [DOI: 10.1186/s43088-022-00294-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Abstract
Background
A meta-analysis was made to assess the impact of entecavir comparison with tenofovir disoproxil fumarate as nucleos(t)ide analogue on hepatic cellular carcinoma (HCC). The study had subjects with chronic hepatitis B virus (HBV). Systemic research was done for all studies concerned with our topic till the date (March 2022). We included 19 studies in which 27,618 subjects participated. All subjects included were diagnosed with chronic HBV at the beginning of the study. A total of 15,734 subjects from the overall 27,618 were medicated with entecavir; however, 11,884 subjects were on tenofovir disoproxil fumarate. We calculated the odds ratio (OR) with confidence intervals (CIs) of 95% to evaluate the impact of entecavir and tenofovir disoproxil fumarate on HCC in subjects with chronic HBV by applying a dichotomous approach with a random or fixed-effect model.
Results
Chronic HBV subjects treated with entecavir showed a higher significant biochemical response than those treated with tenofovir disoproxil fumarate (OR 1.39; 95% CI 1.21–1.60, at p < 0.001). Also, no significant difference was detected with entecavir compared to tenofovir disoproxil fumarate concerning the occurrence of hepatic cells cancer (OR 1.26; 95% CI 0.96–1.67, p = 0.10), virological response (OR 0.89; 95% CI 0.63–1.25, p = 0.49), and seroconversion (OR 1.27; 95% CI 0.76–2.14, p = 0.37).
Conclusions
The use of entecavir resulted in a significantly higher biochemical response; nevertheless, it did not show any significant variation concerning the occurrence of hepatic cancer, virological response, or serological conversion compared to tenofovir disoproxil fumarate in chronic HBV subjects. So, results interpretation needs to be carried out carefully owing to the limited number of studies included in specific comparisons, e.g., serological conversion.
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Poynard T, Lacombe JM, Deckmyn O, Peta V, Akhavan S, Zoulim F, de Ledinghen V, Samuel D, Mathurin P, Ratziu V, Thabut D, Housset C, Fontaine H, Pol S, Carrat F. External Validation of LCR1-LCR2, a Multivariable Hepatocellular Carcinoma Risk Calculator, in a Multiethnic Cohort of Patients With Chronic Hepatitis B. GASTRO HEP ADVANCES 2022; 1:604-617. [PMID: 39132068 PMCID: PMC11308549 DOI: 10.1016/j.gastha.2022.02.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 02/09/2022] [Indexed: 08/13/2024]
Abstract
Background and Aims The liver cancer risk test (LCR1-LCR2) is a multianalyte blood test combining proteins involved in liver cell repair (apolipoprotein A1, haptoglobin), hepatocellular carcinoma (HCC) risk factors (gender, age, gamma glutamyl transpeptidase), a marker of fibrosis (alpha2-macroglobulin), and alpha-fetoprotein, a specific marker of HCC. The aim was to externally validate LCR1-LCR2 in hepatitis B. Methods Preincluded patients were from the Hepather cohort, a multicenter, multiethnic prospective study in 6071 patients. The coprimary study outcome was the negative predictive value of LCR1-LCR2 at 5 years for the occurrence of HCC and survival without HCC according to the predetermined LCR1-LCR2 cutoffs, adjusted for risk covariables and for chronic hepatitis B treatment and quantified using time-dependent Cox proportional hazards models. A post hoc analysis compared the number of patients needed to screen one cancer by LCR1-LCR2 and PAGE-B. Results A total of 3520 patients, 191 (5.4%) with cirrhosis, with at least 1 year of follow-up were included. A total of 76 HCCs occurred over a median (interquartile range) of 6.0 years (4.8-7.3) of follow-up. Among the 3367 patients with low-risk LCR1-LCR2, the 5-year negative predictive value was 99.3% (95% confidence interval = 99.0-99.6), with a significant Cox hazard ratio (6.4, 3.1-13.0; P < .001) obtained after adjustment for exposure to antivirals, age, gender, geographical origin, HBe-Ag status, alcohol consumption, and type-2 diabetes. LCR1-LCR2 outperformed PAGE-B for number of patients needed to screen mean (95% CI), 8.5 (3.2-8.1) vs 26.3 (17.5-38.5; P < .0001), respectively. Conclusion The performance of LCR1-LCR2 to identify patients with chronic hepatitis B at very low risk of HCC at 5 years was externally validated. ClinicalTrials.gov: NCT01953458.
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Affiliation(s)
- Thierry Poynard
- Department of Hepato-Gastroenterology, Assistance Publique-Hôpitaux de Paris (AP-HP), Pitié-Salpêtrière Hospital, Paris, France
- INSERM, Centre de Recherche Saint-Antoine (CRSA), Institute of Cardiometabolism and Nutrition (ICAN), Sorbonne Université, Paris, France
| | - Jean Marc Lacombe
- INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Sorbonne Université, Paris, France
| | | | - Valentina Peta
- INSERM, Centre de Recherche Saint-Antoine (CRSA), Institute of Cardiometabolism and Nutrition (ICAN), Sorbonne Université, Paris, France
- Research Unit, BioPredictive, Paris, France
| | - Sepideh Akhavan
- Department of Hepato-Gastroenterology, Assistance Publique-Hôpitaux de Paris (AP-HP), Pitié-Salpêtrière Hospital, Paris, France
| | - Fabien Zoulim
- Hepatology Unit Hôpital Haut-Lévêque, Pessac, and INSERM U1053, Université Bordeaux Segalen, Bordeaux, France
| | - Victor de Ledinghen
- Department of Hepatology, Hospices civils de Lyon, Hôpital Croix Rousse, INSERM U1052, Université de Lyon, Lyon, France
| | - Didier Samuel
- Hepatology Department, AP-HP, Hospital Paul Brousse, UMR-S1193, Villejuif, Université Paris-Saclay, and Hepatinov, Villejuif, France
| | | | - Vlad Ratziu
- Department of Hepato-Gastroenterology, Assistance Publique-Hôpitaux de Paris (AP-HP), Pitié-Salpêtrière Hospital, Paris, France
- INSERM, Centre de Recherche Saint-Antoine (CRSA), Institute of Cardiometabolism and Nutrition (ICAN), Sorbonne Université, Paris, France
| | - Dominique Thabut
- Department of Hepato-Gastroenterology, Assistance Publique-Hôpitaux de Paris (AP-HP), Pitié-Salpêtrière Hospital, Paris, France
- INSERM, Centre de Recherche Saint-Antoine (CRSA), Institute of Cardiometabolism and Nutrition (ICAN), Sorbonne Université, Paris, France
| | - Chantal Housset
- INSERM, Centre de Recherche Saint-Antoine (CRSA), Institute of Cardiometabolism and Nutrition (ICAN), Sorbonne Université, Paris, France
| | - Hélène Fontaine
- Assistance Publique-Hôpitaux de Paris (AP-HP), Department of Hepato-Gastroenterology, AP-HP, Hôpital Cochin, Hepatology Department, Paris, France
| | - Stanislas Pol
- Assistance Publique-Hôpitaux de Paris (AP-HP), Department of Hepato-Gastroenterology, AP-HP, Hôpital Cochin, Hepatology Department, Paris, France
| | - Fabrice Carrat
- INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Sorbonne Université, Paris, France
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Hepatitis B Virus-Associated Hepatocellular Carcinoma. Viruses 2022; 14:v14050986. [PMID: 35632728 PMCID: PMC9146458 DOI: 10.3390/v14050986] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 05/02/2022] [Accepted: 05/03/2022] [Indexed: 02/06/2023] Open
Abstract
Hepatitis B virus (HBV) is DNA-based virus, member of the Hepadnaviridae family, which can cause liver disease and increased risk of hepatocellular carcinoma (HCC) in infected individuals, replicating within the hepatocytes and interacting with several cellular proteins. Chronic hepatitis B can progressively lead to liver cirrhosis, which is an independent risk factor for HCC. Complications as liver decompensation or HCC impact the survival of HBV patients and concurrent HDV infection worsens the disease. The available data provide evidence that HBV infection is associated with the risk of developing HCC with or without an underlying liver cirrhosis, due to various direct and indirect mechanisms promoting hepatocarcinogenesis. The molecular profile of HBV-HCC is extensively and continuously under study, and it is the result of altered molecular pathways, which modify the microenvironment and lead to DNA damage. HBV produces the protein HBx, which has a central role in the oncogenetic process. Furthermore, the molecular profile of HBV-HCC was recently discerned from that of HDV-HCC, despite the obligatory dependence of HDV on HBV. Proper management of the underlying HBV-related liver disease is fundamental, including HCC surveillance, viral suppression, and application of adequate predictive models. When HBV-HCC occurs, liver function and HCC characteristics guide the physician among treatment strategies but always considering the viral etiology in the treatment choice.
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Huang ZH, Lu GY, Qiu LX, Zhong GH, Huang Y, Yao XM, Liu XH, Huang SJ, Wu T, Yuan Q, Wang YB, Su YY, Zhang J, Xia NS. Risk of hepatocellular carcinoma in antiviral treatment-naïve chronic hepatitis B patients treated with entecavir or tenofovir disoproxil fumarate: a network meta-analysis. BMC Cancer 2022; 22:287. [PMID: 35300634 PMCID: PMC8930063 DOI: 10.1186/s12885-022-09413-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 03/15/2022] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Long-term antiviral treatments are associated with a significantly lower hepatocellular carcinoma (HCC) incidence in chronic hepatitis B (CHB) patients by reducing HBV DNA concentrations. However, it is still controversial whether antiviral strategies affect HCC development in antiviral treatment-naïve CHB patients. This study aimed to estimate the incidence of HCC in antiviral treatment-naïve CHB patients who were treated with Entecavir (ETV) and Tenofovir Disoproxil Fumarate (TDF) and compare the efficacy of two treatment regimens in HCC reduction. METHODS The PubMed, Embase, China National Knowledge Infrastructure, and Wanfang databases were systematically searched until June 24, 2021. The pooled incidence and 95% confidence interval of HCC were calculated by the Freeman-Tukey double arcsine transformation method. The efficacies of ETV and TDF treatments in HCC reduction were compared through a network meta-analysis. RESULTS A total of 27 studies were identified as eligible for this systematic review. The incidence densities in the ETV and TDF treatment groups were 2.78 (95% CI: 2.21-3.40) and 2.59 (95% CI: 1.51-3.96) per 100 persons-year among patients with preexisting cirrhosis and 0.49 (95% CI: 0.32-0.68) and 0.30 (95% CI: 0.06-0.70) per 100 persons-year among patients without preexisting cirrhosis. As the proportion of CHB patients with preexisting cirrhosis increased, the incidence density of HCC also increased gradually. Compared with other Nucleos(t)ide analogs (NAs) treatments, ETV and TDF treatments significantly lowered the risk of HCC, with hazard ratios (HRs) of 0.60 (95% CI: 0.40-0.90) and 0.56 (95% CI: 0.35-0.89), respectively. However, there was no difference in the incidence density of HCC between ETV and TDF treatments (HR = 0.92, 95% CI: 0.71-1.20) regardless of preexisting cirrhosis. CONCLUSION ETV and TDF treatments were associated with significantly lower risks of HCC than other NAs treatments. However, no difference was observed between ETV and TDF treatments in the risk of HCC development regardless of preexisting cirrhosis among treatment-naïve CHB patients.
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Affiliation(s)
- Ze-Hong Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Gui-Yang Lu
- The First Affiliated Hospital of Xiamen University, Xiamen, 361003, Fujian, China
| | - Ling-Xian Qiu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Guo-Hua Zhong
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Yue Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Xing-Mei Yao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Xiao-Hui Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Shou-Jie Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Ting Wu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Quan Yuan
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Ying-Bin Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China.
| | - Ying-Ying Su
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China.
| | - Jun Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
| | - Ning-Shao Xia
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Fujian, 361102, Xiamen, China
- The Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen, 361102, Fujian, China
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Wei Y, Gong J, He X, Liu B, Liu T, Yang S, Zhou Z, Liang L, Zhan S, Xia Z, Duan G, Lin B, Han Q, Li S, Qin W, Pickhardt PJ, Deng D. An MRI-Based Radiomic Model for Individualized Prediction of Hepatocellular Carcinoma in Patients With Hepatitis B Virus-Related Cirrhosis. Front Oncol 2022; 12:800787. [PMID: 35359425 PMCID: PMC8964115 DOI: 10.3389/fonc.2022.800787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Accepted: 02/17/2022] [Indexed: 12/01/2022] Open
Abstract
Objective To develop and validate a radiomic nomogram for individualized prediction of hepatocellular carcinoma (HCC) in HBV cirrhosis patients based on baseline magnetic resonance imaging examinations and clinical data. Methods 364 patients with HBV cirrhosis from five hospitals were assigned to the training, internal validation, external validation-1 or external validation-2 cohort. All patients underwent baseline magnetic resonance image (MRI) scans and clinical follow-up within three-year time. Clinical risk factors and MRI-based features were extracted and analyzed. The radiomic signatures were built using the radiomics-score (Rad-score) that calculated for each patient as a linear weighted combination of selected MRI-based features. Prognostic performances of the clinical and radiomic nomograms were evaluated with Cox modeling in the training and validation cohorts. Results Eighteen features were selected for inclusion in the Rad-score prognostic model. The radiomic signature from multi-sequence MRI yielded a concordance index (C-index) of 0.710, 0.681, 0.632 and 0.658 in the training, internal validation, external validation-1, external validation-2 cohorts, respectively. Sex and Child-Turcotte-Pugh (CTP) class were the most prognostic clinical risk factors in univariate Cox proportional hazards analyses. The radiomic combined nomogram that integrated the radiomic signature with the clinical factors yielded a C-index of 0.746, 0.710, and 0.641 in the training, internal validation, and external validation-1 cohorts, respectively, which was an improvement over either the clinical nomogram or radiomic signature alone. Conclusion We developed an MRI-based radiomic combined nomogram with good discrimination ability for the individualized prediction of HCC in HBV cirrhosis patients within three-year time.
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Affiliation(s)
- Yichen Wei
- Department of Radiology, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Jie Gong
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Xin He
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Bo Liu
- Department of Radiology, Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Tiejun Liu
- Department of Radiology, Affiliated Hospital, Guangxi Medicine University, Liuzhou People’s Hospital, Liuzhou, China
| | - Shuohui Yang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhipeng Zhou
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin, China
| | - Lingyan Liang
- Department of Radiology, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Songhua Zhan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Ziqiang Xia
- Department of Radiology, Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Gaoxiong Duan
- Department of Radiology, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Bin Lin
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin, China
| | - Qiuli Han
- Department of Radiology, Affiliated Hospital, Guangxi Medicine University, Liuzhou People’s Hospital, Liuzhou, China
| | - Shasha Li
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Wei Qin
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China
- *Correspondence: Demao Deng, ; Wei Qin,
| | - Perry J. Pickhardt
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, United States
| | - Demao Deng
- Department of Radiology, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
- *Correspondence: Demao Deng, ; Wei Qin,
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Kubota N, Fujiwara N, Hoshida Y. Liver cancer risk-predictive molecular biomarkers specific to clinico-epidemiological contexts. Adv Cancer Res 2022; 156:1-37. [PMID: 35961696 PMCID: PMC7616039 DOI: 10.1016/bs.acr.2022.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
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.
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Affiliation(s)
- Naoto Kubota
- Liver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Naoto Fujiwara
- Liver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States; Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yujin Hoshida
- Liver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States.
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28
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Kim HY, Lampertico P, Nam JY, Lee HC, Kim SU, Sinn DH, Seo YS, Lee HA, Park SY, Lim YS, Jang ES, Yoon EL, Kim HS, Kim SE, Ahn SB, Shim JJ, Jeong SW, Jung YJ, Sohn JH, Cho YK, Jun DW, Dalekos GN, Idilman R, Sypsa V, Berg T, Buti M, Calleja JL, Goulis J, Manolakopoulos S, Janssen HLA, Jang MJ, Lee YB, Kim YJ, Yoon JH, Papatheodoridis GV, Lee JH. An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B. J Hepatol 2022; 76:311-318. [PMID: 34606915 DOI: 10.1016/j.jhep.2021.09.025] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 09/13/2021] [Accepted: 09/15/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Several models have recently been developed to predict risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). Our aims were to develop and validate an artificial intelligence-assisted prediction model of HCC risk. METHODS Using a gradient-boosting machine (GBM) algorithm, a model was developed using 6,051 patients with CHB who received entecavir or tenofovir therapy from 4 hospitals in Korea. Two external validation cohorts were independently established: Korean (5,817 patients from 14 Korean centers) and Caucasian (1,640 from 11 Western centers) PAGE-B cohorts. The primary outcome was HCC development. RESULTS In the derivation cohort and the 2 validation cohorts, cirrhosis was present in 26.9%-50.2% of patients at baseline. A model using 10 parameters at baseline was derived and showed good predictive performance (c-index 0.79). This model showed significantly better discrimination than previous models (PAGE-B, modified PAGE-B, REACH-B, and CU-HCC) in both the Korean (c-index 0.79 vs. 0.64-0.74; all p <0.001) and Caucasian validation cohorts (c-index 0.81 vs. 0.57-0.79; all p <0.05 except modified PAGE-B, p = 0.42). A calibration plot showed a satisfactory calibration function. When the patients were grouped into 4 risk groups, the minimal-risk group (11.2% of the Korean cohort and 8.8% of the Caucasian cohort) had a less than 0.5% risk of HCC during 8 years of follow-up. CONCLUSIONS This GBM-based model provides the best predictive power for HCC risk in Korean and Caucasian patients with CHB treated with entecavir or tenofovir. LAY SUMMARY Risk scores have been developed to predict the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B. We developed and validated a new risk prediction model using machine learning algorithms in 13,508 antiviral-treated patients with chronic hepatitis B. Our new model, based on 10 common baseline characteristics, demonstrated superior performance in risk stratification compared with previous risk scores. This model also identified a group of patients at minimal risk of developing HCC, who could be indicated for less intensive HCC surveillance.
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Affiliation(s)
- Hwi Young Kim
- Department of Internal Medicine, College of Medicine, Ewha Womans University, Seoul, Republic of Korea
| | - Pietro Lampertico
- Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Division of Gastroenterology and Hepatology, Milan, Italy; CRC "A. M. and A. Migliavacca" Center for Liver Disease, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Joon Yeul Nam
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Hyung-Chul Lee
- Department of Anesthesiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Seung Up Kim
- Department of Internal Medicine and Yonsei Liver Center, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dong Hyun Sinn
- Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Yeon Seok Seo
- Department of Internal Medicine, Korea University Anam Hospital, Korea University College, Republic of Korea
| | - Han Ah Lee
- Department of Internal Medicine, Korea University Anam Hospital, Korea University College, Republic of Korea; Department of Internal Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Republic of Korea
| | - Soo Young Park
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, Republic of Korea
| | - Young-Suk Lim
- Department of Internal Medicine, University of Ulsan College of Medicine, Asan Medical Centre, Seoul, Republic of Korea
| | - Eun Sun Jang
- Departments of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Republic of Korea
| | - Eileen L Yoon
- Department of Internal Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Republic of Korea; Department of Internal Medicine, Hanyang University Hospital, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Hyoung Su Kim
- Department of Internal Medicine, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea
| | - Sung Eun Kim
- Department of Internal Medicine, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang-si, Republic of Korea
| | - Sang Bong Ahn
- Department of Internal Medicine, Nowon Eulji Medical Center, Eulji University College of Medicine, Seoul, Republic of Korea
| | - Jae-Jun Shim
- Department of Internal Medicine, Kyung Hee University School of Medicine, Seoul, Republic of Korea
| | - Soung Won Jeong
- Department of Internal Medicine, Soonchunhyang University College of Medicine, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea
| | - Yong Jin Jung
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Republic of Korea
| | - Joo Hyun Sohn
- Department of Internal Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri-si, Republic of Korea
| | - Yong Kyun Cho
- Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Dae Won Jun
- Department of Internal Medicine, Hanyang University Hospital, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - George N Dalekos
- Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, General University Hospital of Larissa, Larissa, Greece
| | - Ramazan Idilman
- Department of Gastroenterology, Ankara University School of Medicine, Ankara, Turkey
| | - Vana Sypsa
- Department of Hygiene, Epidemiology & Medical Statistics, Medical School of National and Kapodistrian University of Athens, Athens, Greece
| | - Thomas Berg
- Division of Hepatology, Department of Medicine II, Leipzig University Medical Center, Leipzig, Germany
| | - Maria Buti
- Hospital General Universitario Vall Hebron and Ciberehd, Barcelona, Spain
| | | | - John Goulis
- 4th Department of Internal Medicine, Aristotle University of Thessaloniki Medical School, General Hospital of Thessaloniki "Hippokratio", Thessaloniki, Greece
| | - Spilios Manolakopoulos
- 2nd Department of Internal Medicine, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Hippokratio", Athens, Greece
| | - Harry L A Janssen
- Liver Clinic, Toronto Western & General Hospital, University Health Network, Toronto, ON, Canada
| | - Myoung-Jin Jang
- Medical Research Collaboration Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yun Bin Lee
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yoon Jun Kim
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jung-Hwan Yoon
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - George V Papatheodoridis
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greece.
| | - Jeong-Hoon Lee
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
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Comparative performance of risk prediction models for hepatitis B-related hepatocellular carcinoma in the United States. J Hepatol 2022; 76:294-301. [PMID: 34563579 PMCID: PMC8786210 DOI: 10.1016/j.jhep.2021.09.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 08/24/2021] [Accepted: 09/03/2021] [Indexed: 01/29/2023]
Abstract
BACKGROUND & AIMS Guidelines recommend hepatocellular carcinoma (HCC) surveillance in patients with chronic HBV infection. Several HCC risk prediction models are available to guide surveillance decisions, but their comparative performance remains unclear. METHODS Using a retrospective cohort of patients with HBV treated with nucleos(t)ide analogues at 130 Veterans Administration facilities between 9/1/2008 and 12/31/2018, we calculated risk scores from 10 HCC risk prediction models (REACH-B, PAGE-B, m-PAGE-B, CU-HCC, HCC-RESCUE, CAMD, APA-B, REAL-B, AASL-HCC, RWS-HCC). We estimated the models' discrimination and calibration. We calculated HCC incidence in risk categories defined by the reported cut-offs for all models. RESULTS Of 3,101 patients with HBV (32.2% with cirrhosis), 47.0% were treated with entecavir, 40.6% tenofovir, and 12.4% received both. During a median follow-up of 4.5 years, 113 patients developed HCC at an incidence of 0.75/100 person-years. AUC values for 3-year HCC risk were the highest for RWS-HCC, APA-B, REAL-B, and AASL-HCC (all >0.80). Of these, 3 (APA-B, RWS-HCC, REAL-B) incorporated alpha-fetoprotein. AUC values for the other models ranged from 0.73 for PAGE-B to 0.79 for CAMD and HCC-RESCUE. Of the 7 models with AUC >0.75, only APA-B was poorly calibrated. In total, 10-20% of the cohort was deemed low-risk based on the published cut-offs. None of the patients in the low-risk groups defined by PAGE-B, m-PAGE-B, AASL-HCC, and REAL-B developed HCC during the study timeframe. CONCLUSION In this national cohort of US-based patients with HBV on antiviral treatment, most models performed well in predicting HCC risk. A low-risk group, in which no cases of HCC occurred within a 3-year timeframe, was identified by several models (PAGE-B, m-PAGE-B, CAMD, AASL-HCC, REAL-B). Further studies are warranted to examine whether these patients could be excluded from HCC surveillance. LAY SUMMARY Risk prediction models for hepatocellular carcinoma (HCC) in patients infected with hepatitis B virus (HBV) could guide HCC surveillance decisions. In this large cohort of US-based patients receiving treatment for HBV, most published models discriminated between those who did or did not develop HCC, although the RWS-HCC, REAL-B, and AASL-HCC performed the best. If confirmed in future studies, these models could help identify a low-risk subset of patients on antiviral treatment who could be excluded from HCC surveillance.
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Yu JH, Cho SG, Jin YJ, Lee JW. The best predictive model for hepatocellular carcinoma in patients with chronic hepatitis B infection. Clin Mol Hepatol 2021; 28:351-361. [PMID: 34823308 PMCID: PMC9293610 DOI: 10.3350/cmh.2021.0281] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 11/25/2021] [Indexed: 11/06/2022] Open
Abstract
Chronic hepatitis B (CHB) seriously threatens human health. About 820,000 deaths annually are due to related complications such as hepatitis B and hepatocellular carcinoma (HCC). Recently, the use of oral antiviral agents has significantly improved the prognosis of patients with CHB infection and reduced the risk of HCC. However, hepatitis B virus still remains a major factor in the development of HCC, raising many concerns. Therefore, numerous studies have been conducted to assess the risk of HCC in patients with CHB infection and many models have been proposed to predict the risk of developing HCC. However, as each study has different models for predicting HCC development that can be applied depending on the use of antiviral agents or the type of antiviral agents, it is necessary to properly understand characteristics of each model when using it for the evaluation of HCC in patients with CHB infection. In addition, because different variables such as host factor, viral activity, and cirrhosis are used to evaluate the risk of HCC development, it is necessary to assess the risk by carefully verifying which variables are used. Recently, studies have also evaluated the risk of HCC using risk prediction models through transient elastography and artificial intelligence (AI) system. These HCC risk predication models are also noteworthy. In this review, we aimed to compare HCC risk prediction models in patients with CHB infection reported to date to confirm variables used and specificity between each model to determine an appropriate HCC risk prediction method.
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Affiliation(s)
- Jung Hwan Yu
- Department of Internal Medicine, Inha University Hospital and School of Medicine, Incheon, South Korea
| | - Soon Gu Cho
- Department of Radiology, Inha University Hospital and School of Medicine, Incheon, South Korea
| | - Young-Joo Jin
- Department of Internal Medicine, Inha University Hospital and School of Medicine, Incheon, South Korea
| | - Jin-Woo Lee
- Department of Internal Medicine, Inha University Hospital and School of Medicine, Incheon, South Korea
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31
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Demirtas CO, Brunetto MR. Surveillance for hepatocellular carcinoma in chronic viral hepatitis: Is it time to personalize it? World J Gastroenterol 2021; 27:5536-5554. [PMID: 34588750 PMCID: PMC8433616 DOI: 10.3748/wjg.v27.i33.5536] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 04/28/2021] [Accepted: 08/02/2021] [Indexed: 02/06/2023] Open
Abstract
Surveillance with abdominal ultrasound with or without alpha-fetoprotein is recommended by clinical practice guidelines for patients who are considered to be at risk of developing hepatocellular carcinoma (HCC), including those with cirrhosis, advanced fibrosis and special subgroups of chronic hepatitis B (CHB). Application of the standard surveillance strategy to all patients with chronic liver disease (CLD) with or without cirrhosis imposes major sustainability and economic burdens on healthcare systems. Thus, a number of HCC risk scores were constructed, mainly from Asian cohorts, to stratify the HCC prediction in patients with CHB. Similarly, even if less than for CHB, a few scoring systems were developed for chronic hepatitis C patients or cirrhotic patients with CLD of different etiologies. Recently, a few newsworthy HCC-risk algorithms were developed for patients with cirrhosis using the combination of serologic HCC markers and clinical parameters. Overall, the HCC risk stratification appears at hand by several validated multiple score systems, but their optimal performance is obtained only in populations who show highly homogenous clinic-pathologic, epidemiologic, etiologic and therapeutic characteristics and this limitation poses a major drawback to their sustainable use in clinical practice. A better understanding of the dynamic process driving the progression from CLD to HCC derived from studies based on molecular approaches and genetics, epigenetics and liquid biopsy will enable the identification of new biomarkers to define the individual risk of HCC in the near future, with the possibility to achieve a real and cost/effective personalization of surveillance.
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Affiliation(s)
- Coskun Ozer Demirtas
- Department of Gastroenterology and Hepatology, Marmara University, School of Medicine, Istanbul 34854, Turkey
| | - Maurizia Rossana Brunetto
- Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa 56125, Italy
- Hepatology Unit, University Hospital of Pisa, Pisa 56125, Italy
- Biostructure and Bio-imaging Institute, National Research Council of Italy, Naples 56125, Italy
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32
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Hsu YC, Tseng CH, Huang YT, Yang HI. Application of Risk Scores for Hepatocellular Carcinoma in Patients with Chronic Hepatitis B: Current Status and Future Perspective. Semin Liver Dis 2021; 41:285-297. [PMID: 34161993 DOI: 10.1055/s-0041-1730924] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Accurate risk prediction for hepatocellular carcinoma (HCC) among patients with chronic hepatitis B (CHB) may guide treatment strategies including initiation of antiviral therapy and also inform implementation of HCC surveillance. There have been 26 risk scores developed to predict HCC in CHB patients with (n = 14) or without (n = 12) receiving antiviral treatment; all of them invariably include age in the scoring formula. Virological biomarkers of replicative activities (i.e., hepatitis B virus DNA level or hepatitis B envelope antigen status) are frequently included in the scores derived from patients with untreated CHB, whereas measurements that gauge severity of liver fibrosis and/or reserve of hepatic function (i.e., cirrhosis diagnosis, liver stiffness measurement, platelet count, or albumin) are essential components in the scores developed from treated patients. External validation is a prerequisite for clinical application but not yet performed for all scores. For the future, higher predictive accuracy may be achieved with machine learning based on more comprehensive data.
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Affiliation(s)
- Yao-Chun Hsu
- Center for Liver Diseases, E-Da Hospital, Kaohsiung, Taiwan.,School of Medicine, College of Medicine, I-Shou University, Kaohsiung, Taiwan.,Department of Medicine, Fu-Jen Catholic University Hospital, New Taipei, Taiwan.,Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan
| | - Cheng-Hao Tseng
- School of Medicine, College of Medicine, I-Shou University, Kaohsiung, Taiwan.,Division of Gastroenterology and Hepatology, E-Da Cancer Hospital, Kaohsiung, Taiwan
| | - Yen-Tsung Huang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Hwai-I Yang
- Genomics Research Center, Academia Sinica, Taipei, Taiwan.,Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan.,Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.,Biomedical Translation Research Center, Academia Sinica, Taipei, Taiwan
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Lok J, Agarwal K. Screening for Hepatocellular Carcinoma in Chronic Hepatitis B: An Update. Viruses 2021; 13:v13071333. [PMID: 34372539 PMCID: PMC8309969 DOI: 10.3390/v13071333] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 06/27/2021] [Accepted: 07/06/2021] [Indexed: 11/24/2022] Open
Abstract
(1) Background: Hepatocellular carcinoma (HCC) is an important cause of mortality in individuals with chronic hepatitis B infection, with screening of high-risk groups recommended in all major international guidelines. Our understanding of the risk factors involved has improved over time, encouraging researchers to develop models that predict future risk of HCC development. (2) Methods: A literature search of the PubMed database was carried out to identify studies that derive or validate models predicting HCC development in patients with chronic hepatitis B. Subsequently, a second literature search was carried out to explore the potential role of novel viral biomarkers in this field. (3) Results: To date, a total of 23 models have been developed predicting future HCC risk, of which 12 have been derived from cohorts of treatment-naïve individuals. Most models have been developed in Asian populations (n = 20), with a smaller number in Caucasian cohorts (n = 3). All of the models demonstrate satisfactory performance in their original derivation cohorts, but many lack external validation. In recent studies, novel viral biomarkers have demonstrated utility in predicting HCC risk in patients with chronic hepatitis B, amongst both treated and treatment-naïve patients. (4) Conclusion: Several models have been developed to predict the risk of HCC development in individuals with chronic hepatitis B infection, but many have not been externally validated outside of the Asian population. Further research is needed to refine these models and facilitate a more tailored HCC surveillance programme in the future.
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Affiliation(s)
- James Lok
- Department of Gastroenterology, St. George’s Hospital, London SW17 0QT, UK
- Correspondence:
| | - Kosh Agarwal
- Institute of Liver Studies, King’s College Hospital, London SE5 9RS, UK;
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Sachar Y, Brahmania M, Dhanasekaran R, Congly SE. Screening for Hepatocellular Carcinoma in Patients with Hepatitis B. Viruses 2021; 13:1318. [PMID: 34372524 PMCID: PMC8310362 DOI: 10.3390/v13071318] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 07/05/2021] [Accepted: 07/05/2021] [Indexed: 12/18/2022] Open
Abstract
Chronic hepatitis B (CHB) infection is a significant risk factor for developing hepatocellular carcinoma (HCC). As HCC is associated with significant morbidity and mortality, screening patients with CHB at a high risk for HCC is recommended in an attempt to improve these outcomes. However, the screening recommendations on who to screen and how often are not uniform. Identifying patients at the highest risk of HCC would allow for the best use of health resources. In this review, we evaluate the literature on screening patients with CHB for HCC, strategies for optimizing adherence to screening, and potential risk stratification tools to identify patients with CHB at a high risk of developing HCC.
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Affiliation(s)
- Yashasavi Sachar
- London Health Sciences Center, Department of Medicine, Division of Gastroenterology, Western University, London, ON N6A 5A5, Canada; (Y.S.); (M.B.)
| | - Mayur Brahmania
- London Health Sciences Center, Department of Medicine, Division of Gastroenterology, Western University, London, ON N6A 5A5, Canada; (Y.S.); (M.B.)
- Centre for Quality, Innovation and Safety, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 5W9, Canada
| | - Renumathy Dhanasekaran
- Department of Medicine, Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA 94305, USA;
| | - Stephen E. Congly
- Department of Medicine, Division of Gastroenterology and Hepatology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4Z6, Canada
- O’Brien Institute of Public Health, University of Calgary, Calgary, AB T2N 4Z6, Canada
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Guo J, Gao XS. Prediction models for development of hepatocellular carcinoma in chronic hepatitis B patients. World J Clin Cases 2021; 9:3238-3251. [PMID: 34002133 PMCID: PMC8107908 DOI: 10.12998/wjcc.v9.i14.3238] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 02/11/2021] [Accepted: 03/17/2021] [Indexed: 02/06/2023] Open
Abstract
Chronic hepatitis B (CHB)-related hepatocellular carcinoma (HCC) is a major health problem in Asian-Pacific regions. Antiviral therapy reduces, but does not completely prevent, HCC development. Thus, there is a need for accurate risk prediction to assist prognostication and decisions on the need for antiviral therapy and HCC surveillance. A few risk scores have been developed to predict the occurrence of HCC in CHB patients. Initially, the scores were derived from untreated CHB patients. With the development and extensive clinical application of nucleos(t)ide analog(s) (NA), the number of risk scores based on treated CHB patients has increased gradually. The components included in risk scores may be categorized into host factors and hepatitis B virus factors. Hepatitis activities, hepatitis B virus factors, and even liver fibrosis or cirrhosis are relatively controlled by antiviral therapy. Therefore, variables that are more dynamic during antiviral therapy have since been included in risk scores. However, host factors are more difficult to modify. Most existing scores derived from Asian populations have been confirmed to be accurate in predicting HCC development in CHB patients from Asia, while these scores have not offered excellent predictability in Caucasian patients. These findings support that more relevant variables should be considered to provide individualized predictions that are easily applied to CHB patients of different ethnicities. CHB patients should receive different intensities of HCC surveillance according to their risk category.
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Affiliation(s)
- Jiang Guo
- Department of Interventional Oncology, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Xue-Song Gao
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
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Güzelbulut F, Gökçen P, Can G, Adalı G, Değirmenci Saltürk AG, Bahadır Ö, Özdil K, Doğanay HL. Validation of the HCC-RESCUE score to predict hepatocellular carcinoma risk in Caucasian chronic hepatitis B patients under entecavir or tenofovir therapy. J Viral Hepat 2021; 28:826-836. [PMID: 33586270 DOI: 10.1111/jvh.13485] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 01/12/2021] [Accepted: 01/29/2021] [Indexed: 02/06/2023]
Abstract
The HCC-RESCUE score was developed to predict hepatocellular carcinoma (HCC) risk in Korean chronic hepatitis B (CHB) patients under entecavir therapy. We aimed to validate the HCC-RESCUE score to predict HCC risk in Caucasian CHB patients under entecavir or tenofovir therapy and to compare the predictive performance of the HCC-RESCUE score with those of the CAMD, PAGE-B and modified PAGE-B (mPAGE-B) scores. The study included 647 nucleos(t)ide analogue-naive noncirrhotic and compensated/decompensated cirrhotic patients who had received entecavir or tenofovir for ≥6 months and did not develop HCC during the first 6 months of therapy. Patients with HCC-RESCUE scores ≤64, 65-84 and ≥85 points were classified into low-, intermediate- and high-risk groups, respectively. The AUROCs of the HCC-RESCUE, CAMD, PAGE-B and mPAGE-B scores to predict HCC risk at 5 years were 0.875, 0.870, 0.866 and 0.880, and those at 10 years were 0.862, 0.845, 0.841 and 0.862, respectively (both p > .05). Cumulative HCC incidences at 5 years were 0.0%, 10.5% and 15.8%, and those at 10 years were 1.4%, 15.5% and 24.9%, respectively, in the low-, intermediate- and high-risk groups based on the HCC-RESCUE score (both log rank p < .001). In the entecavir versus tenofovir cohorts, the AUROCs of the HCC-RESCUE score to predict HCC risk at 5 and 10 years were 0.831 versus 0.898 and 0.803 versus 0.910, respectively (both p > .05). The HCC-RESCUE score accurately predicted HCC risk in Caucasian CHB patients under entecavir or tenofovir therapy. A substantial proportion of patients can be dropped from HCC surveillance by using the HCC-RESCUE score.
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Affiliation(s)
- Fatih Güzelbulut
- Department of Gastroenterology, Haydarpaşa Numune Training and Research Hospital, University of Health Sciences Turkey, Istanbul, Turkey
| | - Pınar Gökçen
- Department of Gastroenterology, Ümraniye Training and Research Hospital, University of Health Sciences Turkey, Istanbul, Turkey
| | - Güray Can
- Faculty of Medicine, Department of Gastroenterology, Abant Izzet Baysal University, Bolu, Turkey
| | - Gupse Adalı
- Department of Gastroenterology, Ümraniye Training and Research Hospital, University of Health Sciences Turkey, Istanbul, Turkey
| | - Ayça Gökçen Değirmenci Saltürk
- Department of Gastroenterology, Haydarpaşa Numune Training and Research Hospital, University of Health Sciences Turkey, Istanbul, Turkey
| | - Özgür Bahadır
- Department of Gastroenterology, Haydarpaşa Numune Training and Research Hospital, University of Health Sciences Turkey, Istanbul, Turkey
| | - Kamil Özdil
- Department of Gastroenterology, Ümraniye Training and Research Hospital, University of Health Sciences Turkey, Istanbul, Turkey
| | - Hamdi Levent Doğanay
- Department of Gastroenterology, Ümraniye Training and Research Hospital, University of Health Sciences Turkey, Istanbul, Turkey
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Papatheodoridis GV, Dalekos GN, Idilman R, Sypsa V, Van Boemmel F, Buti M, Calleja JL, Goulis J, Manolakopoulos S, Loglio A, Papatheodoridi M, Gatselis N, Veelken R, Lopez-Gomez M, Hansen BE, Savvidou S, Kourikou A, Vlachogiannakos J, Galanis K, Yurdaydin C, Esteban R, Janssen HL, Berg T, Lampertico P. Predictive performance of newer Asian hepatocellular carcinoma risk scores in treated Caucasians with chronic hepatitis B. JHEP Rep 2021; 3:100290. [PMID: 34041470 PMCID: PMC8144729 DOI: 10.1016/j.jhepr.2021.100290] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 03/23/2021] [Accepted: 03/25/2021] [Indexed: 12/22/2022] Open
Abstract
Background & Aims Recently, several risk scores for prediction of hepatocellular carcinoma (HCC) were developed in cohorts of treated Asian patients with chronic hepatitis B (CHB), but they have not been assessed in non-Asian patients. We evaluated the predictability and comparative utility of our PAGE-B and recent Asian HCC risk scores in nucleos(t)ide analogue (NA)-treated adult Caucasian patients with CHB, with or without well-documented compensated cirrhosis but not previous diagnosis of HCC. Methods We included 1,951 patients treated with entecavir/tenofovir and followed up for a median of 7.6 years. The c-statistic was used to estimate the predictability of PAGE-B, HCC-Rescue, CAMD, mPAGE-B, and AASL score for HCC development within 5 or 10 years. The low- and high-risk group cut-offs were used for estimation of negative (NPV) and positive predictive values (PPV), respectively. Results HCC developed in 103/1,951 (5.3%) patients during the first 5 years and in another 39/1,428 (2.7%) patients between years 5 and 10. The 3-, 5-, and 10-year cumulative HCC rates were 3.3%, 5.9%, and 9.6%, respectively. All scores offered good 5- and 10-year HCC prediction (c-statistic: 0.78–0.82). NPVs were always >99% (99.3–100%), whereas PPV ranged between 13% and 24%. Conclusions In NA-treated Caucasian patients with CHB including compensated cirrhosis, HCC risk scores developed in NA-treated Asian patients offer good 5- and 10-year HCC predictability, similar to that of PAGE-B. PAGE-B and mPAGE-B scores are simpler in clinical practice, as they do not require an accurate diagnosis of cirrhosis, but the addition of albumin in mPAGE-B score does not seem to offer an advantage in patients with well compensated liver disease. Lay summary Several risk scores for prediction of hepatocellular carcinoma (HCC) were recently developed in cohorts of treated Asian patients with chronic hepatitis B (CHB). In Caucasian patients with CHB treated with oral antivirals, newer Asian HCC risk scores offer good 5- and 10-year HCC predictability, similar to that of PAGE-B. For clinical practice, PAGE-B and mPAGE-B scores are simpler, as they do not require an accurate diagnosis of cirrhosis.
In treated Caucasian patients with chronic hepatitis B, newer Asian hepatocellular carcinoma risk scores offer good 5- and 10-year predictability, similar to that of PAGE-B. PAGE-B and mPAGE-B scores are simpler in clinical practice, as they do not require an accurate diagnosis of cirrhosis. The addition of albumin in mPAGE-B does not seem to offer an advantage in patients with well-compensated liver disease.
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Key Words
- ALT, alanine aminotransferase
- AUROC, area under receiver operating characteristic
- CHB, chronic hepatitis B
- Cirrhosis
- ETV, entecavir
- Entecavir
- HCC, hepatocellular carcinoma
- HR, hazard ratio
- NA, nucleos(t)ide analogue
- NPV, negative predictive value
- PPV, positive predictive value
- Prediction
- TDF, tenofovir disoproxil fumarate
- Tenofovir
- ULN, upper limit of normal
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Affiliation(s)
- George V. Papatheodoridis
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens “Laiko”, Athens, Greece
- Corresponding author. Address: Department of Gastroenterology, School of Medicine, National and Kapodistrian University of Athens, Laiko General Hospital of Athens, 17 Agiou Thoma Street, 11527 Athens, Greece. Tel: +30-2132061115, Fax: +30-2107462601
| | - George N. Dalekos
- Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, General University Hospital of Larissa, Larissa, Greece
| | - Ramazan Idilman
- Department of Gastroenterology, Ankara University School of Medicine, Ankara, Turkey
| | - Vana Sypsa
- Department of Hygiene, Epidemiology & Medical Statistics, Medical School of National and Kapodistrian University of Athens, Athens, Greece
| | - Florian Van Boemmel
- Division of Hepatology, Department of Medicine II, Leipzig University Medical Center, Leipzig, Germany
| | - Maria Buti
- Hospital General Universitario Vall Hebron and Ciberehd, Barcelona, Spain
| | | | - John Goulis
- 4th Department of Internal Medicine, Αristotle University of Thessaloniki Medical School, Thessaloniki, Greece
| | - Spilios Manolakopoulos
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens “Laiko”, Athens, Greece
- 2nd Department of Internal Medicine, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens “Hippokratio”, Athens, Greece
| | - Alessandro Loglio
- Division of Gastroenterology and Hepatology, CRC “A. M. and A. Migliavacca” Center for Liver Disease, Foundation IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Margarita Papatheodoridi
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens “Laiko”, Athens, Greece
| | - Nikolaos Gatselis
- Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, General University Hospital of Larissa, Larissa, Greece
| | - Rhea Veelken
- Division of Hepatology, Department of Medicine II, Leipzig University Medical Center, Leipzig, Germany
| | | | - Bettina E. Hansen
- Department of Gastroenterology & Hepatology, Erasmus MC University Medical Center, Rotterdam, Netherlands
- Liver Clinic, Toronto Western & General Hospital, University Health Network, Toronto, ON, Canada
| | - Savvoula Savvidou
- 4th Department of Internal Medicine, Αristotle University of Thessaloniki Medical School, Thessaloniki, Greece
| | - Anastasia Kourikou
- 2nd Department of Internal Medicine, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens “Hippokratio”, Athens, Greece
| | - John Vlachogiannakos
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens “Laiko”, Athens, Greece
| | - Kostas Galanis
- Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, General University Hospital of Larissa, Larissa, Greece
| | - Cihan Yurdaydin
- Department of Gastroenterology & Hepatology, Koc University Medical School, Istanbul, Turkey
| | - Rafael Esteban
- Hospital General Universitario Vall Hebron and Ciberehd, Barcelona, Spain
| | - Harry L.A. Janssen
- Liver Clinic, Toronto Western & General Hospital, University Health Network, Toronto, ON, Canada
| | - Thomas Berg
- Division of Hepatology, Department of Medicine II, Leipzig University Medical Center, Leipzig, Germany
| | - Pietro Lampertico
- Division of Gastroenterology and Hepatology, CRC “A. M. and A. Migliavacca” Center for Liver Disease, Foundation IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
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Wang X, Liu X, Dang Z, Yu L, Jiang Y, Wang X, Yan Z. Nucleos(t)ide Analogues for Reducing Hepatocellular Carcinoma in Chronic Hepatitis B Patients: A Systematic Review and Meta-Analysis. Gut Liver 2021. [PMID: 31158948 DOI: 10.5009/gnl18546.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Background/Aims Studies have shown that nucleos(t)ide analogue (NA) treatment can reduce the risk of hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) patients, but it is unclear which NA is most effective. We performed a meta-analysis and systematic review comparing the efficacies of NAs in CHB patients. Methods We searched literature databases for randomized controlled trials (RCTs) and observational studies that analyzed the hepatic biochemical response, virological response, seroconversion rate, drug resistance rate, and HCC incidence rate in CHB patients treated with NAs. Meta-analyses were performed with RevMan and Stata/SE software. Results Twelve cohort studies and one RCT were selected, in which entecavir (ETV), lamivudine (LAM), telbivudine (LdT), and/or tenofovir disoproxil fumarate (TDF) were evaluated in CHB patients. The meta-analysis showed that ETV was superior to LAM with regard to the HCC incidence (p<0.001), biochemical response (p=0.001), virological response (p=0.02), and drug resistance (p<0.001), and ETV was superior to LdT with regard to the virological response (p<0.001) and drug resistance (p<0.001). We found no significant difference between ETV and TDF with regard to the HCC incidence (p=0.08), biochemical response (p=0.39), virological response (p=0.31), serological conversion (p=0.38), or drug resistance (p=0.95). NA-treated patients with pre-existing cirrhosis had a 5.49 times greater incidence of HCC than those without cirrhosis (p<0.001). Conclusions ETV or TDF should be used for long-term first-line monotherapy in CHB patients according to the current guidelines. Standardized protocols are needed for future studies of ETV and TDF to facilitate conclusive comparisons. Patients with cirrhosis are at significantly elevated risk for HCC, despite the benefits of NA treatment.
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Affiliation(s)
- Xinhui Wang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Xiaoli Liu
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Zhibo Dang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Lihua Yu
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Yuyong Jiang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Xianbo Wang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Zhiyun Yan
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
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Wang X, Liu X, Dang Z, Yu L, Jiang Y, Wang X, Yan Z. Nucleos(t)ide Analogues for Reducing Hepatocellular Carcinoma in Chronic Hepatitis B Patients: A Systematic Review and Meta-Analysis. Gut Liver 2021; 14:232-247. [PMID: 31158948 PMCID: PMC7096226 DOI: 10.5009/gnl18546] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 03/12/2019] [Accepted: 04/05/2019] [Indexed: 01/10/2023] Open
Abstract
Background/Aims Studies have shown that nucleos(t)ide analogue (NA) treatment can reduce the risk of hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) patients, but it is unclear which NA is most effective. We performed a meta-analysis and systematic review comparing the efficacies of NAs in CHB patients. Methods We searched literature databases for randomized controlled trials (RCTs) and observational studies that analyzed the hepatic biochemical response, virological response, seroconversion rate, drug resistance rate, and HCC incidence rate in CHB patients treated with NAs. Meta-analyses were performed with RevMan and Stata/SE software. Results Twelve cohort studies and one RCT were selected, in which entecavir (ETV), lamivudine (LAM), telbivudine (LdT), and/or tenofovir disoproxil fumarate (TDF) were evaluated in CHB patients. The meta-analysis showed that ETV was superior to LAM with regard to the HCC incidence (p<0.001), biochemical response (p=0.001), virological response (p=0.02), and drug resistance (p<0.001), and ETV was superior to LdT with regard to the virological response (p<0.001) and drug resistance (p<0.001). We found no significant difference between ETV and TDF with regard to the HCC incidence (p=0.08), biochemical response (p=0.39), virological response (p=0.31), serological conversion (p=0.38), or drug resistance (p=0.95). NA-treated patients with pre-existing cirrhosis had a 5.49 times greater incidence of HCC than those without cirrhosis (p<0.001). Conclusions ETV or TDF should be used for long-term first-line monotherapy in CHB patients according to the current guidelines. Standardized protocols are needed for future studies of ETV and TDF to facilitate conclusive comparisons. Patients with cirrhosis are at significantly elevated risk for HCC, despite the benefits of NA treatment.
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Affiliation(s)
- Xinhui Wang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Xiaoli Liu
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Zhibo Dang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Lihua Yu
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Yuyong Jiang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Xianbo Wang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Zhiyun Yan
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
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Stratification of Hepatocellular Carcinoma Risk Following HCV Eradication or HBV Control. J Clin Med 2021; 10:jcm10020353. [PMID: 33477752 PMCID: PMC7832303 DOI: 10.3390/jcm10020353] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/07/2021] [Accepted: 01/13/2021] [Indexed: 12/18/2022] Open
Abstract
Hepatocellular carcinoma (HCC) incidence has dramatically decreased in patients infected with HCV and HBV due to the widespread use of highly effective antiviral agents. Nevertheless, a substantial proportion of patients with advanced fibrosis or cirrhosis following HCV clearance of in case of HBV control whatever the stage of fibrosis remains at risk of liver cancer development. Cancer predictors in these virus-free patients include routine parameters estimating coexisting comorbidities, persisting liver inflammation or function impairment, and results of non-invasive tests which can be easily combined into HCC risk scoring systems. The latter enables stratification according to various liver cancer incidences and allocation of patients into low, intermediate or high HCC risk probability groups. All international guidelines endorse lifelong surveillance of these patients using semi-annual ultrasound, with known sensibility issues. Refining HCC prediction in this growing population ultimately will trigger personalized management using more effective surveillance tools such as contrast-enhanced imaging techniques or circulating biomarkers while taking into account cost-effectiveness parameters.
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Chang JW, Lee JS, Lee HW, Kim BK, Park JY, Kim DY, Ahn SH, Seo YS, Lee HA, Kim MN, Lee YR, Hwang SG, Rim KS, Um SH, Tak WY, Kweon YO, Park SY, Kim SU. Validation of risk prediction scores for hepatocellular carcinoma in patients with chronic hepatitis B treated with entecavir or tenofovir. J Viral Hepat 2021; 28:95-104. [PMID: 33029863 DOI: 10.1111/jvh.13411] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 08/11/2020] [Accepted: 08/23/2020] [Indexed: 12/15/2022]
Abstract
Several prediction scores for the early detection of hepatocellular carcinoma (HCC) are available. We validated the predictive accuracy of age, albumin, sex, liver cirrhosis (AASL), RESCUE-B, PAGE-B and modified PAGE-B (mPAGE-B) scores in chronic hepatitis B (CHB) patients treated with entecavir (ETV) or tenofovir disoproxil fumarate (TDF). Between 2007 and 2014, 3171 patients were recruited (1645, ETV; 1517, TDF). The predictive accuracy of each prediction score was assessed. The mean age of the study population (1977 men; 1194 women) was 48.8 years. Liver cirrhosis was present in 1040 (32.8%) patients. During follow-up (median, 58.2 months), 280 (8.8%) patients developed HCC; these patients were significantly older; more likely to be male; had significantly higher proportions of liver cirrhosis, hypertension and diabetes; and had significantly higher values for the four risk scores than those who did not develop HCC (all P < .05). Older age (hazard ratio [HR] = 1.048), male sex (HR = 2.142), liver cirrhosis (HR = 3.144) and prolonged prothrombin time (HR = 2.589) were independently associated with an increased risk of HCC (all P < .05), whereas a higher platelet count (HR = 0.996) was independently associated with a decreased risk of HCC (P < .05). The predictive accuracy of AASL score was the highest for 3- and 5-year HCC predictions (areas under the curve [AUCs] = 0.818 and 0.816, respectively), followed by RESCUE-B, PAGE-B and mPAGE-B scores (AUC = 0.780-0.815 and 0.769-0.814, respectively). In conclusion, four HCC prediction scores were assessed in Korean CHB patients treated with ETV or TDF. The AASL score showed the highest predictive accuracy.
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Affiliation(s)
- Jin Won Chang
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Korea
| | - Jae Seung Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Hye Won Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Beom Kyung Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Jun Yong Park
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Do Young Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Sang Hoon Ahn
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Yeon Seok Seo
- Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Han Ah Lee
- Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Mi Na Kim
- Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, Korea
| | - Yu Rim Lee
- Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Korea
| | - Seong Gyu Hwang
- Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, Korea
| | - Kyu Sung Rim
- Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, Korea
| | - Soon Ho Um
- Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Won Young Tak
- Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Korea
| | - Young Oh Kweon
- Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Korea
| | - Soo Young Park
- Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Korea
| | - Seung Up Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Korea
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Papatheodoridis GV, Voulgaris T, Papatheodoridi M, Kim WR. Risk Scores for Hepatocellular Carcinoma in Chronic Hepatitis B: A Promise for Precision Medicine. Hepatology 2020; 72:2197-2205. [PMID: 32602980 DOI: 10.1002/hep.31440] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 05/13/2020] [Accepted: 06/15/2020] [Indexed: 02/06/2023]
Affiliation(s)
- George V Papatheodoridis
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greeces
| | - Thodoris Voulgaris
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greeces
| | - Margarita Papatheodoridi
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greeces
| | - W Ray Kim
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, CA
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Nam JY, Sinn DH, Bae J, Jang ES, Kim JW, Jeong SH. Deep learning model for prediction of hepatocellular carcinoma in patients with HBV-related cirrhosis on antiviral therapy. JHEP Rep 2020; 2:100175. [PMID: 33117971 PMCID: PMC7581930 DOI: 10.1016/j.jhepr.2020.100175] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 08/14/2020] [Accepted: 08/18/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND & AIMS Personalised risk prediction of the development of hepatocellular carcinoma (HCC) among patients with liver cirrhosis on potent antiviral therapy is important for targeted screening and individualised intervention. This study aimed to develop and validate a new model for risk prediction of HCC development based on deep learning, and to compare it with previously reported risk models. METHODS A novel deep-learning-based model was developed from a cohort of 424 patients with HBV-related cirrhosis on entecavir therapy with 2 residual blocks, including 7 layers of a neural network, and it was validated using an independent external cohort (n = 316). The deep-learning-based model was compared to 6 previously reported models (platelet, age, and gender-hepatitis B score [PAGE-B], Chinese University HCC score [CU-HCC], HCC-Risk Estimating Score in CHB patients Under Entecavir [HCC-RESCUE], age, diabetes, race, etiology of cirrhosis, sex, and severity HCC score [ADRESS-HCC], modified PAGE-B score [mPAGE], and Toronto HCC risk index [THRI]) using Harrell's concordance (c)-index. RESULTS During a median 5.2 yr of follow-up (inter-quartile range 2.8-6.9 yr), 86 patients (20.3%) developed HCC. The deep-learning-based model had a Harrell's c-index of 0.719 in the derivation cohort and 0.782 in the validation cohort. Goodness of fit was confirmed by the Hosmer-Lemeshow test (p >0.05). Moreover, this model in the validation cohort had the highest c-index among the 6 previously reported models: PAGE-B (0.570), CU-HCC (0.548), HCC-RESCUE (0.577), ADRESS-HCC (0.551), mPAGE (0.598), and THRI (0.587) (all p <0.001). The misclassification rate of this model was 23.7% (model accuracy: 76.3%) in the validation group. CONCLUSIONS The deep-learning-based model had better performance than the previous models for predicting the HCC risk in patients with HBV-related cirrhosis on potent antivirals. LAY SUMMARY For early detection of hepatocellular carcinoma, it is important to maintain regular surveillance. However, there is currently no standard prediction model for risk stratification that can be used to establish a personalised surveillance strategy. We develop and validate a deep-learning-based model that showed better performance than previous models.
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Key Words
- ADRESS-HCC, age, diabetes, race, etiology of cirrhosis, sex, and severity HCC score
- CU-HCC, Chinese University HCC score
- Cirrhosis
- Convolutional neural network
- HCC, hepatocellular carcinoma
- HCC-RESCUE, HCC-Risk Estimating Score in CHB patients Under Entecavir
- Hepatitis B virus
- Hepatocellular carcinoma
- PAGE-B, platelet, age, and gender-hepatitis B score
- Prediction model
- SMC, Samsung Medical Center
- SNUBH, Seoul National University Bundang Hospital
- THRI, Toronto HCC risk index
- US, ultrasonography
- c-index, concordance index
- mPAGE-B, modified platelet, age, and gender-hepatitis B score
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Affiliation(s)
- Joon Yeul Nam
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dong Hyun Sinn
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Junho Bae
- DEEPNOID Inc., Seoul, Republic of Korea
| | - Eun Sun Jang
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jin-Wook Kim
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sook-Hyang Jeong
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
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Tseng CH, Tseng CM, Wu JL, Hsu YC, El-Serag HB. Magnitude of and prediction for risk of hepatocellular carcinoma in patients with chronic hepatitis B taking entecavir or tenofovir therapy: A systematic review. J Gastroenterol Hepatol 2020; 35:1684-1693. [PMID: 32343431 DOI: 10.1111/jgh.15078] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 04/01/2020] [Accepted: 04/23/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND AND AIM Entecavir (ETV) and tenofovir disoproxil fumarate (TDF) have been shown to reduce incidence of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). This systematic review aims to evaluate the magnitude, change over time, and prediction of residual HCC risks in CHB patients treated with ETV/TDF therapy. METHODS Available literature was systematically reviewed through searches of PubMed and EMBASE databases from January 1, 2006 to September 1, 2019, to identify cohort studies that reported HCC incidence in CHB patients during ETV/TDF therapy. Studies were screened by title and abstract and then evaluated for eligibility in terms of full text. RESULTS We identified 141 studies for full-text review, and 34 were eligible for analysis. From 19 studies with data separated by cirrhosis status, the 5-year cumulative incidence of HCC was 0.5-6.9% in patients without cirrhosis, 4.5-21.6% in compensated cirrhosis, and 36.3-46.5% in decompensated cirrhosis. All four studies that addressed temporal changes in HCC risks consistently found the incidence rate decreased over time in patients with cirrhosis, although the findings were inconsistent in patients without cirrhosis. Six predictive scores were developed and validated to predict incident HCC during ETV/TDF therapy in CHB patients. Common scoring variables included age, sex, cirrhosis (fibrosis grade), and hepatic function. Conflicting results were reported in seven individual studies and two meta-analyses that compared ETV versus TDF. CONCLUSIONS The residual risk of HCC remains during ETV/TDF treatment in CHB patients with cirrhosis but declines over time. Risk stratification is attainable by validated predictive scores.
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Affiliation(s)
- Cheng-Hao Tseng
- Division of Gastroenterology and Hepatology, E-DA Cancer Hospital/I-Shou University, Kaohsiung, Taiwan.,Center for Liver Diseases and Division of Gastroenterology and Hepatology, E-DA Hospital/I-Shou University, Kaohsiung, Taiwan
| | - Chao-Ming Tseng
- Division of Gastroenterology and Hepatology, E-DA Cancer Hospital/I-Shou University, Kaohsiung, Taiwan.,Center for Liver Diseases and Division of Gastroenterology and Hepatology, E-DA Hospital/I-Shou University, Kaohsiung, Taiwan
| | - Jia-Ling Wu
- Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Yao-Chun Hsu
- Division of Gastroenterology and Hepatology, E-DA Cancer Hospital/I-Shou University, Kaohsiung, Taiwan.,Center for Liver Diseases and Division of Gastroenterology and Hepatology, E-DA Hospital/I-Shou University, Kaohsiung, Taiwan.,School of Medicine, College of Medicine, I-Shou University, Kaohsiung, Taiwan
| | - Hashem B El-Serag
- Michael E. DeBakey Veterans Affairs Medical Center and Section of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine Houston, Houston, Texas, USA
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Voulgaris T, Papatheodoridi M, Lampertico P, Papatheodoridis GV. Clinical utility of hepatocellular carcinoma risk scores in chronic hepatitis B. Liver Int 2020; 40:484-495. [PMID: 31884726 DOI: 10.1111/liv.14334] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 11/28/2019] [Accepted: 12/15/2019] [Indexed: 02/06/2023]
Abstract
BACKGROUND Several risk scores have been recently developed to predict hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) patients. We systematically assessed the performance of the available HCC risk scores. METHODS Literature search was performed to identify all published studies reporting development or external validation of HCC risk scores in CHB patients. RESULTS Until March 2019, 12 scores were developed in untreated Asian and 7 scores in treated Asian (n = 6) or Caucasian (n = 1) patients. All scores provided significant predictions for HCC development in the derivation and validation cohorts of their original studies (c-statistic: 0.76-0.95) and usually classified patients into low, medium and high HCC risk groups. Eleven independent studies and three studies developing their own scores have validated externally some scores in Asian (GAG-HCC:5, CU-HCC:6, REACH-B:6, REACH-Bm:4, LSM-HCC:3, PAGE-B:5) or Caucasian/mixed origin patients (GAG-HCC:4, CU-HCC:4, REACH-B:4, PAGE-B:2). All scores offered acceptable predictability in almost all independent Asian cohorts (c-statistic: 0.70-0.86), but only PAGE-B and recently modified PAGE-B (mPAGE-B) offered good predictability in all independent Caucasian and/or Asian cohorts. Negative predictive values for 5-year HCC prediction were ≤99% (95%-99%) in most independent cohorts assessing Asian risk scores and 99%-100% in all independent cohorts (Caucasian/mixed origin:2; Asian:3) assessing PAGE-B and/or recently mPAGE-B. CONCLUSIONS Direct comparison of the newest HCC risk scores in independent patient cohorts of different origin remains intriguing, although statistical associations may not be directly transferable to clinical practice. PAGE-B and recently mPAGE-B score seem to offer persistently high predictability for Caucasian and/or Asian treated patients with low HCC risk who require no surveillance.
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Affiliation(s)
- Thodoris Voulgaris
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greece
| | - Margarita Papatheodoridi
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greece
| | - Pietro Lampertico
- Division of Gastroenterology and Hepatology, CRC "A. M. and A. Migliavacca" Center for the Study of Liver Disease, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Università degli Studi di Milano, Milan, Italy
| | - George V Papatheodoridis
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greece
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Kim SU, Seo YS, Lee HA, Kim MN, Kim EH, Kim HY, Lee YR, Lee HW, Park JY, Kim DY, Ahn SH, Han KH, Hwang SG, Rim KS, Um SH, Tak WY, Kweon YO, Kim BK, Park SY. Validation of the CAMD Score in Patients With Chronic Hepatitis B Virus Infection Receiving Antiviral Therapy. Clin Gastroenterol Hepatol 2020; 18:693-699.e1. [PMID: 31252188 DOI: 10.1016/j.cgh.2019.06.028] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 05/29/2019] [Accepted: 06/16/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Researchers previously developed a scoring system to determine the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B virus (HBV) infection, based on the presence of cirrhosis, patient age, male sex, and diabetes (called the CAMD scoring system). We validated the CAMD scoring system and compared its performance with that of other risk assessment models in an independent cohort. METHODS We followed up 3277 patients with chronic HBV infection (mean age, 48.7 y; 62.6% male; 32.4% with cirrhosis) who were treated with entecavir (n = 1725) or tenofovir (n = 1552) as the first-line antiviral agent in 4 academic teaching hospitals in the Republic of Korea. The primary outcome was development of HCC. We evaluated the ability of the CAMD, PAGE-B, and mPAGE-B scoring systems to identify patients who would develop HCC using integrated area under the curve (iAUC) analysis. RESULTS Over a median follow-up period of 58.2 months, 8.9% of the patients developed HCC. Patients who developed HCC were older, more likely to be male, and had higher proportions of cirrhosis and diabetes than patients who did not develop HCC (all P < .05). CAMD scores identified patients who developed HCC with an iAUC of 0.790, mPAGE-B scores with an iAUC of 0.769, and PAGE-B scores with an iAUC of 0.760. The 5-year cumulative risks of HCC were 1.3% in patients with low CAMD scores (<8), 8.0% in patients with intermediate CAMD scores (8-13), and 24.3% in patients with high CAMD scores (>13) (P < .001 for comparison of low- vs intermediate-score groups and between intermediate- vs high-score groups). The predicted and observed probabilities of HCC had excellent agreement. CONCLUSIONS We validated the CAMD scoring system in determining the risk of HCC in patients with chronic HBV treatment receiving entecavir or tenofovir treatment. Validation was performed in a cohort of patients in the Republic of Korea, where most patients have genotype C2 HBV infection.
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Affiliation(s)
- Seung Up Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea; Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Yeon Seok Seo
- Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea
| | - Han Ah Lee
- Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea
| | - Mi Na Kim
- Department of Internal Medicine, CHA Bundang Medical Center, Cha University, Seongnam, Republic of Korea
| | - Eun Hwa Kim
- Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Ha Yan Kim
- Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yu Rim Lee
- Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Republic of Korea
| | - Hye Won Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Jun Yong Park
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea; Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Do Young Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea; Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Sang Hoon Ahn
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea; Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Kwang-Hyub Han
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea; Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea
| | - Seong Gyu Hwang
- Department of Internal Medicine, CHA Bundang Medical Center, Cha University, Seongnam, Republic of Korea
| | - Kyu Sung Rim
- Department of Internal Medicine, CHA Bundang Medical Center, Cha University, Seongnam, Republic of Korea
| | - Soon Ho Um
- Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea
| | - Won Young Tak
- Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Republic of Korea
| | - Young Oh Kweon
- Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Republic of Korea
| | - Beom Kyung Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Republic of Korea; Yonsei Liver Center, Severance Hospital, Seoul, Republic of Korea.
| | - Soo Young Park
- Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Republic of Korea.
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Liao Y. Obstacles and opportunities in the prevention and treatment of HBV-related hepatocellular carcinoma. Genes Dis 2020; 7:291-298. [PMID: 32884983 PMCID: PMC7452511 DOI: 10.1016/j.gendis.2019.12.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 12/31/2019] [Indexed: 12/25/2022] Open
Abstract
Despite the tremendous progresses toward our understanding of the mechanisms of how liver cancer was developed, the therapeutic outcomes of liver cancer in the clinic have very limited improvement within the past three decades or so. In addition, both the incidence and mortality of liver cancer worldwide are not dropping, but increasing steadily, in the last decade. Thus, it is time for us to rethink what has been wrong and how could we do better in the upcoming years, in order to achieve our goal of improving the therapeutic outcomes of patients with liver cancer in the clinic, and at the meantime, effectively reducing the incidence of liver cancer by blocking malignant transformation of hepatocytes from chronic viral infection. This is also one of the main reasons why we try to organize this special issue on primary liver cancer in the journal of Genes & Diseases. In this perspective, I will summarize the major obstacles confronted with in the prevention and management of patients with chronic hepatitis B infection and subsequent development of liver cirrhosis and liver cancer. Next, I will delineate the pitfalls and underlying mechanisms of why the current anti-viral strategies and therapeutic agents are not as effective as one expected in terms of successful reduction or prevention chronic hepatitis B infection associated liver cirrhosis and liver cancer. I will then provide my personal perspectives on potential approaches and strategies for effective prevention and management of hepatitis B-related liver cancer.
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Affiliation(s)
- Yong Liao
- Key Laboratory of Molecular Biology for Infectious Diseases, Ministry of Education, Chongqing, PR China.,Institute for Viral Hepatitis, Chongqing Medical University, Chongqing, PR China.,Department of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, PR China
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48
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Abd El Aziz MA, Sacco R, Facciorusso A. Nucleos(t)ide analogues and Hepatitis B virus-related hepatocellular carcinoma: A literature review. Antivir Chem Chemother 2020; 28:2040206620921331. [PMID: 32418480 PMCID: PMC7232045 DOI: 10.1177/2040206620921331] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Accepted: 04/01/2020] [Indexed: 01/10/2023] Open
Abstract
Hepatitis B virus is mainly considered to cause hepatocellular carcinoma which is the fourth leading cause of cancer-related mortality worldwide. Treatment of Hepatitis B virus with nucleos(t)ide analogues can decrease the progression of the disease and subsequently decreases the incidence of hepatocellular carcinoma. In this review, we have discussed the different classes of nucleos(t)ide analogues used in the treatment of Hepatitis B virus and their relationship with the development of hepatocellular carcinoma. Furthermore, we discussed the effect of treatment of Hepatitis B virus with Nucleoside analogues (NAs) before, during and after surgery, chemoembolization, radiofrequency ablation, and chemotherapy for the treatment of hepatocellular carcinoma.
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Affiliation(s)
| | - Rodolfo Sacco
- Department of Medical Sciences, Section of Gastroenterology,
University of Foggia, Foggia Italy
| | - Antonio Facciorusso
- Department of Medical Sciences, Section of Gastroenterology,
University of Foggia, Foggia Italy
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49
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Yuan G, Zhou Y, Liu J, Hu C, Huang H, Ren Y, Yu W, Guo Y, Zhang YY, Zhou Y. AFP specificity for HCC surveillance is increased by mitigating liver injury among treated chronic hepatitis B patients with elevated AFP. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2019; 12:1315-1323. [PMID: 31933945 PMCID: PMC6947068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 01/18/2019] [Indexed: 06/10/2023]
Abstract
OBJECTIVE The aim of this study was to assess AFP response in chronic hepatitis B (CHB) patients with baseline positive AFP (≥7 ng/mL) who received antiviral therapy thereafter. METHODS A cohort study was conducted to assess AFP response in CHB patients who had baseline positive AFP and got antiviral therapy. RESULTS This retrospective study enrolled 302 antiviral-treatment-naïve CHB patients with positive AFP. After a 12-month antiviral treatment, 144 patients normalized AFP during follow-up while the rest remained AFP-positive. There were no significant differences in baseline characteristics and virologic and ALT responses to antiviral therapy between the two groups. During a mean follow-up of 34 ± 6 months, 16 patients (5.3%) in this cohort developed HCC, and 14 (8.9%) of them emerged in the AFP positive group. There was a significant difference (P=0.004) in HCC occurrence between AFP normalized and non-normalized groups after treatment. Univariate and multivariate analyses revealed that cirrhosis (HR=9.983, 95% CI=3.609-27.617, P<0.001), and non-AFP response to antiviral treatment (HR=6.517, 95% CI=1.475-28.784, P=0.013) were two independent factors associated with HCC occurrence. CONCLUSIONS To our knowledge, this is the first investigator-initiated cohort study to assess the performance of on-treatment AFP in CHB patients with baseline positive AFP. In contrast to the criticism that AFP is neither sensitive nor specific, the current study has provided important evidence that on-antiviral-treatment AFP normalization is a specific protective marker for HCC in patients with HBV-related chronic liver diseases who started antiviral therapy thereafter.
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Affiliation(s)
- Guosheng Yuan
- Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical UniversityGuangzhou, China
| | - Yuchen Zhou
- Department of Hepatobiliary Surgery, TCM-Integrated Cancer Center, Southern Medical UniversityGuangzhou, China
| | - Junwei Liu
- Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical UniversityGuangzhou, China
| | - Chengguang Hu
- Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical UniversityGuangzhou, China
| | - Huaping Huang
- Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical UniversityGuangzhou, China
| | - Yanyu Ren
- Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical UniversityGuangzhou, China
| | - Wenxuan Yu
- Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical UniversityGuangzhou, China
| | - Yabin Guo
- Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical UniversityGuangzhou, China
| | | | - Yuanping Zhou
- Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical UniversityGuangzhou, China
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Additional role of liver stiffness measurement in stratifying residual hepatocellular carcinoma risk predicted by serum biomarkers in chronic hepatitis B patients under antiviral therapy. Eur J Gastroenterol Hepatol 2018; 30:1447-1452. [PMID: 30063482 DOI: 10.1097/meg.0000000000001226] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND The risk of hepatocellular carcinoma (HCC) remains among patients who are treated with antiviral therapy (AVT). The degree of liver fibrosis has been suggested as an important biomarker to stratify the risk of developing HCC. We tested whether liver stiffness (LS) measured using transient elastography is useful over two noninvasive serum biomarkers of fibrosis [the aspartate aminotransferase to platelet ratio index (APRI) and fibrosis-4 (FIB-4)]. PATIENTS AND METHODS A retrospective cohort of 1014 CHB patients who were under AVT with nucleos(t)ide analogs for at least a year was analyzed. The risk of HCC development according to serum biomarkers (APRI and FIB-4) and LS was compared. RESULTS The HCC risk was higher for those with a higher degree of liver fibrosis, as estimated by the LS, APRI, and FIB-4. When the two serum biomarkers were used to group the patients, the 3-year HCC incidence rates were 7.3, 3.0, and 1.3% for both high APRI (≥0.5) and FIB-4 (≥1.45) scores, either a high APRI or FIB-4 score, and both low APRI and FIB-4 scores, respectively (P<0.001). Among the 758 patients with discordant or both low APRI and FIB-4 scores, the LS value was high (>6) for a significant proportion of the patients (39.9%). The HCC risk was significantly different according to the LS value (3-year HCC incidence rate of 1.1, 2.0, and 6.8% for LS <6, 6-9, and >9, respectively, P<0.001). CONCLUSION Among CHB patients under AVT, LS could stratify risk for HCC, including patients with discordant or both low APRI and FIB-4 score. This finding indicates that LS measurement plays an additional role over the serum biomarkers in stratifying the residual risk of HCC.
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