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Li SQ, Yang CX, Wu CM, Cui JJ, Wang JN, Yin XP. Prediction of glypican-3 expression in hepatocellular carcinoma using multisequence magnetic resonance imaging-based histology nomograms. Quant Imaging Med Surg 2024; 14:4436-4449. [PMID: 39022267 PMCID: PMC11250339 DOI: 10.21037/qims-24-111] [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: 01/17/2024] [Accepted: 05/11/2024] [Indexed: 07/20/2024]
Abstract
Background Hepatocellular carcinoma (HCC) is often associated with the overexpression of multiple proteins and genes. For instance, patients with HCC and a high expression of the glypican-3 (GPC3) gene have a poor prognosis, and noninvasive assessment of GPC3 expression before surgery is helpful for clinical decision-making. Therefore, our primary aim in this study was to develop and validate multisequence magnetic resonance imaging (MRI) radiomics nomograms for predicting the expression of GPC3 in individuals diagnosed with HCC. Methods We conducted a retrospective analysis of 143 patients with HCC, including 123 cases from our hospital and 20 cases from The Cancer Genome Atlas (TCGA) or The Cancer Imaging Archive (TCIA) public databases. We used preoperative multisequence MRI images of the patients for the radiomics analysis. We extracted and screened the imaging histologic features using fivefold cross-validation, Pearson correlation coefficient, and the least absolute shrinkage and selection operator (LASSO) analysis method. We used logistic regression (LR) to construct a radiomics model, developed nomograms based on the radiomics scores and clinical parameters, and evaluated the predictive performance of the nomograms using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Results Our multivariate analysis results revealed that tumor morphology (P=0.015) and microvascular (P=0.007) infiltration could serve as independent predictors of GPC3 expression in patients with HCC. The nomograms integrating multisequence radiomics radiomics score, tumor morphology, and microvascular invasion had an area under the curve (AUC) value of 0.989. This approach was superior to both the radiomics model (AUC 0.979) and the clinical model (AUC 0.793). The sensitivity, specificity, and accuracy of 0.944, 0.800, and 0.913 for the test set, respectively, and the model's calibration curve demonstrated good consistency (Brier score =0.029). The decision curve analysis (DCA) indicated that the nomogram had a higher net clinical benefit for predicting the expression of GPC3. External validation of the model's prediction yielded an AUC value of 0.826. Conclusions Our study findings highlight the close association of multisequence MRI imaging and radiomic features with GPC3 expression. Incorporating clinical parameters into nomograms can offer valuable preoperative insights into tailoring personalized treatment plans for patients diagnosed with HCC.
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Affiliation(s)
- Si-Qi Li
- Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China
- College of Clinical Medical of Hebei University, Baoding, China
- Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China
| | - Cun-Xia Yang
- Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China
- College of Clinical Medical of Hebei University, Baoding, China
- Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China
| | - Chun-Mei Wu
- Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China
- College of Clinical Medical of Hebei University, Baoding, China
- Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China
| | - Jing-Jing Cui
- United Imaging Intelligence (Beijing) Co., Ltd., Beijing, China
| | - Jia-Ning Wang
- Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China
- College of Clinical Medical of Hebei University, Baoding, China
- Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China
| | - Xiao-Ping Yin
- Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China
- College of Clinical Medical of Hebei University, Baoding, China
- Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China
- College of Nursing of Hebei University, Baoding, China
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2
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Lee SY, Nah BKY, Leo J, Koh JH, Huang DQ. Optimizing care of HBV infection and HBV-related HCC. Clin Liver Dis (Hoboken) 2024; 23:e0169. [PMID: 38911998 PMCID: PMC11192014 DOI: 10.1097/cld.0000000000000169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/04/2024] [Indexed: 06/25/2024] Open
Affiliation(s)
- Shi Yan Lee
- Department of Medicine, Division of Gastroenterology and Hepatology, National University Hospital, Singapore, Singapore
| | - Benjamin Kai Yi Nah
- Department of Medicine, Division of Gastroenterology and Hepatology, National University Hospital, Singapore, Singapore
| | - Jazleen Leo
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jia Hong Koh
- Department of Medicine, Division of Gastroenterology and Hepatology, National University Hospital, Singapore, Singapore
| | - Daniel Q. Huang
- Department of Medicine, Division of Gastroenterology and Hepatology, National University Hospital, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- National University Centre for Organ Transplantation, National University Health System, Singapore
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3
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Chun HS, Papatheodoridis GV, Lee M, Lee HA, Kim YH, Kim SH, Oh YS, Park SJ, Kim J, Lee HA, Kim HY, Kim TH, Yoon EL, Jun DW, Ahn SH, Sypsa V, Yurdaydin C, Lampertico P, Calleja JL, Janssen HLA, Dalekos GN, Goulis J, Berg T, Buti M, Kim SU, Kim YJ. PAGE-B incorporating moderate HBV DNA levels predicts risk of HCC among patients entering into HBeAg-positive chronic hepatitis B. J Hepatol 2024; 80:20-30. [PMID: 37734683 DOI: 10.1016/j.jhep.2023.09.011] [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: 02/26/2023] [Revised: 07/31/2023] [Accepted: 09/05/2023] [Indexed: 09/23/2023]
Abstract
BACKGROUND & AIMS Recent studies reported that moderate HBV DNA levels are significantly associated with hepatocellular carcinoma (HCC) risk in hepatitis B e antigen (HBeAg)-positive, non-cirrhotic patients with chronic hepatitis B (CHB). We aimed to develop and validate a new risk score to predict HCC development using baseline moderate HBV DNA levels in patients entering into HBeAg-positive CHB from chronic infection. METHODS This multicenter cohort study recruited 3,585 HBeAg-positive, non-cirrhotic patients who started antiviral treatment with entecavir or tenofovir disoproxil fumarate at phase change into CHB from chronic infection in 23 tertiary university-affiliated hospitals of South Korea (2012-2020). A new HCC risk score (PAGED-B) was developed (training cohort, n = 2,367) based on multivariable Cox models. Internal validation using bootstrap sampling and external validation (validation cohort, n = 1,218) were performed. RESULTS Sixty (1.7%) patients developed HCC (median follow-up, 5.4 years). In the training cohort, age, gender, platelets, diabetes and moderate HBV DNA levels (5.00-7.99 log10 IU/ml) were independently associated with HCC development; the PAGED-B score (based on these five predictors) showed a time-dependent AUROC of 0.81 for the prediction of HCC development at 5 years. In the validation cohort, the AUROC of PAGED-B was 0.85, significantly higher than for other risk scores (PAGE-B, mPAGE-B, CAMD, and REAL-B). When stratified by the PAGED-B score, the HCC risk was significantly higher in high-risk patients than in low-risk patients (sub-distribution hazard ratio = 8.43 in the training and 11.59 in the validation cohorts, all p <0.001). CONCLUSIONS The newly established PAGED-B score may enable risk stratification for HCC at the time of transition into HBeAg-positive CHB. IMPACT AND IMPLICATIONS In this study, we developed and validated a new risk score to predict hepatocellular carcinoma (HCC) development in patients entering into hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB) from chronic infection. The newly established PAGED-B score, which included baseline moderate HBV DNA levels (5-8 log10 IU/ml), improved on the predictive performance of prior risk scores. Based on a patient's age, gender, diabetic status, platelet count, and moderate DNA levels (5-8 log10 IU/ml) at the phase change into CHB from chronic infection, the PAGED-B score represents a reliable and easily available risk score to predict HCC development during the first 5 years of antiviral treatment in HBeAg-positive patients entering into CHB. With a scoring range from 0 to 12 points, the PAGED-B score significantly differentiated the 5-year HCC risk: low <7 points and high ≥7 points.
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Affiliation(s)
- Ho Soo Chun
- Department of Internal Medicine, Ewha Womans University College of Medicine, Seoul, Korea; Department of Internal Medicine, Ewha Womans University Medical Center, Seoul, Korea
| | - George V Papatheodoridis
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greece
| | - Minjong Lee
- Department of Internal Medicine, Ewha Womans University College of Medicine, Seoul, Korea; Department of Internal Medicine, Ewha Womans University Medical Center, Seoul, Korea.
| | - Hye Ah Lee
- Clinical Trial Center, Ewha Womans University Seoul Hospital, Seoul, Korea
| | - Yeong Hwa Kim
- Department of Internal Medicine, Ewha Womans University College of Medicine, Seoul, Korea
| | - Seo Hyun Kim
- Department of Internal Medicine, Ewha Womans University College of Medicine, Seoul, Korea
| | - Yun-Seo Oh
- Department of Internal Medicine, Ewha Womans University College of Medicine, Seoul, Korea
| | - Su Jin Park
- Department of Internal Medicine, Ewha Womans University College of Medicine, Seoul, Korea
| | - Jihye Kim
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Han Ah Lee
- Department of Internal Medicine, Ewha Womans University College of Medicine, Seoul, Korea; Department of Internal Medicine, Ewha Womans University Medical Center, Seoul, Korea
| | - Hwi Young Kim
- Department of Internal Medicine, Ewha Womans University College of Medicine, Seoul, Korea; Department of Internal Medicine, Ewha Womans University Medical Center, Seoul, Korea
| | - Tae Hun Kim
- Department of Internal Medicine, Ewha Womans University College of Medicine, Seoul, Korea; Department of Internal Medicine, Ewha Womans University Medical Center, Seoul, Korea
| | - Eileen L Yoon
- Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Korea
| | - Dae Won Jun
- Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Korea
| | - Sang Hoon Ahn
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea; Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Vana Sypsa
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greece
| | - Cihan Yurdaydin
- Department of Gastroenterology & Hepatology, Koc University Medical School, Istanbul, Turkey
| | - 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
| | | | - Harry LA Janssen
- Department of Gastroenterology & Hepatology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - 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
| | - John Goulis
- 4th Department of Internal Medicine, Αristotle University of Thessaloniki Medical School, Thessaloniki, 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
| | - Seung Up Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea; Yonsei Liver Center, Severance Hospital, Seoul, Korea.
| | - Yoon Jun Kim
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea.
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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: 0] [Impact Index Per Article: 0] [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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5
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Jin L, Zhang X, Fan M, Li W, Zhang X. NamiRNA-mediated high expression of KNSTRN correlates with poor prognosis and immune infiltration in hepatocellular carcinoma. Contemp Oncol (Pozn) 2023; 27:163-175. [PMID: 38239867 PMCID: PMC10793618 DOI: 10.5114/wo.2023.133507] [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: 09/04/2023] [Accepted: 11/12/2023] [Indexed: 01/22/2024] Open
Abstract
Introduction Mutations of kinetochore-localized astrin/sperm-associated antigen 5 (KNSTRN) can interfere with chromatid cohesion, increase aneuploidy in tumours, and enhance tumourigenesis. However, the role of the KNSTRN-binding protein in hepatocellular carcinoma (HCC) remains unclear. Material and methods Using The Cancer Genome Atlas databases, we investigated the potential oncogenic functions of KNSTRN in HCC along with R and various computational tools. Results Detailed results revealed that elevated expression of KNSTRN was considerably associated with poor overall survival (HR = 1.48, 95% CI: 1.05-2.09, p = 0.027) and progress-free interval (HR = 1.41, 95% CI: 1.05-1.89, p = 0.021) in HCC. Gene ontology/Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis showed that KNSTRN is closely related to organelle fission, chromosomal region, tubulin binding, and cell cycle signalling pathway. TIMER database analysis showed the correlations between KNSTRN expression and tumour-infiltrating immune cells, biomarkers of immune cells, and immune checkpoint expression. Moreover, the KNSTRN level was significantly positively associated with immunosuppressive cells in the tumour microenvironment, including regulatory T-cells, myeloid-derived suppressor cells, and cancer-associated fibrocytes. Finally, a possible nuclear activating miRNA (NamiRNA)-enhancer network of hsa-miR-107, which activates the KNSTRN expression in liver hepatocellular carcinoma, was constructed by correlation analysis. Conclusions NamiRNA-mediated upregulation of KNSTRN correlated with poor prognosis and tumour immune infiltration in HCC. KNSTRN could serve as an effective biomarker for the diagnosis and prognosis of HCC and support the development of novel therapeutic strategies.
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Affiliation(s)
- Liang Jin
- Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Xiaojing Zhang
- Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Ming Fan
- Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Weimin Li
- Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Xuan Zhang
- Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
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6
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Huang DQ, Singal AG, Kanwal F, Lampertico P, Buti M, Sirlin CB, Nguyen MH, Loomba R. Hepatocellular carcinoma surveillance - utilization, barriers and the impact of changing aetiology. Nat Rev Gastroenterol Hepatol 2023; 20:797-809. [PMID: 37537332 DOI: 10.1038/s41575-023-00818-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/30/2023] [Indexed: 08/05/2023]
Abstract
Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. Surveillance for HCC is critical for early detection and treatment, but fewer than one-quarter of individuals at risk of HCC undergo surveillance. Multiple failures across the screening process contribute to the underutilization of surveillance, including limited disease awareness among patients and health-care providers, knowledge gaps, and difficulty recognizing patients who are at risk. Non-alcoholic fatty liver disease and alcohol-associated liver disease are the fastest-rising causes of HCC-related death worldwide and are associated with unique barriers to surveillance. In particular, more than one-third of patients with HCC related to non-alcoholic fatty liver disease do not have cirrhosis and therefore lack a routine indication for HCC surveillance on the basis of current practice guidelines. Semi-annual abdominal ultrasound with measurement of α-fetoprotein levels is recommended for HCC surveillance, but the sensitivity of this approach for early HCC is limited, especially for patients with cirrhosis or obesity. In this Review, we discuss the current status of HCC surveillance and the remaining challenges, including the changing aetiology of liver disease. We also discuss strategies to improve the utilization and quality of surveillance for HCC.
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Affiliation(s)
- Daniel Q Huang
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Health System, Singapore, Singapore.
| | - Amit G Singal
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Fasiha Kanwal
- Center for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
- Section of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
| | - 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
| | - Maria Buti
- Liver Unit, Department of Internal Medicine, Hospital Universitari Valle d'Hebron, Vall d'Hebron Barcelona Hospital Campus, Universitat Autònoma de Barcelona, Barcelona, Spain
- CIBER-EHD del Instituto Carlos III, Barcelona, Spain
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, UCSD School of Medicine, San Diego, CA, USA
| | - Mindie H Nguyen
- Department of Epidemiology and Population Health, Stanford University Medical Center, Stanford University, Palo Alto, CA, USA
- Division of Gastroenterology and Hepatology, Stanford University Medical Center, Stanford University, Palo Alto, CA, USA
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology and Hepatology, University of California at San Diego, San Diego, CA, USA
- Division of Epidemiology, Department of Family Medicine and Public Health, University of California at San Diego, San Diego, CA, USA
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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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8
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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: 1.0] [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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9
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Lee HA, Kim SU, Seo YS, Ahn SH, Rim CH. Comparable outcomes between immune-tolerant and active phases in noncirrhotic chronic hepatitis B: a meta-analysis. Hepatol Commun 2023; 7:e0011. [PMID: 36691962 PMCID: PMC9851695 DOI: 10.1097/hc9.0000000000000011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 10/10/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Antiviral therapy is not indicated for patients with chronic hepatitis B (CHB) in the immune-tolerant (IT) phase. We compared the outcomes between the untreated IT phase and the treated immune-active (IA) phase in noncirrhotic HBeAg-positive CHB patients. METHODS We systematically searched 4 databases, including PubMed, Medline, Embase, and Cochrane, until August 2021. The pooled incidence rates of HCC and mortality in the IT and IA cohorts and phase change in the IT cohort were investigated. Studies that included patients with liver cirrhosis were excluded. RESULTS Thirteen studies involving 11,903 patients were included. The overall median of the median follow-up period was 62.4 months. The pooled 5-year and 10-year incidence rates of HCC were statistically similar between the IT and IA cohorts (1.1%, 95% CI: 0.4%-2.8% vs. 1.1%, 95% CI: 0.5%-2.3%, and 2.7%, 95% CI: 1.0%-7.3% vs. 3.6%, 95% CI: 2.4%-5.5%, respectively, all p>0.05). The pooled 5-year odds ratio of HCC between IT and IA cohorts was 1.05 (95% CI: 0.32-3.45; p=0.941). The pooled 5-year incidence rate of mortality was statistically similar between the IT and IA cohorts (1.9%, 95% CI: 1.1%-3.4% vs. 1.0%, 95% CI: 0.3%-2.9%, p=0.285). Finally, the pooled 5-year incidence rate of phase change in the IT cohort was 36.1% (95% CI: 29.5%-43.2%). CONCLUSION The pooled incidence rates of HCC and mortality were comparable between the untreated IT and the treated IA phases in noncirrhotic HBeAg-positive CHB patients.
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Affiliation(s)
- Han Ah Lee
- Department of Internal Medicine, College of Medicine, Ewha Womans University, Seoul, Korea
| | - Seung Up Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Yeon Seok Seo
- Departments of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Sang Hoon Ahn
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
- Yonsei Liver Center, Severance Hospital, Seoul, Korea
| | - Chai Hong Rim
- Department of Radiation Oncology, Korea University College of Medicine, Seoul, Korea
- Department of Radiation Oncology, Korea University Ansan Hospital, Gyeonggi-do, Korea
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Mao HD, Zheng SQ, Yang SH, Huang ZY, Xue Y, Zhou M. A new model predicts hepatocellular carcinoma in patients with HBV-related decompensated liver cirrhosis and long-term antiviral therapy: a prospective study. PeerJ 2023; 11:e15014. [PMID: 36992940 PMCID: PMC10042153 DOI: 10.7717/peerj.15014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 02/16/2023] [Indexed: 03/31/2023] Open
Abstract
Background We aimed to evaluate the prediction values of non-invasive models for hepatocellular carcinoma (HCC) development in patients with HBV-related liver cirrhosis (LC) and long-term NA treatment. Methods Patients with compensated or decompensated cirrhosis (DC), who achieved long-term virological response, were enrolled. DC and its stages were defined by the complications including ascites, encephalopathy, variceal bleeding, or renal failure. Prediction accuracy of several risk scores, including ALBI, CAMD, PAGE-B, mPAGE-B and aMAP, was compared. Results The median follow-up duration was 37 (28-66) months. Among the 229 patients, 9 (9.57%) patients in the compensated LC group and 39 (28.89%) patients in the DC group developed HCC. The incidence of HCC was higher in the DC group ( X 2 = 12.478, P < 0.01). The AUROC of ALBI, aMAP, CAMD, PAGE-B and mPAGE-B scores were 0.512, 0.667, 0.638, 0.663, 0.679, respectively. There was no significant difference in AUROC between CAMD, aMAP, PAGE-B and mPAGE-B (all P > 0.05). Univariable analysis showed that age, DC status and platelet were associated with HCC development, and multivariable analysis showed that age and DC status (both P < 0.01) were independent risk factors for HCC development, then Model (Age_DC) was developed and its AUROC was 0.718. Another model, Model (Age_DC_PLT_TBil) consisting of age, DC stage, PLT, TBil was also developed, and its AUROC was larger than that of Model (Age_DC) (0.760 vs. 0.718). Moreover, AUROC of Model (Age_DC_PLT_TBil) was larger than the other five models (all P < 0.05). With an optimal cut-off value of 0.236, Model (Age_DC_PLT_TBil) achieved 70.83% sensitivity, 76.24% specificity. Conclusion There is a lack of non-invasive risk scores for HCC development in HBV-related DC, and a new model consisting of age, DC stage, PLT, TBil may be an alternative.
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Affiliation(s)
- Hao-dan Mao
- Institute of Hepatology, Changzhou Third People’s Hospital, Changzhou, Jiangsu, China
- Department of Infectious Diseases, Changzhou Third People’s Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Shu-qin Zheng
- Institute of Hepatology, Changzhou Third People’s Hospital, Changzhou, Jiangsu, China
| | - Su-hua Yang
- Institute of Hepatology, Changzhou Third People’s Hospital, Changzhou, Jiangsu, China
- Department of Infectious Diseases, Changzhou Third People’s Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Ze-yu Huang
- Institute of Hepatology, Changzhou Third People’s Hospital, Changzhou, Jiangsu, China
- Department of Infectious Diseases, Changzhou Third People’s Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Yuan Xue
- Institute of Hepatology, Changzhou Third People’s Hospital, Changzhou, Jiangsu, China
- Department of Infectious Diseases, Changzhou Third People’s Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Min Zhou
- Institute of Hepatology, Changzhou Third People’s Hospital, Changzhou, Jiangsu, China
- Department of Infectious Diseases, Changzhou Third People’s Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
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Shi K, Li P, Zhang Q, Zhang Y, Bi Y, Zeng X, Wang X. Development of a nomogram to predict the risk of hepatocellular carcinoma in patients with hepatitis B-related cirrhosis on antivirals. Front Oncol 2023; 13:1128062. [PMID: 36874109 PMCID: PMC9978349 DOI: 10.3389/fonc.2023.1128062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/06/2023] [Indexed: 02/18/2023] Open
Abstract
Objective Patients with compensated hepatitis B-related cirrhosis receiving antivirals are at the risk of hepatocellular carcinoma (HCC). This study aimed to develop and validate a nomogram for predicting the incidence of HCC in patients with hepatitis-B related cirrhosis. Design A total of 632 patients with compensated hepatitis-B related cirrhosis treated with entecavir or tenofovir between August 2010 and July 2018 were enrolled. Cox regression analysis was used to identify independent risk factors for HCC and a nomogram was developed using these factors. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analyses were used to evaluate the nomogram performance. The results were validated in an external cohort (n = 324). Results In the multivariate analysis, age per 10 years, neutrophil-lymphocyte ratio > 1.6, and platelet count < 86×109/L were independent predictors of HCC occurrence. A nomogram was developed to predict HCC risk using these three factors (ranging from 0 to 20). The nomogram showed better performance (AUC: 0.83) than that of the established models (all P < 0.05). The 3-year cumulative HCC incidences in the low- (scores < 4), medium- (4-10), and high-risk (> 10) subgroups were 0.7%, 4.3%, and 17.7%, respectively, in the derivation cohort, and 1.2%, 3.9%, and 17.8%, respectively, in the validation cohort. Conclusion The nomogram showed good discrimination and calibration in estimating HCC risk in patients with hepatitis-B related cirrhosis on antivirals. High-risk patients with a score > 10 points require close surveillance.
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Affiliation(s)
- Ke Shi
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Ping Li
- Department of Hepatology, Tianjin Second People's Hospital, Tianjin, China
| | - Qun Zhang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Yi Zhang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Yufei Bi
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Xuanwei Zeng
- 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
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Suboptimal Performance of Hepatocellular Carcinoma Prediction Models in Patients with Hepatitis B Virus-Related Cirrhosis. Diagnostics (Basel) 2022; 13:diagnostics13010003. [PMID: 36611295 PMCID: PMC9818663 DOI: 10.3390/diagnostics13010003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [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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Kim BH, Cho Y, Park JW. Surveillance for hepatocellular carcinoma: It is time to move forward. Clin Mol Hepatol 2022; 28:810-813. [PMID: 36064304 PMCID: PMC9597219 DOI: 10.3350/cmh.2022.0257] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 08/30/2022] [Indexed: 01/05/2023] Open
Affiliation(s)
- Bo Hyun Kim
- Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang, Korea
| | - Yuri Cho
- Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang, Korea
| | - Joong-Won Park
- Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang, Korea,Corresponding author : Joong-Won Park Division of Gastroenterology, Department of Internal Medicine, Center for Liver and Pancreatobiliary Cancer, National Cancer Center, 323 Ilsan-ro Ilsandong-gu, Goyang 10408, Korea Tel: +82-31-920-1605, Fax: +82-31-920-1520, E-mail:
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