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Li Z, Hong Q, Li K. Nomogram predicting survival in patients with lymph node-negative hepatocellular carcinoma based on the SEER database and external validation. Eur J Gastroenterol Hepatol 2024; 36:904-915. [PMID: 38652516 PMCID: PMC11136272 DOI: 10.1097/meg.0000000000002756] [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: 12/08/2023] [Accepted: 02/19/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND The relationship between lymph node (LN) status and survival outcome in hepatocellular carcinoma (HCC) is a highly controversial topic. The aim of this study was to investigate the prognostic factors in patients without LN metastasis (LNM) and to construct a nomogram to predict cancer-specific survival (CSS) in this group of patients. METHODS We screened 6840 eligible HCC patients in the Surveillance, Epidemiology and End Results(SEER)database between 2010 and 2019 and randomized them into a training cohort and an internal validation cohort, and recruited 160 patients from Zhongnan Hospital of Wuhan University as an external validation cohort. Independent prognostic factors obtained from univariate and multivariate analysis were used to construct a nomogram prediction model. The concordance index (C-index), area under curve (AUC), calibration plots and decision curve analysis (DCA) were used to assess the predictive power and clinical application of the model. RESULTS Univariate and multivariate analysis revealed age, gender, bone metastasis, lung metastasis, AFP, T stage, surgery and chemotherapy as independent prognostic factors. The C-index of the constructed nomogram for the training cohort, internal validation cohort and external validation cohort are 0.746, 0.740, and 0.777, respectively. In the training cohort, the AUC at 1-, 3-, and 5-year were 0.81, 0.800, and 0.800, respectively. Calibration curves showed great agreement between the actual observations and predictions for the three cohorts. The DCA results suggest that the nomogram model has more clinical application potential. CONCLUSION We constructed a nomogram to predict CSS in HCC patients without LNM. The model has been internally and externally validated to have excellent predictive performance and can help clinicians determine prognosis and make treatment decisions.
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Affiliation(s)
- Ziqiang Li
- Department of Hepatobiliary and Pancreatic Surgery, Hubei Provincial Clinical Medicine Research Center for Minimally Invasive Diagnosis and Treatment of Hepatobiliary and Pancreatic Diseases, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Qingyong Hong
- Department of Hepatobiliary and Pancreatic Surgery, Hubei Provincial Clinical Medicine Research Center for Minimally Invasive Diagnosis and Treatment of Hepatobiliary and Pancreatic Diseases, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Kun Li
- Department of Hepatobiliary and Pancreatic Surgery, Hubei Provincial Clinical Medicine Research Center for Minimally Invasive Diagnosis and Treatment of Hepatobiliary and Pancreatic Diseases, Zhongnan Hospital of Wuhan University, Wuhan, China
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Zhang J, Jiang S, Li M, Xue H, Zhong X, Li S, Peng H, Liang J, Liu Z, Rao S, Chen H, Cao Z, Gong Y, Chen G, Zhang R, Zhang L. Head-to-head comparison of 18F-FAPI and 18F-FDG PET/CT in staging and therapeutic management of hepatocellular carcinoma. Cancer Imaging 2023; 23:106. [PMID: 37899452 PMCID: PMC10614420 DOI: 10.1186/s40644-023-00626-y] [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: 08/12/2023] [Accepted: 10/19/2023] [Indexed: 10/31/2023] Open
Abstract
BACKGROUND Fluorine 18 (18F) fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) has limitations in staging hepatocellular carcinoma (HCC). The recently introduced 18F-labeled fibroblast-activation protein inhibitor (FAPI) has shown promising prospects in detection of HCC lesions. This study aimed to investigate the initial staging and restaging performance of 18F-FAPI PET/CT compared to 18F-FDG PET/CT in HCC. METHODS This prospective study enrolled histologically confirmed HCC patients from March 2021 to September 2022. All patients were examined with 18F-FDG PET/CT and 18F-FAPI PET/CT within 1 week. The maximum standard uptake value (SUVmax), tumor-to-background ratio (TBR), and diagnostic accuracy were compared between the two modalities. RESULTS A total of 67 patients (57 men; median age, 57 [range, 32-83] years old) were included. 18F-FAPI PET showed higher SUVmax and TBR values than 18F-FDG PET in the intrahepatic lesions (SUVmax: 6.7 vs. 4.3, P < 0.0001; TBR: 3.9 vs. 1.7, P < 0.0001). In diagnostic performance, 18F-FAPI PET/CT had higher detection rate than 18F-FDG PET/CT in intrahepatic lesions [92.2% (238/258) vs 41.1% (106/258), P < 0.0001] and lymph node metastases [97.9% (126/129) vs 89.1% (115/129), P = 0.01], comparable in distant metastases [63.6% (42/66) vs 69.7% (46/66), P > 0.05]. 18F-FAPI PET/CT detected primary tumors in 16 patients with negative 18F-FDG, upgraded T-stages in 12 patients and identified 4 true positive findings for local recurrence than 18F-FDG PET, leading to planning therapy changes in 47.8% (32/67) of patients. CONCLUSIONS 18F-FAPI PET/CT identified more primary lesions, lymph node metastases than 18F-FDG PET/CT in HCC, which is helpful to improve the clinical management of HCC patients. TRIAL REGISTRATION Clinical Trials, NCT05485792 . Registered 1 August 2022, Retrospectively registered.
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Affiliation(s)
- Jing Zhang
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
- Department of Nuclear Medicine, the First Affiliated Hospital of Guangzhou Medical University, No.28 Qiaozhong Road, Guangzhou, Guangdong, 510163, P. R. China
| | - Shuqin Jiang
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
| | - Mengsi Li
- Department of Radiology, the Third Affiliated Hospital of Sun Yat-Sen University, No.600, Tianhe Road, Guangzhou, Guangdong, 510630, P. R. China
| | - Haibao Xue
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
| | - Xi Zhong
- Department of Radiology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, Guangdong, 510095, P. R. China
| | - Shuyi Li
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
| | - Hao Peng
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
| | - Jiuceng Liang
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
| | - Zhidong Liu
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
| | - Songquan Rao
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
| | - Haipeng Chen
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
| | - Zewen Cao
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China
| | - Yuanfeng Gong
- Department of Hepatobiliary Surgery, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, Guangdong, 510095, P. R. China
| | - Guoshuo Chen
- Department of Interventional Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, Guangdong, 510095, P. R. China
| | - Rusen Zhang
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China.
| | - Linqi Zhang
- Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou, 510095, People's Republic of China.
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Wang X, Zhao M, Zhang C, Chen H, Liu X, An Y, Zhang L, Guo X. Establishment and Clinical Application of the Nomogram Related to Risk or Prognosis of Hepatocellular Carcinoma: A Review. J Hepatocell Carcinoma 2023; 10:1389-1398. [PMID: 37637500 PMCID: PMC10460189 DOI: 10.2147/jhc.s417123] [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: 04/13/2023] [Accepted: 08/17/2023] [Indexed: 08/29/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most prevalent primary liver malignancy, accounting for approximately 90% of all primary liver cancers, with high mortality and a poor prognosis. A large number of predictive models have been applied that integrate multiple clinical factors and biomarkers to predict the prognosis of HCC. Nomograms, as easy-to-use prognostic predictive models, are widely used to predict the probability of clinical outcomes. We searched PubMed with the keywords "hepatocellular carcinoma" and "nomogram", and 974 relative literatures were retrieved. According to the construction methodology and the real validity of the nomograms, in this study, 97 nomograms for HCC were selected in 77 publications. These 97 nomograms were established based on more than 100,000 patients, covering seven main prognostic outcomes. The research data of 56 articles are from hospital-based HCC patients, and 13 articles provided external validation results of the nomogram. In addition to AFP, tumor size, tumor number, stage, vascular invasion, age, and other common prognostic risk factors are included in the HCC-related nomogram, more and more biomarkers, including gene mRNA expression, gene polymorphisms, and gene signature, etc. were also included in the nomograms. The establishment, assessment and validation of these nomograms are also discussed in depth. This study would help clinicians construct and select appropriate nomograms to guide precise judgment and appropriate treatments.
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Affiliation(s)
- Xiangze Wang
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, 475004, People’s Republic of China
| | - Minghui Zhao
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, 475004, People’s Republic of China
| | - Chensheng Zhang
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, 475004, People’s Republic of China
| | - Haobo Chen
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, 475004, People’s Republic of China
| | - Xingyu Liu
- School of Computer and Information Engineering, Henan University, Kaifeng, 475004, People’s Republic of China
| | - Yang An
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, 475004, People’s Republic of China
| | - Lu Zhang
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, 475004, People’s Republic of China
| | - Xiangqian Guo
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, 475004, People’s Republic of China
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Diagnosis of Metastatic Lymph Nodes in Patients With Hepatocellular Carcinoma Using Dual-Energy Computed Tomography. J Comput Assist Tomogr 2022; 47:00004728-990000000-00109. [PMID: 36573327 DOI: 10.1097/rct.0000000000001429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
OBJECTIVE Our study aimed to investigate the role of quantitative parameters derived from dual-energy computed tomography (DECT) in discriminating metastatic from nonmetastatic lymph nodes in hepatocellular carcinoma (HCC). METHODS Forty-two patients (34 males; mean age, 53.7 years) with HCC underwent unenhanced computed tomography scans and triple-phase DECT scans of the upper abdomen. A total of 72 suspected lymph nodes were resected, including 43 nonmetastatic and 29 metastatic lymph nodes. The maximum short-axis diameter of the lymph nodes, iodine concentration, normalized iodine concentration (NIC), and slope of the spectral curve were analyzed for the HCC primary lesions and the suspected lymph nodes. Lymph node metastasis was confirmed by pathologic examination. RESULTS A maximum short-axis diameter of >10 mm had a sensitivity and a specificity of 75.9% (22/29) and 53.5% (23/43) in diagnosing metastatic lymph nodes. The iodine concentration, NIC, and slope of the spectral curve of the nonmetastatic lymph nodes were significantly higher than those of the primary HCC lesions and the metastatic lymph nodes (all P < 0.05). Among all the analyzed spectral parameters, the NIC in the arterial phase had the highest sensitivity and specificity of 88.4% and 86.2% in diagnosing metastatic lymph nodes. CONCLUSIONS The arterial phase NIC of DECT has superior diagnostic performance than the traditional lymph node size in diagnosing metastatic lymph nodes in HCC.
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Zhang H, Du X, Dong H, Xu W, Zhou P, Liu S, Qing X, Zhang Y, Yang M, Zhang Y. Risk factors and predictive nomograms for early death of patients with advanced hepatocellular carcinoma: a large retrospective study based on the SEER database. BMC Gastroenterol 2022; 22:348. [PMID: 35854221 PMCID: PMC9297630 DOI: 10.1186/s12876-022-02424-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 07/12/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is a kind of tumor with high invasiveness, and patients with advanced HCC have a higher risk of early death. The aim of the present study was to identify the risk factors of early death in patients with advanced HCC and establish predictive nomograms. METHODS Death that occurred within 3 months of initial diagnosis is defined as early death. Patients diagnosed with stage IV HCC between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results database for model establishment and verification. Univariable and multivariable logistic regression analyses were used to identify the risk factors. Predictive nomograms were constructed and an internal validation was performed. Decision curve analysis (DCA) was used to verify the true clinical application value of the models. RESULTS Of 6603 patients (57% age > 60, 81% male, 70% white, 46% married), 21% and 79% had stage IVA and IVB, respectively. On the multivariable analyses, risk factors for early deaths in patients with stage IVA were age, tumor size, histological grade, alpha-fetoprotein (AFP), fibrosis score, tumor stage (T stage), surgery, radiotherapy, and chemotherapy, and that in stage IVB were age, histological grade, AFP, T stage, node stage (N stage), bone metastasis, lung metastasis, surgery, radiotherapy, and chemotherapy. The areas under the curves (AUCs) were 0.830 (95% CI 0.809-0.851) and 0.789 (95% CI 0.768-0.810) in stage IVA and IVB, respectively. Nomograms comprising risk factors with the concordance indexes (C-indexes) were 0.820 (95% CI 0.799-0.841) in stage IVA and 0.785 (95% CI 0.764-0.0.806) in stage IVB for internal validation (Bootstrapping, 1000re-samplings). The calibration plots of the nomograms show that the predicted early death was consistent with the actual value. The results of the DCA analysis show that the nomograms had a good clinical application. CONCLUSION The nomograms can be beneficial for clinicians in identifying the risk factors for early death of patients with advanced HCC and predicting the probability of early death, so as to allow for individualized treatment plans to be accurately selected.
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Affiliation(s)
- Haidong Zhang
- Medical School, Southeast University, Nanjing, China
| | - Xuanlong Du
- Medical School, Southeast University, Nanjing, China
| | - Hui Dong
- Medical School, Southeast University, Nanjing, China
| | - Wenjing Xu
- Medical School, Southeast University, Nanjing, China
| | | | - Shiwei Liu
- Medical School, Southeast University, Nanjing, China
| | - Xin Qing
- Medical School, Southeast University, Nanjing, China
| | - Yu Zhang
- Medical School, Southeast University, Nanjing, China
| | - Meng Yang
- Department of Ultrasound, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Yewei Zhang
- Hepatopancreatobiliary Center, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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Chen X, Lu Y, Shi X, Han G, Zhang L, Ni C, Zhao J, Gao Y, Wang X. Epidemiological and Clinical Characteristics of Five Rare Pathological Subtypes of Hepatocellular Carcinoma. Front Oncol 2022; 12:864106. [PMID: 35463333 PMCID: PMC9026181 DOI: 10.3389/fonc.2022.864106] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 03/14/2022] [Indexed: 12/14/2022] Open
Abstract
BackgroundHepatocellular carcinoma (HCC) is a highly heterogeneous tumor with several rare pathological subtypes and which is still poorly understood. This study aimed to describe the epidemiological and clinical spectrum of five rare HCC subtypes and develop a competing risk nomogram for cancer-specific survival prediction.MethodsThe study cohort was recruited from the Surveillance, Epidemiology, and End Results database. The clinicopathological data of 50,218 patients histologically diagnosed with classic HCC and five rare subtypes (ICD-O-3 Histology Code = 8170/3-8175/3) between 2004 and 2018 were reviewed. The annual percent change (APC) was calculated utilizing Joinpoint regression. The nomogram was developed based on multivariable competing risk survival analyses. Akaike information criterion, Bayesian information criterion, C-index, calibration curve, and area under the receiver operating characteristic curve were obtained to evaluate the prognostic performance. A decision curve analysis was introduced to examine the clinical value of the models.ResultsDespite scirrhous carcinoma, which showed a decreasing trend (APC = -6.8%, P = 0.025), the morbidity of other rare subtypes remained stable from 2004 to 2018. The incidence-based mortality was plateau in all subtypes during the period. Clear cell carcinoma is the most common subtype (n = 551, 1.1%), followed by subtypes of fibrolamellar (n = 241, 0.5%), scirrhous (n = 82, 0.2%), spindle cell (n = 61, 0.1%), and pleomorphic (n = 17, ~0%). The patients with fibrolamellar carcinoma were younger and more likely to have a non-cirrhotic liver and better prognoses. Scirrhous carcinoma shared almost the same macro-clinical characteristics and outcomes as the classic HCC. Clear cell carcinoma tended to occur in the Asia-Pacific elderly male population, and more than half of them were large HCC (Size>5cm). Sarcomatoid (including spindle cell and pleomorphic) carcinoma was associated with a larger tumor size, poorer differentiation, and more dismal prognoses. The pathological subtype, T stage, M stage, surgery, alpha-fetoprotein, and cancer history were confirmed as the independent predictors in patients with rare subtypes. The nomogram showed good calibration, discrimination, and net benefits in clinical practice.ConclusionThe rare subtypes had unique clinicopathological features and biological behaviors compared with the classic HCC. Our findings could provide a valuable reference for clinicians. The constructed nomogram could predict the prognoses with good performance, which is meaningful to individualized management.
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Affiliation(s)
- Xiaoyuan Chen
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
- NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing Medical University, Nanjing, China
- School of Medicine, Southeast University, Nanjing, China
| | - Yiwei Lu
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
- NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing Medical University, Nanjing, China
| | - Xiaoli Shi
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
- NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing Medical University, Nanjing, China
- School of Medicine, Southeast University, Nanjing, China
| | - Guoyong Han
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
- NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing Medical University, Nanjing, China
| | - Long Zhang
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
- NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing Medical University, Nanjing, China
| | - Chuangye Ni
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
- NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing Medical University, Nanjing, China
| | - Jie Zhao
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
- NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing Medical University, Nanjing, China
- Department of General Surgery, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China
| | - Yun Gao
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
- NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing Medical University, Nanjing, China
- *Correspondence: Xuehao Wang, ; Yun Gao,
| | - Xuehao Wang
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
- NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing Medical University, Nanjing, China
- School of Medicine, Southeast University, Nanjing, China
- *Correspondence: Xuehao Wang, ; Yun Gao,
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