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Zandavi SM, Kim C, Goodwin T, Thilakanathan C, Bostanara M, Akon AC, Al Mouiee D, Barisic S, Majeed A, Kemp W, Chu F, Smith M, Collins K, Wong VWS, Wong GLH, Behary J, Roberts SK, Ng KKC, Vafaee F, Zekry A. AI-powered prediction of HCC recurrence after surgical resection: Personalised intervention opportunities using patient-specific risk factors. Liver Int 2024. [PMID: 39046171 DOI: 10.1111/liv.16050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 06/18/2024] [Accepted: 07/11/2024] [Indexed: 07/25/2024]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) recurrence following surgical resection remains a significant clinical challenge, necessitating reliable predictive models to guide personalised interventions. In this study, we sought to harness the power of artificial intelligence (AI) to develop a robust predictive model for HCC recurrence using comprehensive clinical datasets. METHODS Leveraging data from 958 patients across multiple centres in Australia and Hong Kong, we employed a multilayer perceptron (MLP) as the optimal classifier for model generation. RESULTS Through rigorous internal cross-validation, including a cohort from the Chinese University of Hong Kong (CUHK), our AI model successfully identified specific pre-surgical risk factors associated with HCC recurrence. These factors encompassed hepatic synthetic function, liver disease aetiology, ethnicity and modifiable metabolic risk factors, collectively contributing to the predictive synergy of our model. Notably, our model exhibited high accuracy during cross-validation (.857 ± .023) and testing on the CUHK cohort (.835), with a notable degree of confidence in predicting HCC recurrence within accurately classified patient cohorts. To facilitate clinical application, we developed an online AI digital tool capable of real-time prediction of HCC recurrence risk, demonstrating acceptable accuracy at the individual patient level. CONCLUSION Our findings underscore the potential of AI-driven predictive models in facilitating personalised risk stratification and targeted interventions to mitigate HCC recurrence by identifying modifiable risk factors unique to each patient. This model aims to aid clinicians in devising strategies to disrupt the underlying carcinogenic network driving recurrence.
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Affiliation(s)
- Seid Miad Zandavi
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
- UNSW Data Science Hub, University of New South Wales, Sydney, New South Wales, Australia
| | - Christy Kim
- St George and Sutherland Clinical Campuses, University of New South Wales, Sydney, New South Wales, Australia
- Department of Gastroenterology and Hepatology, St George Hospital, Sydney, New South Wales, Australia
| | - Thomas Goodwin
- Department of Gastroenterology and Hepatology, The Alfred Hospital, Melbourne, Victoria, Australia
| | - Cynthuja Thilakanathan
- St George and Sutherland Clinical Campuses, University of New South Wales, Sydney, New South Wales, Australia
- Department of Gastroenterology and Hepatology, St George Hospital, Sydney, New South Wales, Australia
| | - Maryam Bostanara
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Anna Camille Akon
- St George and Sutherland Clinical Campuses, University of New South Wales, Sydney, New South Wales, Australia
- Department of Gastroenterology and Hepatology, St George Hospital, Sydney, New South Wales, Australia
| | - Daniel Al Mouiee
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
- The Ingham Institute for Applied Medical Research, Sydney, New South Wales, Australia
| | - Sasha Barisic
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
- School of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales, Australia
| | - Ammar Majeed
- Department of Gastroenterology and Hepatology, The Alfred Hospital, Melbourne, Victoria, Australia
- Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - William Kemp
- Department of Gastroenterology and Hepatology, The Alfred Hospital, Melbourne, Victoria, Australia
- Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Francis Chu
- Department of Liver Surgery, St George Hospital, University of New South Wales, Sydney, New South Wales, Australia
| | - Marty Smith
- Department of Hepatobiliary Surgery, The Alfred Hospital, Melbourne, Victoria, Australia
| | - Kate Collins
- Department of Gastroenterology and Hepatology, The Austin Hospital, Melbourne, Victoria, Australia
| | - Vincent Wai-Sun Wong
- Medical Data Analytics Centre, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Grace Lai-Hung Wong
- Medical Data Analytics Centre, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Jason Behary
- St George and Sutherland Clinical Campuses, University of New South Wales, Sydney, New South Wales, Australia
- Department of Gastroenterology and Hepatology, St George Hospital, Sydney, New South Wales, Australia
| | - Stuart K Roberts
- Department of Gastroenterology and Hepatology, The Alfred Hospital, Melbourne, Victoria, Australia
- Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Kelvin K C Ng
- Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China
| | - Fatemeh Vafaee
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
- UNSW Data Science Hub, University of New South Wales, Sydney, New South Wales, Australia
| | - Amany Zekry
- St George and Sutherland Clinical Campuses, University of New South Wales, Sydney, New South Wales, Australia
- Department of Gastroenterology and Hepatology, St George Hospital, Sydney, New South Wales, Australia
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Yen YH, Kuo FY, Eng HL, Liu YW, Yong CC, Li WF, Wang CC, Lin CY. Tumor necrosis as a predictor of early tumor recurrence after resection in patients with hepatoma. PLoS One 2023; 18:e0292144. [PMID: 37972101 PMCID: PMC10653529 DOI: 10.1371/journal.pone.0292144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/02/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND Tumor necrosis is a significant risk factor affecting patients' prognosis after liver resection (LR) for hepatocellular carcinoma (HCC). We aimed to develop a model with tumor necrosis as a variable to predict early tumor recurrence in HCC patients undergoing LR. MATERIALS AND METHODS Patients who underwent LR between 2010 and 2018 for newly diagnosed HCC but did not receive neoadjuvant therapy were enrolled in this retrospective study. Six predictive factors based on pathological features-tumor size > 5 cm, multiple tumors, high-grade tumor differentiation, tumor necrosis, microvascular invasion, and cirrhosis-were chosen a priori based on clinical relevance to construct a multivariate logistic regression model. The variables were always retained in the model. The impact of each variable on early tumor recurrence within one year of LR was estimated and visualized using a nomogram. The nomogram's performance was evaluated using calibration plots with bootstrapping. RESULTS Early tumor recurrence was observed in 161 (21.3%) patients. The concordance index of the proposed nomogram was 0.722. The calibration plots showed good agreement between nomogram predictions and actual observations of early recurrence. CONCLUSION We developed a nomogram incorporating tumor necrosis to predict early recurrence of HCC after LR. Its predictive accuracy is satisfactory.
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Affiliation(s)
- Yi-Hao Yen
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Fang-Ying Kuo
- Department of Pathology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Hock-Liew Eng
- Department of Pathology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yueh-Wei Liu
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chee-Chien Yong
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Wei-Feng Li
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chih-Chi Wang
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chih-Yun Lin
- Biostatistics Center of Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
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Zuo D, Li Y, Liu H, Liu D, Fang Q, Li P, Tu L, Xiong Y, Zeng Y, Liu P. Value of Non-tumoral Liver Volume in the Prognosis of Large Hepatocellular Carcinoma Patients After R0 Resection. J Clin Transl Hepatol 2023; 11:560-571. [PMID: 36969888 PMCID: PMC10037504 DOI: 10.14218/jcth.2022.00170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/02/2022] [Accepted: 07/29/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND AND AIMS Hepatectomy is an effective treatment for selected patients with large hepatocellular carcinoma (HCC). This study aimed to develop a nomogram incorporating non-tumoral liver volume (non-TLV) and liver function markers to predict the patients' overall survival (OS) and disease-free survival (DFS). METHODS Data of 198 consecutive large HCC patients who underwent hepatectomy at the Zhongshan Hospital Xiamen University were collected. Another 68 patients from the Mengchao Hepatobiliary Surgery Hospital served as an external validation cohort. The nomograms were developed based on the independent prognostic factors screened by multivariate Cox regression analyses. Concordance index (C-index), calibration curves, and time-dependent receiver operating characteristic (ROC) curves were used to measure the discrimination and predictive accuracy of the models. RESULTS High HBV DNA level, low non-TLV/ICG, vascular invasion, and a poorly differentiated tumor were confirmed as independent risk factors for both OS and DFS. The model established in this study predicted 5-year post-operative survival and DFS in good agreement with the actual observation confirmed by the calibration curves. The C-indexes of the nomograms in predicting OS and DFS were 0.812 and 0.823 in the training cohort, 0.821 and 0.846 in the internal validation cohort, and 0.724 and 0.755 in the external validation cohort. The areas under the ROC curves (AUCs) of nomograms for predicted OS and DFS at 1, 3, and 5 year were 0.85, 0.86, 0.83 and 0.76, 0.76, 0.63, respectively. CONCLUSIONS Nomograms with non-TLV/ICG predicted the prognosis of single large HCC patients accurately and effectively.
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Affiliation(s)
- Dongliang Zuo
- Department of Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
| | - Yuntong Li
- Department of Hepatobiliary Surgery, Zhongshan Hospital Xiamen University, Xiamen, Fujian, China
| | - Hongzhi Liu
- Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Surgery Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Dongxu Liu
- Public Health Clinical Center of Chengdu, Chengdu, Sichuan, China
| | - Qinliang Fang
- Department of Hepatobiliary Surgery, Zhongshan Hospital Xiamen University, Xiamen, Fujian, China
| | - Pengtao Li
- Department of Hepatobiliary Surgery, Zhongshan Hospital Xiamen University, Xiamen, Fujian, China
| | - Liang Tu
- Department of Hepatobiliary Surgery, Zhongshan Hospital Xiamen University, Xiamen, Fujian, China
| | - Yu Xiong
- Department of Hepatobiliary Surgery, Zhongshan Hospital Xiamen University, Xiamen, Fujian, China
| | - Yongyi Zeng
- Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Surgery Hospital of Fujian Medical University, Fuzhou, Fujian, China
- Correspondence to: Pingguo Liu, Department of Hepatobiliary Surgery, Zhongshan Hospital Xiamen University, 201 Hubin South Rd., Xiamen, Fujian 361001, China. Tel/Fax: +86-592-2993141, E-mail: ; Yongyi Zeng, Mengchao Hepatobiliary Hospital of Fujian Medical University, Xihong Road 312, Fuzhou, Fujian 350025, China. Tel/Fax: +86-591-8370-5927, E-mail:
| | - Pingguo Liu
- Department of Hepatobiliary Surgery, Zhongshan Hospital Xiamen University, Xiamen, Fujian, China
- Correspondence to: Pingguo Liu, Department of Hepatobiliary Surgery, Zhongshan Hospital Xiamen University, 201 Hubin South Rd., Xiamen, Fujian 361001, China. Tel/Fax: +86-592-2993141, E-mail: ; Yongyi Zeng, Mengchao Hepatobiliary Hospital of Fujian Medical University, Xihong Road 312, Fuzhou, Fujian 350025, China. Tel/Fax: +86-591-8370-5927, E-mail:
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Mo ZY, Chen PY, Lin J, Liao JY. Pre-operative MRI features predict early post-operative recurrence of hepatocellular carcinoma with different degrees of pathological differentiation. LA RADIOLOGIA MEDICA 2023; 128:261-273. [PMID: 36763316 PMCID: PMC10020263 DOI: 10.1007/s11547-023-01601-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 01/24/2023] [Indexed: 02/11/2023]
Abstract
PURPOSE To investigate the value of pre-operative gadoxetate disodium (Gd-EOB-DTPA) enhanced MRI predicting early post-operative recurrence (< 2 years) of hepatocellular carcinoma (HCC) with different degrees of pathological differentiation. METHODS Retrospective analysis of pre-operative MR imaging features of 177 patients diagnosed as suffering from HCC and that underwent radical resection. Multivariate logistic regression assessment was adopted to assess predictors for HCC recurrence with different degrees of pathological differentiation. The area under the curve (AUC) of receiver operating characteristics (ROC) was utilized to assess the diagnostic efficacy of the predictors. RESULTS Among the 177 patients, 155 (87.5%) were males, 22 (12.5%) were females; the mean age was 49.97 ± 10.71 years. Among the predictors of early post-operative recurrence of highly-differentiated HCC were an unsmooth tumor margin and an incomplete/without tumor capsule (p = 0.037 and 0.033, respectively) whereas those of early post-operative recurrence of moderately-differentiated HCC were incomplete/without tumor capsule, peritumoral enhancement along with peritumoral hypointensity (p = 0.006, 0.046 and 0.004, respectively). The predictors of early post-operative recurrence of poorly-differentiated HCC were peritumoral enhancement, peritumoral hypointensity, and tumor thrombosis (p = 0.033, 0.006 and 0.021, respectively). The AUCs of the multi-predictor diagnosis of early post-operative recurrence of highly-, moderately-, and poorly-differentiated HCC were 0.841, 0.873, and 0.875, respectively. The AUCs of the multi-predictor diagnosis were each higher than for those predicted separately. CONCLUSIONS The imaging parameters for predicting early post-operative recurrence of HCC with different degrees of pathological differentiation were different and combining these predictors can improve the diagnostic efficacy of early post-operative HCC recurrence.
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Affiliation(s)
- Zhi-ying Mo
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Nanning, 530021 Guangxi People’s Republic of China
| | - Pei-yin Chen
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Nanning, 530021 Guangxi People’s Republic of China
| | - Jie Lin
- Department of Bone Surgery, Wuzhou Peopleʹs Hospital, No. 139 Sanlong Road, Wuzhou, 543000 Guangxi China
| | - Jin-yuan Liao
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Nanning, 530021 Guangxi People’s Republic of China
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Li W, Shen H, Han L, Liu J, Xiao B, Li X, Ye Z. A Multiparametric Fusion Radiomics Signature Based on Contrast-Enhanced MRI for Predicting Early Recurrence of Hepatocellular Carcinoma. JOURNAL OF ONCOLOGY 2022; 2022:3704987. [PMID: 36213823 PMCID: PMC9534653 DOI: 10.1155/2022/3704987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 07/28/2022] [Indexed: 11/18/2022]
Abstract
Objectives The postoperative early recurrence (ER) rate of hepatocellular carcinoma (HCC) is 50%, and no highly reliable predictive tool has been developed yet. The aim of this study was to develop and validate a predictive model with radiomics analysis based on multiparametric magnetic resonance (MR) images to predict early recurrence of HCC. Methods In total, 302 patients (training dataset: n = 211; validation dataset: n = 91) with pathologically confirmed HCC who underwent preoperative MR imaging were enrolled in this study. Three-dimensional regions of interest of the entire lesion were accessed by manually drawing along the tumor margins on the multiple sequences of MR images. Least absolute shrinkage and selection operator Cox regression were then applied to select ER-related radiomics features and construct radiomics signatures. Univariate analysis and multivariate Cox regression analysis were used to identify the significant clinico-radiological factors and establish a clinico-radiological model. A predictive model of ER incorporating the fusion radiomics signature and clinico-radiological risk factors was constructed. The diagnostic performance and clinical utility of this model were measured by receiver-operating characteristic (ROC), calibration curve, and decision curve analyses. Results The fusion radiomics signature consisting of 6 radiomics features achieved good prediction performance (training dataset: AUC = 0.85, validation dataset: AUC = 0.79). The predictive model of ER integrating clinico-radiological risk factors and the fusion radiomics signature improved the prediction efficacy with AUCs of 0.91 and 0.87 in the training and validation datasets, respectively. Furthermore, the nomogram and ER risk stratification system based on the predictive model demonstrated encouraging predictions of the individualized risk of ER and gave three risk groups with low, intermediate, or high risk of ER. Conclusions The proposed predictive model incorporating clinico-radiological factors and the fusion radiomics signature derived from multiparametric MR images may be an effective tool for the individualized prediction of postoperative ER in patients with HCC.
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Affiliation(s)
- Wencui Li
- Department of Radiology, Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Hongru Shen
- Tianjin Cancer Institute, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Lizhu Han
- Department of Radiology, Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jiaxin Liu
- Department of Radiology, Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Bohan Xiao
- Department of Radiology, Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Xubin Li
- Department of Radiology, Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Zhaoxiang Ye
- Department of Radiology, Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
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Long-Term Survival and Risk Factors in Patients with Hepatitis B-Related Hepatocellular Carcinoma: A Real-World Study. Can J Gastroenterol Hepatol 2022; 2022:7750140. [PMID: 36051249 PMCID: PMC9427325 DOI: 10.1155/2022/7750140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 07/01/2022] [Accepted: 07/25/2022] [Indexed: 11/17/2022] Open
Abstract
A retrospective cohort study was conducted to collect 465 patients with hepatitis B-related hepatocellular carcinoma who had undergone radical hepatectomy from January 1, 2012, to August 31, 2018, at the First Affiliated Hospital of the University of Science and Technology of China. The clinical, pathological, and follow-up information was collected to compare the basic characteristics of death and nondeath after radical resection. Kaplan-Meier curves were used for survival analysis and male and female subgroup analysis. The multivariate Cox proportional-hazards regression model was used to analyze independent risk factors related to postoperative death. Of the 465 patients with radical resection of hepatitis B-related hepatocellular carcinoma, 132 died, and 1-, 3-, and 5-year cumulative survival rates after operation were 92.1%, 78%, and 64%, respectively. In the male and female subgroup, 115 and 17 patients died, respectively. The 1-, 3-, and 5-year cumulative survival rates were 92.6%, 77.0%, and 62.6%, respectively, in men, and 89.6%, 78.8%, and 70.2%, respectively, in women. Multivariate Cox proportional-hazards regression analysis showed that microvascular invasion (MVI), Edmondson III/IV, BCLC stage B, and total bilirubin (TB) > 20.5 μmol/L were independent risk factors in patients with hepatitis B-related hepatocellular carcinoma after radical hepatectomy.
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Bae BK, Park HC, Yoo GS, Choi MS, Oh JH, Yu JI. The Significance of Systemic Inflammation Markers in Intrahepatic Recurrence of Early-Stage Hepatocellular Carcinoma after Curative Treatment. Cancers (Basel) 2022; 14:cancers14092081. [PMID: 35565210 PMCID: PMC9102776 DOI: 10.3390/cancers14092081] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 04/11/2022] [Accepted: 04/18/2022] [Indexed: 12/21/2022] Open
Abstract
Simple Summary This retrospective study using the prospectively collected registry data of newly diagnosed, previously untreated hepatocellular carcinoma (HCC) evaluates the significance of systemic inflammatory markers (SIMs) to intrahepatic recurrence (IHR) after curative treatment. Out of 4076 patients who met the inclusion criteria, 52.6% experienced IHR. SIMs, including pre-treatment platelet-to-lymphocyte ratio (PLR), post-treatment changes of neutrophil-to-lymphocyte ratio PLR, and lymphocyte-to-monocyte ratio were significantly associated with the prognosis of early-stage HCC patients who received initial curative treatment. The prognostic significances of SIMs were consistent for IHR-free survival, early and late IHR, and overall survival. Abstract Systemic inflammatory markers (SIMs) are known to be associated with carcinogenesis and prognosis of hepatocellular carcinoma (HCC). We evaluated the significance of SIMs in intrahepatic recurrence (IHR) of early-stage HCC after curative treatment. This study was performed using prospectively collected registry data of newly diagnosed, previously untreated HCC between 2005 and 2017 at a single institution. Inclusion criteria were patients with Barcelona Clinic Liver Cancer stage 0 or A, who underwent curative treatment. Pre-treatment and post-treatment values of platelet, neutrophil, lymphocyte, monocyte, neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and lymphocyte/monocyte ratio (LMR) were analyzed with previously well-known risk factors of HCC to identify factors associated with IHR-free survival (IHRFS), early IHR, and late IHR. Of 4076 patients, 2142 patients (52.6%) experienced IHR, with early IHR in 1018 patients (25.0%) and late IHR in 1124 patients (27.6%). Pre-treatment platelet count and PLR and post-treatment worsening of NLR, PLR, and LMR were independently associated with IHRFS. Pre-treatment platelet count and post-treatment worsening of NLR, PLR, and LMR were significantly related to both early and late IHR. Pre-treatment values and post-treatment changes in SIMs were significant factors of IHR in early-stage HCC, independent of previously well-known risk factors of HCC.
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Affiliation(s)
- Bong Kyung Bae
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (B.K.B.); (G.S.Y.)
| | - Hee Chul Park
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (B.K.B.); (G.S.Y.)
- Correspondence: (H.C.P.); (J.I.Y.)
| | - Gyu Sang Yoo
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (B.K.B.); (G.S.Y.)
| | - Moon Seok Choi
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (M.S.C.); (J.H.O.)
| | - Joo Hyun Oh
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (M.S.C.); (J.H.O.)
| | - Jeong Il Yu
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (B.K.B.); (G.S.Y.)
- Correspondence: (H.C.P.); (J.I.Y.)
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Zhao QY, Liu SS, Fan MX. Prediction of early recurrence of hepatocellular carcinoma after resection based on Gd-EOB-DTPA enhanced magnetic resonance imaging: a preliminary study. J Gastrointest Oncol 2022; 13:792-801. [PMID: 35557582 PMCID: PMC9086065 DOI: 10.21037/jgo-22-224] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 04/11/2022] [Indexed: 08/10/2023] Open
Abstract
BACKGROUND Early recurrence (ER) after radical resection of hepatocellular carcinoma (HCC) affects the prognosis of patients. Gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) can improve the detection rate of small HCC. This study innovatively introduces a new quantitative index combined with qualitative index to compare the differences in clinical and imaging characteristics between ER and non-ER groups and evaluate the feasibility of Gd-EOB-DTPA-enhanced MRI in predicting ER. METHODS A total of 68 patients with HCC confirmed by operation and pathology in the Shandong Cancer Hospital and Institute were included retrospectively. All participants were examined by Gd-EOB-DTPA-enhanced MRI within 3 weeks before surgery. Regular follow-up was performed every 2 months within 1 year after operation. Among them, 18 cases with new lesions were in ER group, and 50 cases without new lesions were in non-ER group. The clinical and imaging data of the 2 groups were collected, and the differences of clinical data and preoperative MRI signs between the ER group and non-ER group were compared. The predictive factors of ER after HCC were analyzed by multivariate logistic regression. RESULTS The quantitative parameter lesion-to-liver contrast enhancement ratio (LLCER) can predict the pathological grade of HCC (P=0.023). The results of univariate analysis between the ER group and non-ER group showed that there were significant differences in pathological grade (P=0.008), lesion morphology (P=0.011), peritumoral low signal intensity in hepatobiliary phase (HBP) (P<0.001), satellite nodules (P<0.001), and LLCER (P<0.001) between the 2 groups. Multivariate logistic regression analysis showed that HBP peritumoral low signal intensity [odds ratio (OR) =7.214, 95% confidence interval (CI): 1.230-42.312, P=0.029], satellite nodules (OR =9.198, 95% CI: 1.402-60.339, P=0.021), and parameter LLCER value (OR =0.906, 95% CI: 0.826-0.995, P=0.039) were independent predictors of ER of HCC after resection. CONCLUSIONS Preoperative Gd-EOB-DTPA enhanced MRI has important predictive value for early recurrence after radical resection of hepatocellular carcinoma.
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Affiliation(s)
- Qi-Yu Zhao
- Department of Radiology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Shi-Shun Liu
- Medical Imaging Department, Jinan Second People’s Hospital, Jinan, China
| | - Ming-Xin Fan
- Department of Radiology, The Third Affiliated Hospital of Shandong First Medical University (Affiliated Hospital of Shandong Academy of Medical Sciences), Jinan, China
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Weighted Gene Coexpression Network Analysis in Mouse Livers following Ischemia-Reperfusion and Extensive Hepatectomy. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2021:3897715. [PMID: 35003298 PMCID: PMC8736699 DOI: 10.1155/2021/3897715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 11/23/2021] [Indexed: 11/17/2022]
Abstract
In mouse models, the recovery of liver volume is mainly mediated by the proliferation of hepatocytes after partial hepatectomy that is commonly accompanied with ischemia-reperfusion. The identification of differently expressed genes in liver following partial hepatectomy benefits the better understanding of the molecular mechanisms during liver regeneration (LR) with appliable clinical significance. Briefly, studying different gene expression patterns in liver tissues collected from the mice group that survived through extensive hepatectomy will be of huge critical importance in LR than those collected from the mice group that survived through appropriate hepatectomy. In this study, we performed the weighted gene coexpression network analysis (WGCNA) to address the central candidate genes and to construct the free-scale gene coexpression networks using the identified dynamic different expressive genes in liver specimens from the mice with 85% hepatectomy (20% for seven-day survial rate) and 50% hepatectomy (100% for seven-day survial rate under ischemia-reperfusion condition compared with the sham group control mice). The WGCNA combined with Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses pinpointed out the apparent distinguished importance of three gene expression modules: the blue module for apoptotic process, the turquoise module for lipid metabolism, and the green module for fatty acid metabolic process in LR following extensive hepatectomy. WGCNA analysis and protein-protein interaction (PPI) network construction highlighted FAM175B, OGT, and PDE3B were the potential three hub genes in the previously mentioned three modules. This work may help to provide new clues to the future fundamental study and treatment strategy for LR following liver injury and hepatectomy.
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Beumer BR, Buettner S, Galjart B, van Vugt JLA, de Man RA, IJzermans JNM, Koerkamp BG. Systematic review and meta-analysis of validated prognostic models for resected hepatocellular carcinoma patients. Eur J Surg Oncol 2021; 48:492-499. [PMID: 34602315 DOI: 10.1016/j.ejso.2021.09.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 09/13/2021] [Accepted: 09/15/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Many prognostic models for Hepatocellular Carcinoma (HCC) have been developed to inform patients and doctors about individual prognosis. Previous reviews of these models were qualitative and did not assess performance at external validation. We assessed the performance of prognostic models for HCC and set a benchmark for biomarker studies. METHODS All externally validated models predicting survival for patients with resected HCC were systematically reviewed. After selection, we extracted descriptive statistics and aggregated c-indices using meta-analysis. RESULTS Thirty-eight validated prognostic models were included. Models used on average 7 (IQR:4-9) prognostic factors. Tumor size, tumor number, and vascular invasion were almost always included. Alpha-fetoprotein (AFP) was commonly incorporated since 2007. Recently, the more subjective items ascites and encephalopathy have been dropped. Eight established models performed poor to moderate at external validation, with a pooled C-index below 0.7; including the Barcelona Clinic Liver Cancer (BCLC) system, the American Joint Committee on Cancer (AJCC) 7th edition, the Cancer of the Liver Italian (CLIP) Program, and the Japan Integrated Staging (JIS) score. Out of 24 prognostic models predicting OS, only 6 (25%) had good performance at external validation with pooled C-indices above 0.7; the Li-post (0.77), Li-OS (0.74), Yang-pre (0.74), Yang-post (0.76), Shanghai-score (0.70), and Wang-nomogram (0.71). Models improved over time, but overall performance and study quality remained low. CONCLUSIONS Six validated prognostic models demonstrated good performance for predicting survival after resection of HCC. These models can guide patients and doctors and are a benchmark for future models incorporating novel biomarkers.
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Affiliation(s)
- Berend R Beumer
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Stefan Buettner
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Boris Galjart
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Jeroen L A van Vugt
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Robert A de Man
- Erasmus MC Transplant Institute, Department of Gastroenterology and Hepatology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Jan N M IJzermans
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Bas Groot Koerkamp
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands.
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Li WF, Yen YH, Liu YW, Wang CC, Yong CC, Lin CC, Cheng YF, Wang JH, Lu SN. Preoperative predictors of early recurrence after resection for hepatocellular carcinoma. Am J Surg 2021; 223:945-950. [PMID: 34399978 DOI: 10.1016/j.amjsurg.2021.08.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/19/2021] [Accepted: 08/09/2021] [Indexed: 02/08/2023]
Abstract
BACKGROUND To assess preoperative image tumor characteristics and alpha-fetoprotein (AFP) levels to predict early recurrence after liver resection (LR) for hepatocellular carcinoma (HCC). METHODS This retrospective study's enrolled patients underwent LR for newly diagnosed HCC between 2011 and 2018. Multivariate logistic regression analyses using the Akaike information criterion were adopted to construct a nomogram to predict early recurrence (i.e. recurrence within 1 year). The performance of this nomogram was evaluated using calibration plots with bootstrapping. RESULTS Early recurrence was identified in 99 patients (11.2%). Four predictive factors, namely an AFP level of >400 ng/mL; image-diagnosed tumor characteristics, including a tumor size of > 5 cm; vascular invasion; and multiple tumors were adopted in the final model of the early recurrence nomogram, with a concordance index of 0.67. The calibration plots showed good agreement between the nomogram predictions and the actual observations of early recurrence. CONCLUSION We have developed a simple nomogram with preoperative image tumor characteristics and AFP levels to predict the early recurrence of HCC after LR.
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Affiliation(s)
- Wei-Feng Li
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Yi-Hao Yen
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.
| | - Yueh-Wei Liu
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chih-Chi Wang
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan.
| | - Chee-Chien Yong
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chih-Che Lin
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Yu-Fan Cheng
- Liver Transplantation Center, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, 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
| | - Sheng-Nan Lu
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
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Mai RY, Zeng J, Meng WD, Lu HZ, Liang R, Lin Y, Wu GB, Li LQ, Ma L, Ye JZ, Bai T. Artificial neural network model to predict post-hepatectomy early recurrence of hepatocellular carcinoma without macroscopic vascular invasion. BMC Cancer 2021; 21:283. [PMID: 33726693 PMCID: PMC7962237 DOI: 10.1186/s12885-021-07969-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 02/24/2021] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND The accurate prediction of post-hepatectomy early recurrence (PHER) of hepatocellular carcinoma (HCC) is vital in determining postoperative adjuvant treatment and monitoring. This study aimed to develop and validate an artificial neural network (ANN) model to predict PHER in HCC patients without macroscopic vascular invasion. METHODS Nine hundred and three patients who underwent curative liver resection for HCC participated in this study. They were randomly divided into derivation (n = 679) and validation (n = 224) cohorts. The ANN model was developed in the derivation cohort and subsequently verified in the validation cohort. RESULTS PHER morbidity in the derivation and validation cohorts was 34.8 and 39.2%, respectively. A multivariable analysis revealed that hepatitis B virus deoxyribonucleic acid load, γ-glutamyl transpeptidase level, α-fetoprotein level, tumor size, tumor differentiation, microvascular invasion, satellite nodules, and blood loss were significantly associated with PHER. These factors were incorporated into an ANN model, which displayed greater discriminatory abilities than a Cox's proportional hazards model, preexisting recurrence models, and commonly used staging systems for predicting PHER. The recurrence-free survival curves were significantly different between patients that had been stratified into two risk groups. CONCLUSION When compared to other models and staging systems, the ANN model has a significant advantage in predicting PHER for HCC patients without macroscopic vascular invasion.
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Affiliation(s)
- Rong-Yun Mai
- Department of Hepatobilliary & Pancreatic Surgery, Guangxi Medical University Cancer Hospital, 71 He Di Road, Nanning, China
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, 530021, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China
| | - Jie Zeng
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, 530021, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China
| | - Wei-da Meng
- Department of Hepatobilliary & Pancreatic Surgery, Guangxi Medical University Cancer Hospital, 71 He Di Road, Nanning, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China
| | - Hua-Ze Lu
- Department of Hepatobilliary & Pancreatic Surgery, Guangxi Medical University Cancer Hospital, 71 He Di Road, Nanning, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China
| | - Rong Liang
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China
- Department of First Chemotherapy, Guangxi Medical University Cancer Hospital, Nanning, 530021, China
| | - Yan Lin
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China
- Department of First Chemotherapy, Guangxi Medical University Cancer Hospital, Nanning, 530021, China
| | - Guo-Bin Wu
- Department of Hepatobilliary & Pancreatic Surgery, Guangxi Medical University Cancer Hospital, 71 He Di Road, Nanning, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China
| | - Le-Qun Li
- Department of Hepatobilliary & Pancreatic Surgery, Guangxi Medical University Cancer Hospital, 71 He Di Road, Nanning, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China
| | - Liang Ma
- Department of Hepatobilliary & Pancreatic Surgery, Guangxi Medical University Cancer Hospital, 71 He Di Road, Nanning, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China
| | - Jia-Zhou Ye
- Department of Hepatobilliary & Pancreatic Surgery, Guangxi Medical University Cancer Hospital, 71 He Di Road, Nanning, China.
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China.
| | - Tao Bai
- Department of Hepatobilliary & Pancreatic Surgery, Guangxi Medical University Cancer Hospital, 71 He Di Road, Nanning, China.
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China.
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Ueno M, Hayami S, Kawai M, Hirono S, Okada KI, Miyazawa M, Kitahata Y, Miyamoto A, Suzaki N, Nakamura M, Yamaue H. Prognostic impact of adjuvant chemolipiodolization and treatment frequency on patients with hepatocellular carcinoma after hepatectomy: Prospective study with historical control group. Surg Oncol 2020; 36:99-105. [PMID: 33321415 DOI: 10.1016/j.suronc.2020.12.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 11/23/2020] [Accepted: 12/06/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Reducing or minimizing metastatic recurrence is a consideration in prolongation of survival of patients with hepatocellular carcinoma. We previously proposed single adjuvant chemolipiodolization (ACL) as a possible adjuvant treatment. The current study aims to further improve prognosis by performing ACL three times (sequential-ACL). METHODS We examined the prognostic impact of sequential-ACL compared with our historical cohort groups: resection alone (non-ALC) and single-ACL. We evaluated recurrence-free survival (RFS), recurrence pattern, and overall survival. Multivariate prognostic analyses were used to adjust baseline bias between three treatment groups. RESULTS Non-ACL (n = 64), single-ACL (n = 137), and sequential-ACL (n = 95) showed 40, 54, and 62% of two-year RFS rates (P = 0.03 and P = 0.007 compared with non-ACL). Recurrence pattern beyond Milan criteria was frequently observed in the non-ACL group (P = 0.003). Five-year overall survival rates of these three groups were 53, 69, and 77% (P = 0.02 and 0.002 compared with non-ACL). Single- and sequential-ACL were selected as independent favorable factors for five-year overall survival; their hazard ratios (95% confidence interval) were 0.61 (0.37-0.99) and 0.48 (0.26-0.86). However, compared with single-ACL, there was no additional prognostic effects of sequential-ACL. CONCLUSIONS Single- and sequential-ACL treatment both showed better RFS and overall survival with minimized recurrence patterns than resection alone. There was not sufficient additional benefit by sequential-ACL, however, over single-ACL. Single-ACL might therefore be appropriate as an adjuvant therapy.
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Affiliation(s)
- Masaki Ueno
- Second Department of Surgery, Wakayama Medical University, Japan.
| | - Shinya Hayami
- Second Department of Surgery, Wakayama Medical University, Japan
| | - Manabu Kawai
- Second Department of Surgery, Wakayama Medical University, Japan
| | - Seiko Hirono
- Second Department of Surgery, Wakayama Medical University, Japan
| | - Ken-Ichi Okada
- Second Department of Surgery, Wakayama Medical University, Japan
| | - Motoki Miyazawa
- Second Department of Surgery, Wakayama Medical University, Japan
| | - Yuji Kitahata
- Second Department of Surgery, Wakayama Medical University, Japan
| | - Atsushi Miyamoto
- Second Department of Surgery, Wakayama Medical University, Japan
| | - Norihiko Suzaki
- Second Department of Surgery, Wakayama Medical University, Japan
| | - Masashi Nakamura
- Second Department of Surgery, Wakayama Medical University, Japan
| | - Hiroki Yamaue
- Second Department of Surgery, Wakayama Medical University, Japan
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Fung AK, Cheng NM, Chong CC, Lee KF, Wong J, Cheung SY, Lok HT, Lai PB, Ng KK. Single-center experience on actual mid-term (≥5 years) and long-term (≥10 years) survival outcome in patients with hepatocellular carcinoma after curative hepatectomy: A bimodal distribution. Medicine (Baltimore) 2020; 99:e23358. [PMID: 33235106 PMCID: PMC7710257 DOI: 10.1097/md.0000000000023358] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Analysis for actual mid-term (≥5 years) and long-term (≥10 years) survivors with hepatocellular carcinoma (HCC) following curative hepatectomy are rarely reported in the literature.This retrospective study aims to study the mid- and long-term survival outcome and associated prognostic factors following curative hepatectomy for HCC in a tertiary referral center.The clinical data of 325 patients who underwent curative hepatectomy for HCC were reviewed. They were stratified into 3 groups for comparison (Group 1, overall survival <5 years; Group 2, overall survival ≥5, and <10 years; Group 3, overall survival ≥10 years). Favorable independent prognostic factors for mid- and long-term survival were analyzed.A bimodal distribution of actual survival outcome was observed, with short-term (<5 years) survival of 52.7% (n = 171), mid-term survival of 18.1% (n = 59), and long-term survival of 29.2% (n = 95). Absence of microvascular invasion (OR 3.690, 95% CI: 1.562-8.695) was independent good prognostic factor for mid-term survival. Regarding long-term overall survival, young age (OR 1.050, 95% CI: 0.920-0.986), ASA grade ≤2 (OR 3.746, 95% CI: 1.325-10.587), high albumin level (OR 1.008, 95% CI: 0.920-0.986), solitary tumor (OR 3.289, 95% CI: 1.149-7.625) and absence of microvascular invasion (OR 4.926, 95% CI: 2.192-11.111) were independent good prognostic factors.Curative hepatectomy results in bimodal actual survival outcome with favorable long-term survival rate of 29.2%. Favorable independent prognostic factors (age, ASA grade, albumin level, tumor number, and microvascular invasion) are identified for overall survival.
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Affiliation(s)
- Andrew K.Y. Fung
- Department of Surgery, Prince of Wales Hospital, New Territories
| | | | - Charing C.N. Chong
- Department of Surgery, Prince of Wales Hospital, New Territories
- Department of Surgery, The Chinese University of Hong Kong, Hong Kong
| | - Kit-Fai Lee
- Department of Surgery, Prince of Wales Hospital, New Territories
| | - John Wong
- Department of Surgery, Prince of Wales Hospital, New Territories
| | | | - Hon-Ting Lok
- Department of Surgery, Prince of Wales Hospital, New Territories
| | - Paul B.S. Lai
- Department of Surgery, Prince of Wales Hospital, New Territories
- Department of Surgery, The Chinese University of Hong Kong, Hong Kong
| | - Kelvin K.C. Ng
- Department of Surgery, Prince of Wales Hospital, New Territories
- Department of Surgery, The Chinese University of Hong Kong, Hong Kong
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