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Xu W, Liu F, Shen X, Li R. Prognostic Nomograms for Patients with Hepatocellular Carcinoma After Curative Hepatectomy, with a Focus on Recurrence Timing and Post-Recurrence Management. J Hepatocell Carcinoma 2020; 7:233-256. [PMID: 33154956 PMCID: PMC7606947 DOI: 10.2147/jhc.s271498] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 10/10/2020] [Indexed: 12/25/2022] Open
Abstract
Background Prognoses of patients with hepatocellular carcinoma (HCC) after curative hepatectomy remain unsatisfactory because of the high incidence of postoperative recurrence. Published predictive systems focus on pre-resection oncological characteristics, ignoring post-recurrence factors. Purpose This study aimed to develop prognostic nomograms for 3- and 5-year overall survival (OS) of patients with HCC after curative hepatectomy, focusing on potentially influential post-recurrence factors. Patients and Methods Clinicopathological and postoperative follow-up data were extracted from 494 patients with HCC who underwent curative hepatectomy between January 2012 and June 2019. Early recurrence (ER) and late recurrence (LR) were defined as recurrence at ≤2 and >2 years, respectively, after curative hepatectomy. Nomograms for the prediction of 3- and 5-year OS were established based on multivariate analysis. The areas under time-dependent receiver operating characteristic curves (AUCs) for the nomograms were calculated independently to verify predictive accuracy. The nomograms were internally validated based on 2000 bootstrap resampling of 75% of the original data. Results In total, 494 patients with HCC who underwent curative hepatectomy met the eligibility criteria. Cox proportional hazard regression analysis identified factors potentially influencing 3- and 5-year OS. Multivariate analysis indicated that patient age, Hong Kong Liver Cancer stage, γ-glutamyl transferase (γ-GGT) level, METAVIR inflammation activity grade, ER and post-recurrence treatment modality were influencing factors for 3-year OS (AUC, 0.891; 95% CI, 0.8364-0.9447). γ-GGT > 60 U/L, hepatectomy extent, LR and post-recurrence treatment modality were influencing factors for 5-year OS (AUC, 0.864; 95% CI, 0.8041-0.9237). Calibration plots showed satisfactory concordance between the predicted and actual observation cohorts. Conclusion We propose new prognostic nomograms for OS prediction with a focus on the differentiation of recurrence timing and post-recurrence management. These nomograms overcome the shortcomings of previous predictive nomograms and significantly improve predictive accuracy.
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Affiliation(s)
- Wei Xu
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, People's Republic of China
| | - Fei Liu
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, People's Republic of China
| | - Xianbo Shen
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, People's Republic of China
| | - Ruineng Li
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, People's Republic of China
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Wong L, Bozhilov K, Hernandez B, Kwee S, Chan O, Ellis L, LeMarchand L. Underlying liver disease and advanced stage liver cancer are associated with elevated neutrophil-lymphocyte ratio. Clin Mol Hepatol 2019; 25:305-316. [PMID: 31001964 PMCID: PMC6759430 DOI: 10.3350/cmh.2019.0004] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Accepted: 02/15/2019] [Indexed: 02/07/2023] Open
Abstract
Background/Aims Inflammation-based scores, such as the neutrophil-to-lymphocyte ratio (NLR), have been associated with prognosis in hepatocellular carcinoma (HCC); but variable cut-off values and potential lack of specificity have limited the utility of NLR. This study evaluates NLR in a large cohort of HCC patients. Methods We retrospectively reviewed 789 HCC cases (1993–2017) for demographics, tumor characteristics, treatment, and survival. NLR was stratified into NLR ≥1.5 and NLR ≥3 and analyzed for correlation with American Joint Committee on Cancer (AJCC) and Barcelona Clinic Liver Cancer (BCLC) stages. In 235 patients who underwent liver resection, survival and recurrence were evaluated by NLR. Results In 789 HCC cases, mean NLR was increased with advanced AJCC and BCLC stages. Hepatitis C patients were less likely to have NLR ≥1.5 and ≥3. Non-alcoholic steatohepatitis patients were more likely to have NLR ≥3. Patients with tumor size >5 cm, rupture, or macrovascular invasion were more likely to have NLR ≥3. In patients treated with resection, NLR ≥3 predicted early recurrence (odds ratio [OR] 4.14, P<0.01) and overall recurrence (OR 4.05, P<0.01). Mean NLR was 4.30 in those with recurrence and 2.75 in those without recurrence. Patients with NLR ≥3 showed significantly worse survival compared to those with NLR <3 (P<0.01 by log-rank test). Conclusions Elevated NLR is associated with advanced cancer stage and aggressive tumor characteristics, such as large size, rupture, and invasion. NLR ≥3 was associated with early and overall recurrence after resection but varied with etiology. NLR may be a useful biomarker in predicting recurrence for HCC patients undergoing curative resection, but further studies are required to elucidate the effect of disease etiology.
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Affiliation(s)
- Linda Wong
- Department of Surgery, University of Hawaii, Honolulu, HI, USA
| | | | | | - Sandi Kwee
- Positron Emission Tomography Research Center, The Queens Medical Center, Honolulu, HI, USA
| | - Owen Chan
- Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Luke Ellis
- Department of Surgery, University of Hawaii, Honolulu, HI, USA
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Ye Z, Jiang H, Chen J, Liu X, Wei Y, Xia C, Duan T, Cao L, Zhang Z, Song B. Texture analysis on gadoxetic acid enhanced-MRI for predicting Ki-67 status in hepatocellular carcinoma: A prospective study. Chin J Cancer Res 2019; 31:806-817. [PMID: 31814684 PMCID: PMC6856708 DOI: 10.21147/j.issn.1000-9604.2019.05.10] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Objective To investigate the value of whole-lesion texture analysis on preoperative gadoxetic acid enhanced magnetic resonance imaging (MRI) for predicting tumor Ki-67 status after curative resection in patients with hepatocellular carcinoma (HCC). Methods This study consisted of 89 consecutive patients with surgically confirmed HCC. Texture features were extracted from multiparametric MRI based on whole-lesion regions of interest. The Ki-67 status was immunohistochemical determined and classified into low Ki-67 (labeling index ≤15%) and high Ki-67 (labeling index >15%) groups. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were applied for generating the texture signature, clinical nomogram and combined nomogram. The discrimination power, calibration and clinical usefulness of the three models were evaluated accordingly. Recurrence-free survival (RFS) rates after curative hepatectomy were also compared between groups. Results A total of 13 texture features were selected to construct a texture signature for predicting Ki-67 status in HCC patients (C-index: 0.878, 95% confidence interval: 0.791-0.937). After incorporating texture signature to the clinical nomogram which included significant clinical variates (AFP, BCLC-stage, capsule integrity, tumor margin, enhancing capsule), the combined nomogram showed higher discrimination ability (C-index: 0.936vs. 0.795, P<0.001), good calibration (P>0.05 in Hosmer-Lemeshow test) and higher clinical usefulness by decision curve analysis. RFS rate was significantly lower in the high Ki-67 group compared with the low Ki-67 group after curative surgery (63.27%vs. 85.00%, P<0.05). Conclusions Texture analysis on gadoxetic acid enhanced MRI can serve as a noninvasive approach to preoperatively predict Ki-67 status of HCC after curative resection. The combination of texture signature and clinical factors demonstrated the potential to further improve the prediction performance.
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Affiliation(s)
- Zheng Ye
- West China School of Medicine, Sichuan University, Chengdu 610041, China
| | - Hanyu Jiang
- West China School of Medicine, Sichuan University, Chengdu 610041, China
| | - Jie Chen
- West China School of Medicine, Sichuan University, Chengdu 610041, China
| | - Xijiao Liu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yi Wei
- West China School of Medicine, Sichuan University, Chengdu 610041, China
| | - Chunchao Xia
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Ting Duan
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Likun Cao
- West China School of Medicine, Sichuan University, Chengdu 610041, China
| | - Zhen Zhang
- West China School of Medicine, Sichuan University, Chengdu 610041, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China
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Hao J, Kim Y, Kim TK, Kang M. PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data. BMC Bioinformatics 2018; 19:510. [PMID: 30558539 PMCID: PMC6296065 DOI: 10.1186/s12859-018-2500-z] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 11/16/2018] [Indexed: 12/13/2022] Open
Abstract
Background Predicting prognosis in patients from large-scale genomic data is a fundamentally challenging problem in genomic medicine. However, the prognosis still remains poor in many diseases. The poor prognosis may be caused by high complexity of biological systems, where multiple biological components and their hierarchical relationships are involved. Moreover, it is challenging to develop robust computational solutions with high-dimension, low-sample size data. Results In this study, we propose a Pathway-Associated Sparse Deep Neural Network (PASNet) that not only predicts patients’ prognoses but also describes complex biological processes regarding biological pathways for prognosis. PASNet models a multilayered, hierarchical biological system of genes and pathways to predict clinical outcomes by leveraging deep learning. The sparse solution of PASNet provides the capability of model interpretability that most conventional fully-connected neural networks lack. We applied PASNet for long-term survival prediction in Glioblastoma multiforme (GBM), which is a primary brain cancer that shows poor prognostic performance. The predictive performance of PASNet was evaluated with multiple cross-validation experiments. PASNet showed a higher Area Under the Curve (AUC) and F1-score than previous long-term survival prediction classifiers, and the significance of PASNet’s performance was assessed by Wilcoxon signed-rank test. Furthermore, the biological pathways, found in PASNet, were referred to as significant pathways in GBM in previous biology and medicine research. Conclusions PASNet can describe the different biological systems of clinical outcomes for prognostic prediction as well as predicting prognosis more accurately than the current state-of-the-art methods. PASNet is the first pathway-based deep neural network that represents hierarchical representations of genes and pathways and their nonlinear effects, to the best of our knowledge. Additionally, PASNet would be promising due to its flexible model representation and interpretability, embodying the strengths of deep learning. The open-source code of PASNet is available at https://github.com/DataX-JieHao/PASNet.
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Affiliation(s)
- Jie Hao
- Kennesaw State University, Kennesaw, USA
| | | | - Tae-Kyung Kim
- University of Texas Southwestern Medical Center, Dallas, USA.,Department of Life Sciences, Pohang Institute of Science and Technology (POSTECH), Dallas, USA
| | - Mingon Kang
- Kennesaw State University, Kennesaw, USA. .,Kennesaw State University, Marietta, USA.
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Li HH, Qi LN, Ma L, Chen ZS, Xiang BD, Li LQ. Effect of KI-67 positive cellular index on prognosis after hepatectomy in Barcelona Clinic Liver Cancer stage A and B hepatocellular carcinoma with microvascular invasion. Onco Targets Ther 2018; 11:4747-4754. [PMID: 30127623 PMCID: PMC6091480 DOI: 10.2147/ott.s165244] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Objective This study aimed to explore the relationship between KI-67 positive cellular index and recurrence-free survival (RFS) in Barcelona Clinic Liver Cancer (BCLC) stage A and B hepatocellular carcinoma (HCC) patients, particularly those with microvascular invasion (MVI). Methods A total of 333 patients who underwent curative hepatectomy had their immunohistochemistry analyzed retrospectively for KI-67 positive cellular index. Results In total, 41.1% (137/333) of HCC patients displayed high KI-67 positive cellular index (>35%). Patients with high KI-67 positive cellular index had poorer RFS than those with low index (P<0.0001). Patients were then subdivided into an MVI positivity group (n=192) and an MVI negativity group (n=141). In the MVI positivity group, patients with high KI-67 positive cellular index had a shorter RFS after operation as compared to those with low index (P<0.0001). However, there was no significant difference in RFS between high- and low-index subgroups within the MVI negativity group (P>0.05). Additionally, patients with high KI-67 positive cellular index combined with MVI positivity had the shortest RFS of all those with MVI negativity, regardless of KI-67 cellular index level (P<0.0001). Multivariate analysis showed that node number >1, capsule absence, high KI-67 positive cellular index, and alpha-fetoprotein >400 ng/mL were independent risk factors for a recurrence of HCC with MVI. Conclusion Our results suggested that high KI-67 positive cellular index may represent a poor prognostic factor in BCLC stage A and B HCC patients, especially those with MVI.
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Affiliation(s)
- Hong-Hao Li
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, China,
| | - Lu-Nan Qi
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, China, .,Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China, .,Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning, 530021, China,
| | - Liang Ma
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, China, .,Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China,
| | - Zu-Shun Chen
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, China,
| | - Bang-De Xiang
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, China, .,Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China, .,Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning, 530021, China,
| | - Le-Qun Li
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, China, .,Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning, 530021, China, .,Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning, 530021, China,
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