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Li L, Wang X, Tan Z, Mao Y, Huang D, Yi X, Jiang M, Chen BT. Preoperative MR - based model for predicting prognosis in patients with intracranial extraventricular ependymoma. Eur J Radiol Open 2025; 14:100650. [PMID: 40248169 PMCID: PMC12005838 DOI: 10.1016/j.ejro.2025.100650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2025] [Revised: 03/19/2025] [Accepted: 03/31/2025] [Indexed: 04/19/2025] Open
Abstract
Objectives To develop and validate a prediction model based on brain MRI features to predict disease-free survival (DFS) and overall survival (OS) for patients with intracranial extraventricular ependymoma (IEE). Methods The study included 114 patients with pathology-proven IEE, of whom 80 were randomly assigned to a training group and 34 to a validation group. Preoperative brain MRI images were assessed with the Visually AcceSAble Rembrandt Images (VASARI) feature set. Clinical variables were assessed including age, gender, KPS, pathological grade of the tumor and blood test data such as eosinophil, blood urea nitrogen and serum creatinine. Multivariate Cox proportional hazards regression analysis was performed to select the independent prognostic factors for DFS and OS. Three prediction models were built with clinical variables, MRI-VASARI features, and combined clinical and MRI-VASARI data, respectively. The predictive power of survival models was assessed using c-index and calibration curve. Results Clinical variables such as eosinophil, blood urea nitrogen and serum creatinine, and MRI-VASARI feature for definition of the non-enhancing margin (F13) were significantly correlated with the prognosis of DFS. Blood urea nitrogen, D-dimer, tumor location (F1), eloquent brain (F3), and T1/FLAIR ratio (F10) were independent predictors of OS. Based on these factors, prediction models were constructed. The concordance indices of the three survival models for OS were 0.732, 0.729, and 0.768, respectively. For DFS, the concordance indices were respectively 0.694, 0.576, and 0.714. Conclusion Predictive modelling combining both clinical and MRI-VASARI features is robust and may assist in the assessment of prognosis in patients with IEE.
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Affiliation(s)
- Liyan Li
- Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, PR China
| | - Xueying Wang
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, PR China
| | - Zeming Tan
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan 410008, PR China
| | - Yipu Mao
- Department of Radiology, Nanning First People's Hospital, Nanning, Guangxi 530021, PR China
| | - Deyou Huang
- Department of Radiology, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi 533000, PR China
| | - Xiaoping Yi
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, PR China
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, Hunan 410008, PR China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan 410008, PR China
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central, South University, Changsha, Hunan 410008, PR China
- Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, Hunan 410008, PR China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, PR China
| | - Muliang Jiang
- Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, PR China
| | - Bihong T. Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, USA
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Zhou XP, Sun LB, Liu WH, Song XY, Gao Y, Xing JP, Gao SH. Development and validation of predictive models for distant metastasis and prognosis of gastroenteropancreatic neuroendocrine neoplasms. Sci Rep 2025; 15:9510. [PMID: 40108260 PMCID: PMC11923110 DOI: 10.1038/s41598-025-92974-x] [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: 11/16/2024] [Accepted: 03/04/2025] [Indexed: 03/22/2025] Open
Abstract
Imaging examinations exhibit a certain rate of missed detection for distant metastases of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). This study aims to develop and validate a risk prediction model for the distant metastases and prognosis of GEP-NENs. This study included patients diagnosed with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. External validation was performed with patients from the China-Japan Union Hospital of Jilin University. Univariate and multivariate logistic regression analyses were conducted on the selected data to identify independent risk factors for distant metastasis in GEP-NENs. A nomogram was subsequently developed using these variables to estimate the probability of distant metastasis in patients with GEP-NENs. Subsequently, patients with distant metastasis from GEP-NENs were selected for univariate and multivariate Cox regression analyses to identify prognostic risk factors. A nomogram was subsequently developed to predict overall survival (OS) in patients with GEP-NENs. Finally, the developed nomogram was validated using Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analysis (DCA). Kaplan-Meier analysis was employed to evaluate survival differences between high-risk and low-risk groups. A total of 11,207 patients with GEP-NENs were selected from the SEER database, and 152 patients from the China-Japan Union Hospital of Jilin University were utilized as an independent external validation cohort. Univariate and multivariate logistic regression analyses revealed that the primary tumor site, tumor grade, pathological type, tumor size, T stage, and N stage are independent predictors of distant metastasis in GEP-NENs. Additionally, among the 1732 patients with distant metastasis of GEP-NENs, univariate and multivariate Cox regression analyses identified N stage, tumor size, pathological type, primary site surgery, and tumor grade as independent prognostic factors. Based on the results of the regression analyses, a nomogram model was developed. Both internal and external validation results demonstrated that the nomogram models exhibited high predictive accuracy and significant clinical utility. In summary, we developed an effective predictive model to assess distant metastasis and prognosis in GEP-NENs. This model assists clinicians in evaluating the risk of distant metastasis and in assessing patient prognosis.
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Affiliation(s)
- Xuan-Peng Zhou
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China
| | - Luan-Biao Sun
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China
| | - Wen-Hao Liu
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China
| | - Xin-Yuan Song
- The Chinese University of Hong Kong, New Territories, 999077, Hong Kong Special Administrative Region, People's Republic of China
| | - Yang Gao
- Zhalute Banner People's Hospital, Tongliao, 029100, Inner Mongolia Autonomous Region, People's Republic of China
| | - Jian-Peng Xing
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China.
| | - Shuo-Hui Gao
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China.
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Guan R, Zheng Z, Deng M, Mei J, Lin Y. Assessment of Tumor Burden Score as a Feasible and Reliable Tool for Prognosis Prediction for Hepatocellular Carcinoma Undergoing Hepatectomy: A Multicenter, Retrospective Study. J Hepatocell Carcinoma 2025; 12:247-260. [PMID: 39959463 PMCID: PMC11827486 DOI: 10.2147/jhc.s488927] [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: 07/27/2024] [Accepted: 01/25/2025] [Indexed: 02/18/2025] Open
Abstract
Background Maximum diameter and number are the main parameters of tumor burden in hepatocellular carcinoma (HCC). Tumor burden score (TBS) shows its distinguished ability to stratify patients with HCC undergoing transcatheter arterial chemoembolization (TACE). However, the prognostic accuracy of TBS in HCC undergoing liver resection and its association with the BCLC stage has not been well evaluated. Methods A total of 3044 treatment-naïve HCC patients from six independent medical centers undergoing liver resection were retrospectively analyzed. Survival analyses were conducted by plotting Kaplan-Meier curves and the Log rank test. We further investigated whether the tumor burden score was a feasible subclassification criterion across the BCLC stage. Then, we also used TBS to identify HCC patients beyond BCLC criteria who could benefit most from surgical resection. Finally, univariate and multivariate cox analysis was used to determine independent prognostic predictors. Results About 44.2% (n=1343) of patients had low TBS, 38.8% (n=1182) had intermediate TBS and 17% (n=519) had high TBS. Overall survival (OS) and recurrence-free survival deteriorated incrementally with increasing TBS (P<0.0001). Subgroup analysis indicated that there was a significant survival difference among the three TBS groups across the BCLC stage (P<0.0001). Low TBS group of patients beyond BCLC criteria reported acceptable outcomes compared to intermediate TBS group patients within BCLC criteria, even better than high TBS group (5-year OS: 64.3%, 69.8%, and 56.3%). Finally, low TBS was identified as an independent protective prognostic factor. Conclusion Tumor burden score is a feasible and reliable prognostic tool for prognosis prediction and clinical decisions.
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Affiliation(s)
- Renguo Guan
- Department of General Surgery, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People’s Republic of China
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, People’s Republic of China
- Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, People’s Republic of China
| | - Zehao Zheng
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, People’s Republic of China
- Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, People’s Republic of China
| | - Min Deng
- Department of General Surgery, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Jie Mei
- Department of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, People’s Republic of China
- Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, People’s Republic of China
| | - Ye Lin
- Department of General Surgery, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People’s Republic of China
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Yang L, Chen C, Wang Q, Zhuang Z, Sun T. Development and Validation of a Competitive Risk Model in Elderly Patients with Transitional Cell Bladder Carcinoma. Med Sci Monit 2025; 31:e946332. [PMID: 39876530 PMCID: PMC11789422 DOI: 10.12659/msm.946332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2024] [Accepted: 11/27/2024] [Indexed: 01/30/2025] Open
Abstract
BACKGROUND Transitional cell bladder carcinoma (tcBC) is the predominant form of bladder cancer, making up around 95% of reported cases. Prognostic factors for older individuals with tcBC differ from those affecting younger patients. The main purpose of this study was to establish a prognostic competing risk model for elderly patients with tcBC. MATERIAL AND METHODS We conducted a retrospective analysis using data from the SEER database, randomly assigning patients to training and validation groups. We applied proportional subdistribution hazard (SH) to assess risk factors for cancer-related mortality (CSM). A competitive risk model was created to predict cancer-specific survival in elderly patients with tcBC. Model validation involved evaluating the area under the receiver operating curve, the consistency index, and a calibration curve. The Kaplan-Meier (K-M) curve was then used to compare mortality risk between high-risk and low-risk groups identified by the model. RESULTS This study randomly assigned 61 293 patients from the SEER database into training (42 905 patients) and validation (18 388 patients) groups in a 7: 3 ratio. Using a proportional subdistribution hazards model, we identified prognostic risk factors such as age, race, sex, marital status, TNM staging, grade, and metastatic status in brain, bone, liver, and lung. We developed a competitive risk model to predict 5-year cancer-specific survival (CSS) in elderly tcBC patients, achieving consistency index (C-index) values of 0.814 and 0.815 for the training and validation groups, respectively. Kaplan-Meier (K-M) analysis revealed 5-year survival probabilities of 35.1% (high-risk) and 42.2% (low-risk) in the training group, with similar rates of 35.7% and 42.0% in the validation group, both showing statistically significant differences (log-rank P<0.01). CONCLUSIONS We successfully established a competitive risk model for forecasting cancer-specific survival in elderly tcBC patients, primarily relying on these identified risk factors. The validation outcomes indicate the model's accuracy and dependability, making it a highly efficient predictive instrument. This tool enables making personalized clinical decisions for both medical professionals and patients.
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Lei X, Su Y, Lei R, Zhang D, Liu Z, Li X, Yang M, Pei J, Chi Y, Song L. Predictive and prognostic nomogram models for liver metastasis in colorectal neuroendocrine neoplasms: a large population study. Front Endocrinol (Lausanne) 2025; 15:1488733. [PMID: 39839478 PMCID: PMC11746099 DOI: 10.3389/fendo.2024.1488733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Accepted: 12/06/2024] [Indexed: 01/23/2025] Open
Abstract
Background In recent years, the incidence of patients with colorectal neuroendocrine neoplasms (CRNENs) has been continuously increasing. When diagnosed, most patients have distant metastases. Liver metastasis (LM) is the most common type of distant metastasis, and the prognosis is poor once it occurs. However, there is still a lack of large studies on the risk and prognosis of LM in CRNENs. This study aims to identify factors related to LM and prognosis and to develop a predictive model accordingly. Methods In this study, the Surveillance, Epidemiology, and End Results (SEER) database was used to collect clinical data from patients with CRNENs. The logistic regression analyses were conducted to identify factors associated with LM in patients with CRNENs. The patients with LM formed the prognostic cohort, and Cox regression analyses were performed to evaluate prognostic factors in patients with liver metastasis of colorectal neuroendocrine neoplasms (LM-CRNENs). Predictive and prognostic nomogram models were constructed based on the multivariate logistic and Cox analysis results. Finally, the capabilities of the nomogram models were verified through model assessment metrics, including the receiver operating characteristic (ROC) curves, calibration curve, and decision curve analysis (DCA) curve. Results This study ultimately encompassed a total of 10,260 patients with CRNENs. Among these patients, 501 cases developed LM. The result of multivariate logistic regression analyses indicated that histologic type, tumor grade, T stage, N stage, lung metastasis, bone metastasis, and tumor size were independent predictive factors for LM in patients with CRNENs (p < 0.05). Multivariate Cox regression analyses indicated that age, primary tumor site, histologic type, tumor grade, N stage, tumor size, chemotherapy, and surgery were independent prognostic factors (p < 0.05) for patients with LM-CRNENs. The predictive and prognostic nomogram models were established based on the independent factors of logistic and Cox analyses. The nomogram models can provide higher accuracy and efficacy in predicting the probability of LM in patients with CRNENs and the prognosis of patients with LM. Conclusion The factors associated with the occurrence of LM in CRNENs were identified. On the other hand, the relevant prognostic factors for patients with LM-CRNENs were also demonstrated. The nomogram models, based on independent factors, demonstrate greater efficiency and accuracy, promising to provide clinical interventions and decision-making support for patients.
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Affiliation(s)
- Xiao Lei
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yanwei Su
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Neuroendocrine Tumor Medical Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Rui Lei
- Department of Endocrinology, Zhoukou First People‘s Hospital, Zhoukou, China
| | - Dongyang Zhang
- School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, China
| | - Zimeng Liu
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiangke Li
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Minjie Yang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jiaxin Pei
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yanyan Chi
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Neuroendocrine Tumor Medical Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lijie Song
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Neuroendocrine Tumor Medical Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Li H, Zhou C, Wang C, Li B, Song Y, Yang B, Zhang Y, Li X, Rao M, Zhang J, Su K, He K, Han Y. Lasso-Cox interpretable model of AFP-negative hepatocellular carcinoma. Clin Transl Oncol 2025; 27:309-318. [PMID: 38965191 DOI: 10.1007/s12094-024-03588-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Accepted: 06/24/2024] [Indexed: 07/06/2024]
Abstract
BACKGROUND In AFP-negative hepatocellular carcinoma patients, markers for predicting tumor progression or prognosis are limited. Therefore, our objective is to establish an optimal predicet model for this subset of patients, utilizing interpretable methods to enhance the accuracy of HCC prognosis prediction. METHODS We recruited a total of 508 AFP-negative HCC patients in this study, modeling with randomly divided training set and validated with validation set. At the same time, 86 patients treated in different time periods were used as internal validation. After comparing the cox model with the random forest model based on Lasso regression, we have chosen the former to build our model. This model has been interpreted with SHAP values and validated using ROC, DCA. Additionally, we have reconfirmed the model's effectiveness by employing an internal validation set of independent periods. Subsequently, we have established a risk stratification system. RESULTS The AUC values of the Lasso-Cox model at 1, 2, and 3 years were 0.807, 0.846, and 0.803, and the AUC values of the Lasso-RSF model at 1, 2, and 3 years were 0.783, 0.829, and 0.776. Lasso-Cox model was finally used to predict the prognosis of AFP-negative HCC patients in this study. And BCLC stage, gamma-glutamyl transferase (GGT), diameter of tumor, lung metastases (LM), albumin (ALB), alkaline phosphatase (ALP), and the number of tumors were included in the model. The validation set and the separate internal validation set both indicate that the model is stable and accurate. Using risk factors to establish risk stratification, we observed that the survival time of the low-risk group, the middle-risk group, and the high-risk group decreased gradually, with significant differences among the three groups. CONCLUSION The Lasso-Cox model based on AFP-negative HCC showed good predictive performance for liver cancer. SHAP explained the model for further clinical application.
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Affiliation(s)
- Han Li
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China
| | - Chengyuan Zhou
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China
| | - Chenjie Wang
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China
| | - Bo Li
- Department of General Surgery (Hepatobiliary Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
| | - Yanqiong Song
- School of Medicine, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Bo Yang
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China
| | - Yan Zhang
- Department of Oncology, Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University, Luzhou, 646000, China
| | - Xueting Li
- Department of Oncology, 363 Hospital, Chengdu, China
| | - Mingyue Rao
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China
| | - Jianwen Zhang
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China
| | - Ke Su
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China
- Department of Radiation Oncology, National Cancer Center/ National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kun He
- Clinical Medical College, Southwest Medical University, Luzhou, 646000, China.
| | - Yunwei Han
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Taiping Street, Luzhou, 646000, Sichuan Province, China.
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Wang X, Chai X, Tang R, Xu Y, Chen Q. Comparison of laparoscopic hepatectomy and radiofrequency ablation for small hepatocellular carcinoma patients: a SEER population-based propensity score matching study. Updates Surg 2024; 76:2755-2766. [PMID: 39354331 PMCID: PMC11628577 DOI: 10.1007/s13304-024-02016-w] [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: 06/01/2024] [Accepted: 09/25/2024] [Indexed: 10/03/2024]
Abstract
This study was designed to compare the efficacy of laparoscopic hepatectomy (LH) and radiofrequency ablation (RFA) in terms of their therapeutic effect on small hepatocellular carcinoma (SHCC). The SEER database was employed to integrate SHCC patients who had received treatment with either LH (n = 1132) or RFA (n = 797). The LH group (n = 623) and the RFA group (n = 623) were matched with 1:1 propensity score matching (PSM) in order to reduce the possibility of selection bias. The Kaplan-Meier method and Cox proportional hazards regression method were employed to ascertain the prognostic factors associated with overall survival (OS) and disease-specific survival (DSS). Both before and after PSM, the 1, 3 and 5-years OS and DSS were significantly higher in the LH groups compared to the RFA group. Besides, for SHCC with tumor size ≤ 2cm (n = 418), even P values not reaching statistical significance, the survival curves were compatible with a superiority of LH over RFA for OS and DSS in overall (P = 0.054 and P = 0.077), primary SHCC (P = 0.110 and P = 0.058) and recurrent SHCC (P = 0.068 and P = 1.000) cohorts. In contrast, for SHCC with tumor size between 2 and 3 cm (n = 828), LH group always had a better OS and DSS in the all cohorts (all P < 0.05). In addition, higher AFP level, poor differentiation grade, recurrent tumor and treatment type were independent prognostic factors for OS, while poor differentiation grade, larger tumor size and treatment type were the independent prognostic factors for DSS (all P < 0.05). LH was associated with better OS and DSS than RFA in SHCC patients. Even in tumor size ≤ 2 cm, LH still should be the first choice as its long-term survival benefits.
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Affiliation(s)
- Xi Wang
- Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xinqun Chai
- Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ruiya Tang
- Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yunjie Xu
- Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qinjunjie Chen
- Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Lun Y, Yuan H, Ma P, Chen J, Lu P, Wang W, Liang R, Zhang J, Gao W, Ding X, Li S, Wang Z, Guo J, Lu L. A prediction model based on random survival forest analysis of the overall survival of elderly female papillary thyroid carcinoma patients: a SEER-based study. Endocrine 2024; 85:1252-1260. [PMID: 38558373 DOI: 10.1007/s12020-024-03797-1] [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: 01/21/2024] [Accepted: 03/24/2024] [Indexed: 04/04/2024]
Abstract
OBJECTIVE Papillary thyroid carcinoma (PTC) is a common malignancy whose incidence is three times greater in females than in males. The prognosis of ageing patients is poor. This research was designed to construct models to predict the overall survival of elderly female patients with PTC. METHODS We developed prediction models based on the random survival forest (RSF) algorithm and traditional Cox regression. The data of 4539 patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Twelve variables were analysed to establish the models. The C-index and the Brier score were selected to evaluate the discriminatory ability of the models. Time-dependent receiver operating characteristic (ROC) curves were also drawn to evaluate the accuracy of the models. The clinical benefits of the two models were compared on the basis of the DCA curve. In addition, the Shapley Additive Explanations (SHAP) plot was used to visualize the contribution of the variables in the RSF model. RESULTS The C-index of the RSF model was 0.811, which was greater than that of the Cox model (0.781). According to the Brier score and the area under the ROC curve (AUC), the RSF model performed better than the Cox model. On the basis of the DCA curve, the RSF model demonstrated fair clinical benefit. The SHAP plot showed that age was the most important variable contributing to the outcome of PTC in elderly female patients. CONCLUSIONS The RSF model we developed performed better than the Cox model and might be valuable for clinical practice.
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Affiliation(s)
- Yuqiang Lun
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Hao Yuan
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Pengwei Ma
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Jiawei Chen
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Peiheng Lu
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Weilong Wang
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Rui Liang
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Junjun Zhang
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Wei Gao
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Xuerui Ding
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Siyu Li
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Zi Wang
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Jianing Guo
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Lianjun Lu
- Department of Otolaryngology Head and Neck Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
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Yang B, Huang G, Chen D, Wei L, Zhao Y, Chen G, Li J, Wang L, Xie B, Jiang W, Chen Z. A nomogram incorporating Psoas muscle index for predicting tumor recurrence after liver transplantation: A retrospective study in an Eastern Asian population. Heliyon 2024; 10:e34019. [PMID: 39262955 PMCID: PMC11388506 DOI: 10.1016/j.heliyon.2024.e34019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 07/01/2024] [Accepted: 07/02/2024] [Indexed: 09/13/2024] Open
Abstract
Background and aims Tumor recurrence significantly affects the prognostic outcomes for liver cancer patients following liver transplantation. However, existing predictive models often neglect the inclusion of body composition indicators. Hence, this research aimed to investigate the significance of the psoas muscle index (PMI) in evaluating the post-transplant prognosis of liver cancer. Methods A retrospective analysis was conducted on liver cancer patients who underwent liver transplantation surgery. Imaging analysis was performed using CT data to calculate PMI based on the left and right psoas muscle areas. Subsequently, the patients were categorized into PMI-Low and PMI-High groups using the established cut-off values. Univariate and multivariate analyses were performed using Cox proportional hazards regression to assess the correlation between PMI and clinical outcomes, and a nomogram was constructed accordingly. Results Among the 225 patients included in the analysis, the PMI-High group exhibited significantly improved overall survival (P < 0.001) and disease-free survival (DFS, P < 0.001) rates compared to the PMI-Low group. PMI exhibited a positive correlation with body mass index (R = 0.25, P < 0.001), but no significant correlations were observed. In the multivariate analysis, PMI (HR = 4.596, P < 0.001), MELD score (HR = 1.591, P = 0.038), and Hangzhou criteria (HR = 2.557, P < 0.001) emerged as significant predictors of DFS. The constructed nomogram, incorporating these predictors, demonstrated outstanding predictive performance. Decision curve analysis revealed the superiority of the nomogram over conventional methods. Conclusions PMI serves as a valuable prognostic factor for tumor recurrence in liver cancer patients after liver transplantation. The established nomogram is pivotal in delivering personalized predictions of DFS.
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Affiliation(s)
- Bo Yang
- Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education, Wuhan, 430030, China
- NHC Key Laboratory of Organ Transplantation, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, 430030, China
| | - Guobin Huang
- Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education, Wuhan, 430030, China
- NHC Key Laboratory of Organ Transplantation, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, 430030, China
| | - Dong Chen
- Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education, Wuhan, 430030, China
- NHC Key Laboratory of Organ Transplantation, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, 430030, China
| | - Lai Wei
- Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education, Wuhan, 430030, China
- NHC Key Laboratory of Organ Transplantation, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, 430030, China
| | - Yuanyuan Zhao
- Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education, Wuhan, 430030, China
- NHC Key Laboratory of Organ Transplantation, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, 430030, China
| | - Gen Chen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Junbo Li
- Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education, Wuhan, 430030, China
- NHC Key Laboratory of Organ Transplantation, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, 430030, China
| | - Lu Wang
- Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education, Wuhan, 430030, China
- NHC Key Laboratory of Organ Transplantation, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, 430030, China
| | - Bowen Xie
- Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education, Wuhan, 430030, China
- NHC Key Laboratory of Organ Transplantation, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, 430030, China
| | - Wei Jiang
- Department of Gastrointestinal Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Zhishui Chen
- Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Ministry of Education, Wuhan, 430030, China
- NHC Key Laboratory of Organ Transplantation, Wuhan, 430030, China
- Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, 430030, China
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Hou S, Li L, Hou H, Zhou T, Zhou H. Establishment of nomogram to predict overall survival and cancer-specific survival of local tumor resection in patients with colorectal cancer liver metastasis with unresectable metastases: a large population-based analysis. Discov Oncol 2024; 15:315. [PMID: 39073708 PMCID: PMC11286894 DOI: 10.1007/s12672-024-01182-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 07/20/2024] [Indexed: 07/30/2024] Open
Abstract
BACKGROUND AND PURPOSE The tumour-node metastasis (TNM) classification is a common model for evaluating the prognostic value of tumour patients. However, few models have been used to predict the survival outcomes of patients with colorectal cancer liver metastasis (CRLM) with unresectable metastases who received the primary local surgery. Thus, we utilized the Surveillance, Epidemiology, and End Results (SEER) database to establish novel nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of these patients. METHODS Extracted primary data on CRLM patients by local surgery from SEER database. All prognostic factors of OS and CSS were determined by Cox regression analysis. The concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves were used to further evaluate the accuracy and discrimination of these nomograms. Decision curve analysis (DCA) was executed to evaluate the nomograms for the clinical net benefit. Risk stratification analysis (RSA) was used to evaluate the reliability of them in clinical. RESULTS 3622 eligible patients were screened and assigned to training cohort (1812) or validation cohort (1810). The age, chemotherapy, tumour grade, primary tumour site, tumour size, lymph node positive rate (LNR), marital status, and carcinoembryonic antigen (CEA) were independent prognostic factors of OS. Additionally, the age, chemotherapy, tumour grade, primary tumour site, tumour size, LNR, and CEA were independent prognostic factors of CSS. The results of C-indexes and ROC curves indicated that the established nomograms exhibited better discrimination power than TNM classification. The calibration curves demonstrated excellent agreement between the predicted and actual survival rates for 1-, 3-, and 5 year OS and CSS. Meanwhile, the validation cohort demonstrated similar results. Background the clinic context, the DCA showed that these nomograms have higher net benefits, and the RSA showed that patients were further divided into low risk, medium risk, and high risk groups according to the predicted scores from nomograms. And, the Kaplan-Meier curve and log-rank test showed that the survival differences among the three groups are statistically significant. CONCLUSIONS The prognostic nomograms showed very high accuracy, identifiability, and clinical practicality in predicting the OS and CSS of CRLM patients with unresectable metastases treated by local surgery at 1-, 3-, and 5 years, which might improve individualized predictions of survival risks and help clinicians formulate treatment plans.
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Affiliation(s)
- Songlin Hou
- The Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China
- Institute of Hepatobiliary, Pancreatic and Intestinal Disease, North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Lifa Li
- The Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China
- Institute of Hepatobiliary, Pancreatic and Intestinal Disease, North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Huafang Hou
- The Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China
| | - Tong Zhou
- The Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China
- Institute of Hepatobiliary, Pancreatic and Intestinal Disease, North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - He Zhou
- The Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China.
- Institute of Hepatobiliary, Pancreatic and Intestinal Disease, North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China.
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11
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Thompson JJ, McGovern J, Roxburgh CSD, Edwards J, Dolan RD, McMillan DC. The relationship between LDH and GLIM criteria for cancer cachexia: Systematic review and meta-analysis. Crit Rev Oncol Hematol 2024; 199:104378. [PMID: 38754770 DOI: 10.1016/j.critrevonc.2024.104378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 04/02/2024] [Accepted: 04/30/2024] [Indexed: 05/18/2024] Open
Abstract
INTRODUCTION Cancer cachexia is a clinical condition characterized by recognizable "sickness behaviors" accompanied by loss of lean body tissue. The Global Leadership on Malnutrition (GLIM) has proposed phenotypic (unintentional weight loss, low body mass index and low muscle mass) and aetiologic (reduced food intake and inflammation or disease burden) diagnostic criteria. Recent work has suggested serum lactate dehydrogenase (LDH) might represent a 3rd aetiologic criteria. Little is known of its relationship with GLIM. A systematic review and meta-analysis of their comparative prognostic value and association was performed. METHODS A search of electronic databases (PubMed, Medline, Ovid, Cochrane) up to February 2023 was used to identify studies that compared the prognostic value of LDH and components of the GLIM criteria in cancer. An analysis of the relationship between LDH and the components of GLIM was undertaken where this data was available. RevMan 5.4.1 was used to perform a meta-analysis for each diagnostic criteria that had 3 or more studies which reported hazard ratios with a 95 per cent confidence interval for overall survival (OS). RESULTS A total of 119 studies were reviewed. Advanced lung cancer was the most studied population. Included in the meta-analysis were 6 studies (n=2165) on LDH and weight loss, 17 studies (n=7540) on LDH and low BMI, 5 studies (n=758) on LDH and low muscle mass, 0 studies on LDH and food intake and 93 studies (n=32,190) on LDH and inflammation. There was a significant association between elevated serum LDH and each of low BMI (OR 1.39, 1.09 - 1.77; p=0.008), elevated NLR (OR 2.04, 1.57 - 2.65; p<0.00001) and elevated CRP (OR 2.58, 1.81 - 3.67; p<0.00001). There was no association between elevated serum LDH and low muscle mass. Only one study presented data on the association between LDH and unintentional weight loss. Elevated LDH showed a comparative OS (HR 1.86, 1.57 - 2.07; p<0.00001) to unintentional weight loss (HR 1.57, 1.23 - 1.99; p=0.0002) and had a similar OS (HR 2.00, 1.70 - 2.34; p<0.00001) to low BMI (HR 1.57, 1.29-2.90; p<0.0001). LDH also showed an OS (HR 2.25, 1.76 - 2.87; p<0.00001) congruous with low muscle mass (HR 1.93, 1.14 - 3.27; p=0.01) and again, LDH conferred as poor an OS (HR 1.77, 1.64-1.90; p<0.00001) as elevated NLR (HR 1.61, 1.48 - 1.77; p<0.00001) or CRP (HR 1.55, 1.43 - 1.69; p<0.00001). CONCLUSION Current literature suggests elevated serum LDH is associated with inflammation in cancer (an aetiologic GLIM criterion), however more work is required to establish the relationship between LDH and the phenotypic components of GLIM. Additionally, elevated serum LDH appears to be a comparative prognosticator of overall survival in cancer when compared to the GLIM criteria.
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Affiliation(s)
- Joshua J Thompson
- Academic Unit of Surgery, School of Medicine, University of Glasgow, Glasgow Royal Infirmary, Glasgow, UK.
| | - Josh McGovern
- Academic Unit of Surgery, School of Medicine, University of Glasgow, Glasgow Royal Infirmary, Glasgow, UK
| | - Campbell S D Roxburgh
- Academic Unit of Surgery, School of Medicine, University of Glasgow, Glasgow Royal Infirmary, Glasgow, UK
| | - Joanne Edwards
- Wolfson Wohl Cancer Research Centre, School of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Ross D Dolan
- Academic Unit of Surgery, School of Medicine, University of Glasgow, Glasgow Royal Infirmary, Glasgow, UK
| | - Donald C McMillan
- Academic Unit of Surgery, School of Medicine, University of Glasgow, Glasgow Royal Infirmary, Glasgow, UK
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12
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Xia F, Zhang Q, Xia G, Ndhlovu E, Chen X, Huang Z, Zhang B, Zhu P. A pathologic scoring system for predicting postoperative prognosis in patients with ruptured hepatocellular carcinoma. Asian J Surg 2024; 47:3015-3025. [PMID: 38326117 DOI: 10.1016/j.asjsur.2024.01.139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/14/2024] [Accepted: 01/26/2024] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND The accuracy of pathological factors to predict the prognosis of patients with ruptured hepatocellular carcinoma (rHCC) is unclear. We aimed to develop and validate a novel scoring system based on pathological factors to predict the postoperative survival of patients with rHCC. METHOD Patients with rHCC who underwent hepatectomy were recruited from three hospitals and allocated to the training (n = 221) and validation (n = 194) cohorts. A new scoring system, namely the MSE (microvascular invasion-satellite foci-Edmondson Steiner) score, was established based on three pathological factors using univariate and multivariate Cox proportional hazards regression analyses, including microvascular invasion, satellite foci, and differentiation grade. Finally, patients were stratified into three groups based on their risk of prognosis (low, intermediate, or high) according to their MSE score. We also constructed MSE score-based nomograms. The performance of the nomograms was assessed by receiver operating characteristic and calibration curve analyses and validated using the validation cohort. RESULTS Three pathological factors were significantly correlated with overall survival (OS) and recurrence-free survival (RFS), three of which were included in the MSE score. The score can clearly stratify rHCC patients after hepatectomy (P < 0.05). And we established nomograms based on the MSE score (MSE score, Barcelona Clinic Liver Cancer stage, and alpha-fetoprotein concentration) to predict postoperative OS and RFS in patients with rHCC. The nomograms showed good discrimination, with C-indices over 0.760 for OS and RFS at 1, 3, and 5 years, respectively. The calibration curve showed excellent nomogram calibration, which was also verified in the validation cohort. CONCLUSION The clinical MSE score were accurate in predicting OS and RFS in patients with rHCC with resectable lesions after hepatectomy.
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Affiliation(s)
- Feng Xia
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qiao Zhang
- Department of Hepatobiliary and Pancreatic Surgery, Zhongshan People's Hospital Affiliated to Guangdong Medical University, Guangdong, China
| | - Guobing Xia
- Department of Hepatobiliary and Pancreatic Surgery, Huangshi Central Hospital of Edong Healthcare Group, Hubei Polytechnic University.Huangshi, Hubei, China
| | - Elijah Ndhlovu
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaoping Chen
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhiyuan Huang
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Bixiang Zhang
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Peng Zhu
- Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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Gao Y, Xu Y, Wang Y, Lu J, Guo JH. Clinical features and prognostic factors of patients with inoperable hepatocellular carcinoma treated with chemotherapy: a population-based study. J Gastrointest Oncol 2024; 15:1122-1140. [PMID: 38989427 PMCID: PMC11231877 DOI: 10.21037/jgo-24-298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 06/07/2024] [Indexed: 07/12/2024] Open
Abstract
Background In inoperable hepatocellular carcinoma (HCC), chemotherapy is a common treatment strategy. However, there is a lack of reliable methods to predict the prognosis of patients with inoperable HCC after chemotherapy. Therefore, the aim of this study was to identify the clinical characteristics of patients with inoperable HCC and to establish and validate nomogram models for predicting the survival outcomes in this patient group following chemotherapy. Methods The data of patients diagnosed with HCC from the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively collected. Logistic regression analyses were used to identify potential factors for inoperability in patients with HCC. Kaplan-Meier analyses were applied to evaluate the impact of chemotherapy on prognosis. Additionally, Cox regression analyses were performed to identify the potential risk factors associated with overall survival (OS) and cancer-specific survival (CSS) in patients with inoperable HCC treated with chemotherapy. Finally, we constructed prognostic nomograms for predicting the 1- and 3-year survival probabilities. Results A total of 3,519 operable patients with HCC and 4,656 patients with inoperable HCC were ultimately included in this study. Logistic regression analyses revealed a significant association between patient age, gender, race, tumor, node, metastasis (TNM) stage, tumor size, pretreatment alpha fetoprotein (AFP) levels, and marital status with inoperability. Moreover, Kaplan-Meier analyses revealed a significant improvement in both OS and CSS with the administration of chemotherapy. Moreover, 1,456 patients with inoperable HCC were enrolled in the training group and 631 patients with inoperable HCC were enrolled in the validation group to develop and validate the prognostic models. Cox regression models indicated that TNM stage, tumor size, and pretreatment AFP were independent risk factors for predicting OS and CSS in patients with inoperable HCC receiving chemotherapy. These factors were subsequently integrated into the predictive nomograms. Conclusions We preliminarily developed survival models with strong predictive capabilities for estimating survival probabilities in patients with HCC following chemotherapy. These models hold potential for clinical application and warrant further exploration through additional studies.
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Affiliation(s)
- Yang Gao
- Center of Interventional Radiology & Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
- Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, Nanjing, China
| | - Yihang Xu
- The First Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Yong Wang
- Center of Interventional Radiology & Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
- Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, Nanjing, China
| | - Jian Lu
- Center of Interventional Radiology & Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
- Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, Nanjing, China
| | - Jin-He Guo
- Center of Interventional Radiology & Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
- Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, Nanjing, China
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14
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Jin N, Rong J, Chen X, Huang L, Ma H. Exploring T-cell exhaustion features in Acute myocardial infarction for a Novel Diagnostic model and new therapeutic targets by bio-informatics and machine learning. BMC Cardiovasc Disord 2024; 24:272. [PMID: 38783198 PMCID: PMC11118734 DOI: 10.1186/s12872-024-03907-x] [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: 12/17/2023] [Accepted: 04/29/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND T-cell exhaustion (TEX), a condition characterized by impaired T-cell function, has been implicated in numerous pathological conditions, but its role in acute myocardial Infarction (AMI) remains largely unexplored. This research aims to identify and characterize all TEX-related genes for AMI diagnosis. METHODS By integrating gene expression profiles, differential expression analysis, gene set enrichment analysis, protein-protein interaction networks, and machine learning algorithms, we were able to decipher the molecular mechanisms underlying TEX and its significant association with AMI. In addition, we investigated the diagnostic validity of the leading TEX-related genes and their interactions with immune cell profiles. Different types of candidate small molecule compounds were ultimately matched with TEX-featured genes in the "DrugBank" database to serve as potential therapeutic medications for future TEX-AMI basic research. RESULTS We screened 1725 differentially expressed genes (DEGs) from 80 AMI samples and 71 control samples, identifying 39 differential TEX-related transcripts in total. Functional enrichment analysis identified potential biological functions and signaling pathways associated with the aforementioned genes. We constructed a TEX signature containing five hub genes with favorable prognostic performance using machine learning algorithms. In addition, the prognostic performance of the nomogram of these five hub genes was adequate (AUC between 0.815 and 0.995). Several dysregulated immune cells were also observed. Finally, six small molecule compounds which could be the future therapeutic for TEX in AMI were discovered. CONCLUSION Five TEX diagnostic feature genes, CD48, CD247, FCER1G, TNFAIP3, and FCGRA, were screened in AMI. Combining these genes may aid in the early diagnosis and risk prediction of AMI, as well as the evaluation of immune cell infiltration and the discovery of new therapeutics.
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Affiliation(s)
- Nake Jin
- Department of Cardiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, State Key Laboratory of Transvascular Implantation Devices, Cardiovascular Key Laboratory of Zhejiang Province, Hangzhou, 310009, Zhejiang, China
- Department of Cardiology, Ningbo Hangzhou Bay Hospital, Ningbo, 315300, Zhejiang, China
| | - Jiacheng Rong
- Department of Cardiology, Ningbo Hangzhou Bay Hospital, Ningbo, 315300, Zhejiang, China
| | - Xudong Chen
- Department of Cardiology, Ningbo Hangzhou Bay Hospital, Ningbo, 315300, Zhejiang, China
| | - Lei Huang
- Department of Cardiology, Ningbo Hangzhou Bay Hospital, Ningbo, 315300, Zhejiang, China
| | - Hong Ma
- Department of Cardiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, State Key Laboratory of Transvascular Implantation Devices, Cardiovascular Key Laboratory of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
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15
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Tan J, Yu Y, Lin X, He Y, Jin W, Qian H, Li Y, Xu X, Zhao Y, Ning J, Zhang Z, Chen J, Wu X. OHCCPredictor: an online risk stratification model for predicting survival duration of older patients with hepatocellular carcinoma. Hepatol Int 2024; 18:550-567. [PMID: 37067674 PMCID: PMC11014809 DOI: 10.1007/s12072-023-10516-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 03/07/2023] [Indexed: 04/18/2023]
Abstract
BACKGROUND Although the elderly constitute more than a third of hepatocellular carcinoma (HCC) patients, they have not been adequately represented in treatment and prognosis studies. Thus, there is not enough evidence to guide the treatment of such patients. The objective of this study is to identify the prognostic factors of older patients with HCC and to construct a new prognostic model for predicting their overall survival (OS). METHODS 2,721 HCC patients aged ≥ 65 were extracted from the public database-Surveillance, Epidemiology, and End Results (SEER) and randomly divided into a training set and an internal validation set with a ratio of 7:3. 101 patients diagnosed from 2008 to 2017 in the First Affiliated Hospital of Zhejiang University School of Medicine were identified as the external validation set. Univariate cox regression analyses and multivariate cox regression analyses were adopted to identify these independent prognostic factors. A predictive nomogram-based risk stratification model was proposed and evaluated using area under the receiver operating characteristic curve (AUC), calibration curves, and a decision curve analysis (DCA). RESULTS These attributes including age, sex, marital status, T stage, N stage, surgery, chemotherapy, tumor size, alpha-fetoprotein level, fibrosis score, bone metastasis, lung metastasis, and grade were the independent prognostic factors for older patients with HCC while predicting survival duration. We found that the nomogram provided a good assessment of OS at 1, 3, and 5 years in older patients with HCC (1-year OS: (training set: AUC = 0.823 (95%CI 0.803-0.845); internal validation set: AUC = 0.847 (95%CI 0.818-0.876); external validation set: AUC = 0.732 (95%CI 0.521-0.943)); 3-year OS: (training set: AUC = 0.813 (95%CI 0.790-0.837); internal validation set: AUC = 0.844 (95%CI 0.812-0.876); external validation set: AUC = 0.780 (95%CI 0.674-0.887)); 5-year OS: (training set: AUC = 0.839 (95%CI 0.806-0.872); internal validation set: AUC = 0.800 (95%CI 0.751-0.849); external validation set: AUC = 0.821 (95%CI 0.727-0.914)). The calibration curves showed that the nomogram was with strong calibration. The DCA indicated that the nomogram can be used as an effective tool in clinical practice. The risk stratification of all subgroups was statistically significant (p < 0.05). In the stratification analysis of surgery, larger resection (LR) achieved a better survival curve than local destruction (LD), but a worse one than segmental resection (SR) and liver transplantation (LT) (p < 0.0001). With the consideration of the friendship to clinicians, we further developed an online interface (OHCCPredictor) for such a predictive function ( https://juntaotan.shinyapps.io/dynnomapp_hcc/ ). With such an easily obtained online tool, clinicians will be provided helpful assistance in formulating personalized therapy to assess the prognosis of older patients with HCC. CONCLUSIONS Age, sex, marital status, T stage, N stage, surgery, chemotherapy, tumor size, AFP level, fibrosis score, bone metastasis, lung metastasis, and grade were independent prognostic factors for elderly patients with HCC. The constructed nomogram model based on the above factors could accurately predict the prognosis of such patients. Besides, the developed online web interface of the predictive model provide easily obtained access for clinicians.
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Affiliation(s)
- Juntao Tan
- Operation Management Office, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, 401320, China
| | - Yue Yu
- Senior Bioinformatician Department of Quantitative, Health Sciences Mayo Clinic, Rochester, MN, 55905, US
| | - Xiantian Lin
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qing Chun Road, Hangzhou, Zhejiang, 310003, China
| | - Yuxin He
- Department of Medical Administration, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, 401320, China
| | - Wen Jin
- Medical Records Department, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Hong Qian
- Medical Records Department, The First Hospital of Lanzhou University, Lanzhou, 730000, China
| | - Ying Li
- Department of Medical Administration, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Xiaomei Xu
- Department of Gastroenterology, Chengdu Fifth People's Hospital, Chengdu, 611130, China
- Department of Infectious Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 404000, China
| | - Yuxi Zhao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qing Chun Road, Hangzhou, Zhejiang, 310003, China
| | - Jianwen Ning
- Emergency Department, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Zhengyu Zhang
- Medical Records Department, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
| | - Jingjing Chen
- Department of Digital Urban Governance, Zhejiang University City College, Hangzhou, 310015, China.
| | - Xiaoxin Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qing Chun Road, Hangzhou, Zhejiang, 310003, China.
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Zhang BL, Liu J, Diao G, Chang J, Xue J, Huang Z, Zhao H, Yu L, Cai J. Construction and Validation of a Novel Nomogram Predicting Recurrence in Alpha-Fetoprotein-Negative Hepatocellular Carcinoma Post-Surgery Using an Innovative Liver Function-Nutrition-Inflammation-Immune (LFNII) Score: A Bicentric Investigation. J Hepatocell Carcinoma 2024; 11:489-508. [PMID: 38463544 PMCID: PMC10924898 DOI: 10.2147/jhc.s451357] [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: 11/29/2023] [Accepted: 02/29/2024] [Indexed: 03/12/2024] Open
Abstract
Purpose We developed a nomogram based on the liver function, nutrition, inflammation, and immunity (LFNII) score to predict recurrence-free survival (RFS) post-resection in patients with hepatocellular carcinoma (HCC) exhibiting alpha-fetoprotein (AFP) negativity (AFP ≤20 ng/mL). Patients and Methods Clinical data of 661 patients diagnosed with alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) who underwent surgical resection at two medical centers between 2012 and 2021 were collected. A total of 462 and 199 patients served as the training and validation sets, respectively. Pre-operative blood markers were collected and analyzed for LFNII. The LFNII score was formulated using the least absolute shrinkage and selection operator Cox regression model. A nomogram model was developed using the training set to incorporate other relevant clinicopathological indicators and predict postoperative recurrence. Model discrimination was assessed using the receiver operating characteristic curve, calibration was evaluated using a calibration curve, and clinical applicability was assessed using clinical decision curve analysis. A comparison with liver cancer staging was performed using the nomogram model. Finally, a cohort study was conducted to validate our findings. Results We derived the LFNII scores from nine indicators. Elevated LFNII scores correlated with unfavorable clinicopathological features. The LFNII score area under the curve revealed superior predictive efficacy at 1-, 2-, and 5-year RFS intervals, with values of 0.675, 0.658, and 0.633, respectively. Multivariate Cox analysis revealed that a high LFNII score independently increased RFS risk in patients with AFP-NHCC. The C-index of the LFNII-nomogram model was 0.686 (95% confidence interval [CI], 0.651-0.721). The nomogram model's clinical application value surpassed that of standard HCC staging systems. Conclusion The LFNII score-derived nomogram effectively predicted the RFS of patients with AFP-NHCC after curative resection.
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Affiliation(s)
- Bo-Lun Zhang
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Jia Liu
- Department of Hepatobiliary Surgery, the Fifth Medical Center of the PLA General Hospital, Beijing, People’s Republic of China
| | - Guanghao Diao
- Department of Hepatobiliary Surgery, the Fifth Medical Center of the PLA General Hospital, Beijing, People’s Republic of China
| | - Jianping Chang
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Junshuai Xue
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Zhen Huang
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Hong Zhao
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Lingxiang Yu
- Department of Hepatobiliary Surgery, the Fifth Medical Center of the PLA General Hospital, Beijing, People’s Republic of China
| | - Jianqiang Cai
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
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Liu C, Li Z, Zhang Z, Li J, Xu C, Jia Y, Zhang C, Yang W, Wang W, Wang X, Liang K, Peng L, Wang J. Prediction of survival and analysis of prognostic factors for patients with AFP negative hepatocellular carcinoma: a population-based study. BMC Gastroenterol 2024; 24:93. [PMID: 38438972 PMCID: PMC10910698 DOI: 10.1186/s12876-024-03185-z] [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: 07/27/2023] [Accepted: 02/20/2024] [Indexed: 03/06/2024] Open
Abstract
PURPOSE Hepatocellular carcinoma (HCC) has a poor prognosis, and alpha-fetoprotein (AFP) is widely used to evaluate HCC. However, the proportion of AFP-negative individuals cannot be disregarded. This study aimed to establish a nomogram of risk factors affecting the prognosis of patients with AFP-negative HCC and to evaluate its diagnostic efficiency. PATIENTS AND METHODS Data from patients with AFP-negative initial diagnosis of HCC (ANHC) between 2004 and 2015 were collected from the Surveillance, Epidemiology, and End Results database for model establishment and validation. We randomly divided overall cohort into the training or validation cohort (7:3). Univariate and multivariate Cox regression analysis were used to identify the risk factors. We constructed nomograms with overall survival (OS) and cancer-specific survival (CSS) as clinical endpoint events and constructed survival analysis by using Kaplan-Meier curve. Also, we conducted internal validation with Receiver Operating Characteristic (ROC) analysis and Decision curve analysis (DCA) to validate the clinical value of the model. RESULTS This study included 1811 patients (1409 men; 64.7% were Caucasian; the average age was 64 years; 60.7% were married). In the multivariate analysis, the independent risk factors affecting prognosis were age, ethnicity, year of diagnosis, tumor size, tumor grade, surgery, chemotherapy, and radiotherapy. The nomogram-based model related C-indexes were 0.762 (95% confidence interval (CI): 0.752-0.772) and 0.752 (95% CI: 0.740-0.769) for predicting OS, and 0.785 (95% CI: 0.774-0.795) and 0.779 (95% CI: 0.762-0.795) for predicting CSS. The nomogram model showed that the predicted death was consistent with the actual value. The ROC analysis and DCA showed that the nomogram had good clinical value compared with TNM staging. CONCLUSION The age(HR:1.012, 95% CI: 1.006-1.018, P-value < 0.001), ethnicity(African-American: HR:0.946, 95% CI: 0.783-1.212, P-value: 0.66; Others: HR:0.737, 95% CI: 0.613-0.887, P-value: 0.001), tumor diameter(HR:1.006, 95% CI: 1.004-1.008, P-value < 0.001), year of diagnosis (HR:0.852, 95% CI: 0.729-0.997, P-value: 0.046), tumor grade(Grade 2: HR:1.124, 95% CI: 0.953-1.326, P-value: 0.164; Grade 3: HR:1.984, 95% CI: 1.574-2.501, P-value < 0.001; Grade 4: HR:2.119, 95% CI: 1.115-4.027, P-value: 0.022), surgery(Liver Resection: HR:0.193, 95% CI: 0.160-0.234, P-value < 0.001; Liver Transplant: HR:0.102, 95% CI: 0.072-0.145, P-value < 0.001), chemotherapy(HR:0.561, 95% CI: 0.471-0.668, P-value < 0.001), and radiotherapy(HR:0.641, 95% CI: 0.463-0.887, P-value:0.007) were independent prognostic factors for patients with ANHC. We developed a nomogram model for predicting the OS and CSS of patients with ANHC, with a good predictive performance.
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Affiliation(s)
- Chengyu Liu
- Graduate School of Hebei Medical University, Shijiazhuang, Hebei, China
- Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University, 169 Tianshan Street, Shijiazhuang, Hebei, China
- Xingtai Key Laboratory of Precision Medicine for Liver Cirrhosis and Portal Hypertension, Xingtai People's Hospital of Hebei Medical University, Xingtai, Hebei, China
| | - Zikang Li
- Graduate School of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Zhilei Zhang
- Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University, 169 Tianshan Street, Shijiazhuang, Hebei, China
| | - Jinlong Li
- Xingtai Key Laboratory of Precision Medicine for Liver Cirrhosis and Portal Hypertension, Xingtai People's Hospital of Hebei Medical University, Xingtai, Hebei, China
| | - Congxi Xu
- Graduate School of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Yuming Jia
- Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University, 169 Tianshan Street, Shijiazhuang, Hebei, China
| | - Chong Zhang
- Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University, 169 Tianshan Street, Shijiazhuang, Hebei, China
| | - Wuhan Yang
- Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University, 169 Tianshan Street, Shijiazhuang, Hebei, China
| | - Wenchuan Wang
- Xingtai Key Laboratory of Precision Medicine for Liver Cirrhosis and Portal Hypertension, Xingtai People's Hospital of Hebei Medical University, Xingtai, Hebei, China
| | - Xiaojuan Wang
- Xingtai Key Laboratory of Precision Medicine for Liver Cirrhosis and Portal Hypertension, Xingtai People's Hospital of Hebei Medical University, Xingtai, Hebei, China
| | - Kuopeng Liang
- Xingtai Key Laboratory of Precision Medicine for Liver Cirrhosis and Portal Hypertension, Xingtai People's Hospital of Hebei Medical University, Xingtai, Hebei, China
| | - Li Peng
- Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University, 169 Tianshan Street, Shijiazhuang, Hebei, China.
| | - Jitao Wang
- Xingtai Key Laboratory of Precision Medicine for Liver Cirrhosis and Portal Hypertension, Xingtai People's Hospital of Hebei Medical University, Xingtai, Hebei, China.
- Hebei Provincial Key Laboratory of Cirrhosis & Portal Hypertension, 145 Xinhua North Road, Xingtai, Hebei, China.
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Kang X, Liu X, Li Y, Yuan W, Xu Y, Yan H. Development and evaluation of nomograms and risk stratification systems to predict the overall survival and cancer-specific survival of patients with hepatocellular carcinoma. Clin Exp Med 2024; 24:44. [PMID: 38413421 PMCID: PMC10899391 DOI: 10.1007/s10238-024-01296-1] [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: 12/03/2023] [Accepted: 01/13/2024] [Indexed: 02/29/2024]
Abstract
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and patients with HCC have a poor prognosis and low survival rates. Establishing a prognostic nomogram is important for predicting the survival of patients with HCC, as it helps to improve the patient's prognosis. This study aimed to develop and evaluate nomograms and risk stratification to predict overall survival (OS) and cancer-specific survival (CSS) in HCC patients. Data from 10,302 patients with initially diagnosed HCC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Patients were randomly divided into the training and validation set. Kaplan-Meier survival, LASSO regression, and Cox regression analysis were conducted to select the predictors of OS. Competing risk analysis, LASSO regression, and Cox regression analysis were conducted to select the predictors of CSS. The validation of the nomograms was performed using the concordance index (C-index), the Akaike information criterion (AIC), the Bayesian information criterion (BIC), Net Reclassification Index (NRI), Discrimination Improvement (IDI), the receiver operating characteristic (ROC) curve, calibration curves, and decision curve analyses (DCAs). The results indicated that factors including age, grade, T stage, N stage, M stage, surgery, surgery to lymph node (LN), Alpha-Fetal Protein (AFP), and tumor size were independent predictors of OS, whereas grade, T stage, surgery, AFP, tumor size, and distant lymph node metastasis were independent predictors of CSS. Based on these factors, predictive models were built and virtualized by nomograms. The C-index for predicting 1-, 3-, and 5-year OS were 0.788, 0.792, and 0.790. The C-index for predicting 1-, 3-, and 5-year CSS were 0.803, 0.808, and 0.806. AIC, BIC, NRI, and IDI suggested that nomograms had an excellent predictive performance with no significant overfitting. The calibration curves showed good consistency of OS and CSS between the actual observation and nomograms prediction, and the DCA showed great clinical usefulness of the nomograms. The risk stratification of OS and CSS was built that could perfectly classify HCC patients into three risk groups. Our study developed nomograms and a corresponding risk stratification system predicting the OS and CSS of HCC patients. These tools can assist in patient counseling and guiding treatment decision making.
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Affiliation(s)
- Xichun Kang
- Department of Epidemiology and Health Statistics, School of Public Health, Hebei Medical University, Shijiazhuang, 050017, China
| | - Xiling Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yaoqi Li
- Department of Epidemiology and Health Statistics, School of Public Health, Hebei Medical University, Shijiazhuang, 050017, China
| | - Wenfang Yuan
- Department of the Sixth Infection, The Fifth Hospital of Shijiazhuang, Shijiazhuang, 050021, China
| | - Yi Xu
- Department of Laboratory Medicine, The Fifth Hospital of Shijiazhuang, Shijiazhuang, 050021, China
| | - Huimin Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Hebei Medical University, Shijiazhuang, 050017, China.
- Clinical Research Center, The Fifth Hospital of Shijiazhuang, Shijiazhuang, 050021, China.
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Li X, Fan Y, Tong J, Lou M. Risk factors, prognostic factors, and nomograms for distant metastases in patients with gastroenteropancreatic neuroendocrine tumors: a population-based study. Front Endocrinol (Lausanne) 2024; 15:1264952. [PMID: 38449852 PMCID: PMC10916283 DOI: 10.3389/fendo.2024.1264952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 01/29/2024] [Indexed: 03/08/2024] Open
Abstract
Background Patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs) have a poor prognosis for distant metastasis. Currently, there are no studies on predictive models for the risk of distant metastasis in GEP-NETs. Methods In this study, risk factors associated with metastasis in patients with GEP-NETs in the Surveillance, Epidemiology, and End Results (SEER) database were analyzed by univariate and multivariate logistic regression, and a nomogram model for metastasis risk prediction was constructed. Prognostic factors associated with distant metastasis in patients with GEP-NETs were analyzed by univariate and multivariate Cox, and a nomogram model for prognostic prediction was constructed. Finally, the performance of the nomogram model predictions is validated by internal validation set and external validation set. Results A total of 9145 patients with GEP-NETs were enrolled in this study. Univariate and multivariate logistic analysis demonstrated that T stage, N stage, tumor size, primary site, and histologic types independent risk factors associated with distant metastasis in GEP-NETs patients (p value < 0.05). Univariate and multivariate Cox analyses demonstrated that age, histologic type, tumor size, N stage, and primary site surgery were independent factors associated with the prognosis of patients with GEP-NETs (p value < 0.05). The nomogram model constructed based on metastasis risk factors and prognostic factors can predict the occurrence of metastasis and patient prognosis of GEP-NETs very effectively in the internal training and validation sets as well as in the external validation set. Conclusion In conclusion, we constructed a new distant metastasis risk nomogram model and a new prognostic nomogram model for GEP-NETs patients, which provides a decision-making reference for individualized treatment of clinical patients.
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Affiliation(s)
- Xinwei Li
- Department of Gastroenterology, Affiliated Cancer Hospital of Bengbu Medical College, Bengbu, China
| | - Yongfei Fan
- Department of Thoracic Surgery, The Affiliated Changzhou Second People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Jichun Tong
- Department of Thoracic Surgery, The Affiliated Changzhou Second People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Ming Lou
- Department of Thoracic Surgery, The Affiliated Changzhou Second People’s Hospital of Nanjing Medical University, Changzhou, China
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Qiao W, Li J, Wang Q, Jin R, Zhang H. Development and Validation of a Prognostic Nomogram for Patients with AFP and DCP Double-Negative Hepatocellular Carcinoma After Local Ablation. J Hepatocell Carcinoma 2024; 11:271-284. [PMID: 38333222 PMCID: PMC10849917 DOI: 10.2147/jhc.s442366] [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: 11/02/2023] [Accepted: 01/26/2024] [Indexed: 02/10/2024] Open
Abstract
Purpose Although alpha-fetoprotein (AFP) and des-gamma-carboxyprothrombin (DCP) have a certain predictive ability for the prognosis of hepatocellular carcinoma (HCC), there are still some cases of aggressive recurrence among patients with AFP and DCP double-negative HCC (DNHC) after local ablation. However, prediction models to forecast the prognosis of DNHC patients are still lacking. Thus, this retrospective study aims to explore the prognostic factors in DNHC patients and develop a nomogram to predict recurrence. Patients and methods 493 DNHC patients who underwent the local ablation at Beijing You'an Hospital between January 1, 2014, and December 31, 2022, were enrolled. A part that was admitted from January 1, 2014, to December 31, 2018, was designated to the training cohort (n = 307); others from January 1, 2019, to December 31, 2022, were allocated to the validation cohort (n = 186). Lasso regression and Cox regression were employed with the aim of screening risk factors and developing the nomogram. The nomogram outcome was assessed by discrimination, calibration, and decision curve analysis (DCA). Results Independent prognostic factors selected by Lasso-Cox analysis included age, tumor size, tumor number, and gamma-glutamyl transferase. The area under the receiver operating characteristic (ROC) curves (AUCs) of the training and validation groups (0.738, 0.742, 0.836, and 0.758, 0.821) exhibited the excellent predicted outcome of the nomogram. Calibration plots and DCA plots suggest desirable calibration performance and clinical utility. Patients were stratified into three risk groups by means of the nomogram: low-risk, intermediate-risk, and high-risk, respectively. There exists an obvious distinction in recurrence-free survival (RFS) among three groups (p<0.0001). Conclusion In conclusion, we established and validated a nomogram for DNHC patients who received local ablation. The nomogram showed excellent predictive power for the recurrence of HCC and could contribute to guiding clinical decisions.
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Affiliation(s)
- Wenying Qiao
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, People’s Republic of China
- Beijing Di’tan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
| | - Jiashuo Li
- Beijing Di’tan Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Qi Wang
- Beijing Di’tan Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Ronghua Jin
- Beijing Di’tan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
| | - Honghai Zhang
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, People’s Republic of China
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Han R, Gan L, Lang M, Li G, Chen L, Tian X, Zhu K, Sun L, Song T. A Retrospective Study on Predicting Recurrence of Intermediate-Stage Hepatocellular Carcinoma After Radical Therapy. J Hepatocell Carcinoma 2024; 11:51-64. [PMID: 38230268 PMCID: PMC10790591 DOI: 10.2147/jhc.s449441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 01/05/2024] [Indexed: 01/18/2024] Open
Abstract
Purpose This study aimed to investigate the potential benefits of radical therapy in patients with stage B disease. Patients and Methods A retrospective analysis was conducted on a cohort of 437 patients diagnosed with stage B hepatocellular carcinoma, who underwent either hepatic resection (HR) or radiofrequency ablation (RFA) at the Cancer Institute and Hospital of Tianjin Medical University from May 2011 to May 2022. Multivariate COX regression analysis was performed to identify the independent prognostic factors related to recurrence-free survival (RFS). The performance of the developed nomogram was evaluated using various statistical measures, including the concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results Multivariate analysis revealed that tumor diameter, number of tumors, number of involved liver segments, alpha-fetoprotein (AFP), carbohydrate antigen 19-9 (CA19-9), lactate dehydrogenase (LDH), and systemic immune inflammation index (SII) were independent prognostic factors influencing patients' RFS, and these factors were incorporated into the nomogram. The C-index of the nomogram in the training cohort was 0.721, and the AUC at 2 and 3 years was 0.772 and 0.790, respectively. These values were appreciably higher than commonly used clinic staging systems and other predictive models. The calibration curve and DCA demonstrated good calibration and net benefit. Survival analysis comparing stage B patients who received radical treatment with stage A patients with multiple lesions did not reveal a significant difference in Kaplan-Meier survival curves (P=0.91). Conclusion The nomogram provided a precise prediction of the recurrence for stage B hepatocellular carcinoma patients undergoing radical treatment. Furthermore, certain stage B patients may benefit from radical treatment.
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Affiliation(s)
- Ruyu Han
- Department of Hepatobiliary Cancer, Liver Cancer Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, 300060, People’s Republic of China
| | - Leijuan Gan
- Department of Hepatobiliary Cancer, Liver Cancer Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, 300060, People’s Republic of China
| | - Mengran Lang
- Department of Hepatobiliary Cancer, Liver Cancer Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, 300060, People’s Republic of China
| | - Guangtao Li
- Department of Hepatobiliary Cancer, Liver Cancer Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, 300060, People’s Republic of China
| | - Lu Chen
- Department of Hepatobiliary Cancer, Liver Cancer Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, 300060, People’s Republic of China
| | - Xindi Tian
- Department of Hepatobiliary Cancer, Liver Cancer Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, 300060, People’s Republic of China
| | - Kangwei Zhu
- Department of Hepatobiliary Cancer, Liver Cancer Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, 300060, People’s Republic of China
| | - Liyu Sun
- Department of Hepatobiliary Cancer, Liver Cancer Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, 300060, People’s Republic of China
| | - Tianqiang Song
- Department of Hepatobiliary Cancer, Liver Cancer Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, 300060, People’s Republic of China
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Kuang T, Ma W, Zhang J, Yu J, Deng W, Dong K, Wang W. Construction of a Nomogram to Predict Overall Survival in Patients with Early-Onset Hepatocellular Carcinoma: A Retrospective Cohort Study. Cancers (Basel) 2023; 15:5310. [PMID: 38001570 PMCID: PMC10670167 DOI: 10.3390/cancers15225310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 10/31/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a widespread and impactful cancer which has pertinent implications worldwide. Although most cases of HCC are typically diagnosed in individuals aged ≥60 years, there has been a notable rise in the occurrence of HCC among younger patients. However, there is a scarcity of precise prognostic models available for predicting outcomes in these younger patients. A retrospective analysis was conducted to investigate early-onset hepatocellular carcinoma (EO-LIHC) using data from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2018. The analysis included 1392 patients from the SEER database and our hospital. Among them, 1287 patients from the SEER database were assigned to the training cohort (n = 899) and validation cohort 1 (n = 388), while 105 patients from our hospital were assigned to validation cohort 2. A Cox regression analysis showed that age, sex, AFP, grade, stage, tumor size, surgery, and chemotherapy were independent risk factors. The nomogram developed in this study demonstrated its discriminatory ability to predict the 1-, 3-, and 5-year overall survival (OS) rates in EO-LIHC patients based on individual characteristics. Additionally, a web-based OS prediction model specifically tailored for EO-LIHC patients was created and validated. Overall, these advancements contribute to improved decision-making and personalized care for individuals with EO-LIHC.
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Affiliation(s)
- Tianrui Kuang
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Wangbin Ma
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Jiacheng Zhang
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Jia Yu
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Wenhong Deng
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Keshuai Dong
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Weixing Wang
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan 430060, China
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Qin Z, Hu Z, Huang B, Wang F, Pan H, He X, Yin L. Construction and application of dynamic online nomogram for prognosis prediction of patients with advanced (Stage III/IV) tongue squamous cell carcinoma. JOURNAL OF STOMATOLOGY, ORAL AND MAXILLOFACIAL SURGERY 2023; 124:101477. [PMID: 37080357 DOI: 10.1016/j.jormas.2023.101477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 04/17/2023] [Indexed: 04/22/2023]
Abstract
OBJECTIVES The prognosis of patients with advanced tongue squamous cell carcinoma (ATSCC) is poor, and their overall survival (OS) is relatively short. Currently, the TNM stage system is often used clinically to assess the prognosis of patients, but the evaluation index of the TNM stage system is relatively single and does not specifically demonstrate relevant prognostic data. Therefore, the purpose of this study was to construct a dynamic online nomogram for predicting the prognosis of patients with ATSCC and to provide some reference for personalized clinical treatment of patients. METHODS Clinical and prognostic information on patients with pathologically confirmed ATSCC from 2000 to 2018 was extracted from the SEER database and randomly divided into a training cohort and a validation cohort in a 7:3 ratio. Multifactorial and univariate Cox regression analyses were used to identify prognostic risk factors. Dynamic online nomogram were constructed using R software. Area under the curve (AUC), C-index, calibration curve, and decision curve analysis (DCA) with time-dependent ROC curves were used to assess the clinical utility of the nomogram. Kaplan-Meier survival curves were used to compare the prognosis of different patient categories. RESULTS A total of 3828 patients with ATSCC were screened in the SEER database.Age,race, primary site, AJCC T,N and M stage, lymph nodes surgery, radiotherapy, chemotherapy and marital status were independent influences on OS(P < 0.05). In the training cohort, the C-index of the OS-related line plot was 0.733 and the AUC for predicting 3-year OS was 0.867. In the validation cohort, the C-index was 0.738 and the AUC for 3-year OS was 0.899. Calibration plots and DCA curves showed good predictive performance of the model in both the training and validation cohorts. Kaplan-Meier survival curves showed that chemotherapy, lymph nodes surgery,married,primary site(tongue base) and radiotherapy had better OS than the non-chemotherapy, non-surgery, single, primary site(tongue anterior), and non-radiotherapy groups, respectively (all P < 0.05). CONCLUSION The established dynamic online nomogram has good predictive performance, which helps to personalize and combine the actual clinical patients to comprehensively predict the prognosis of ATSCC patients and may have better clinical application than the TNM stage system.
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Affiliation(s)
- Zishun Qin
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China; School/Hospital of Stomatology, Lanzhou university, Lanzhou 730000, China
| | - Zonghao Hu
- School/Hospital of Stomatology, Lanzhou university, Lanzhou 730000, China
| | - Benheng Huang
- School/Hospital of Stomatology, Lanzhou university, Lanzhou 730000, China
| | - Feng Wang
- School/Hospital of Stomatology, Lanzhou university, Lanzhou 730000, China
| | - Hongwei Pan
- School/Hospital of Stomatology, Lanzhou university, Lanzhou 730000, China
| | - Xuxia He
- School/Hospital of Stomatology, Lanzhou university, Lanzhou 730000, China; The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China
| | - Lihua Yin
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China; School/Hospital of Stomatology, Lanzhou university, Lanzhou 730000, China.
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Ma C, Jin Y, Wang Y, Xu H, Zhang J. Beyond liver cancer, more application scenarios for alpha-fetoprotein in clinical practice. Front Oncol 2023; 13:1231420. [PMID: 37781207 PMCID: PMC10540843 DOI: 10.3389/fonc.2023.1231420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 08/28/2023] [Indexed: 10/03/2023] Open
Abstract
Alpha-fetoprotein (AFP) is a commonly used clinical biomarker. Before 1970, the two-way agar diffusion method was mainly used, and the specificity of AFP in the diagnosis of primary liver cancer was satisfactory. However, its positivity rate was not very high. The diagnostic value of AFP is changing with the evolution of detection methods. Here, we performed a literature search to identify English-language publications. The search was performed from January 2015 to April 2023 using the PubMed database and the following terms in [Titles/Abstracts]: alpha-fetoprotein, clinical practice, detection, etc. The references of retrieved articles were also screened to broaden the search. Studies referring to liver cancer and AFP detection methods were excluded. In this review, several clinical application scenarios for AFP were systematically reviewed, and its potential detection value in the future was discussed.
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Affiliation(s)
- Chenyu Ma
- Department of Laboratory Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Yuexinzi Jin
- Department of Laboratory Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Yuhan Wang
- Center of Smart Laboratory and Molecular Medicine, School of Medicine, Chongqing University, Chongqing, China
| | - Huaguo Xu
- Department of Laboratory Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Jiexin Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
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Qin Z, Hu Z, Lai M, Wang F, Liu X, Yin L. A nomogram for predicting survival in Patients with oral tongue keratinized squamous cell carcinoma: A SEER-based study. JOURNAL OF STOMATOLOGY, ORAL AND MAXILLOFACIAL SURGERY 2023; 124:101422. [PMID: 36781109 DOI: 10.1016/j.jormas.2023.101422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 02/06/2023] [Accepted: 02/08/2023] [Indexed: 02/13/2023]
Abstract
OBJECTIVE Oral tongue keratinized squamous cell carcinoma (OTKSCC), a relatively rare form of tongue cancer (TC) in clinical practice, accompanied by features of cell keratosis, is an uncommon histological subtype. However, its specific clinicopathological features and prognosis have not been adequately described. In this study, we aimed to create a nomogram using R language software to predict overall survival (OS) of patients with OTKSCC to assess the prognosis of OTKSCC patients. METHODS We extracted clinical and related prognostic data of OTKSCC patients from 1975 to 2019 from the Surveillance, Epidemiology, and End Results database. Independent prognostic factors were selected using univariate and multivariate Cox analyses, and a nomogram was constructed using R software. The C-index, area under the curve (AUC) of receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA) were used to assess the clinical utility of the nomogram. Finally, OS was assessed using the Kaplan-Meier method. RESULTS A total of 2450 OTKSCC patients were included in the study. Univariate and multivariate Cox regression analyses were used to identify age, T stage, N stage, surgery, and radiation therapy as independent risk factors (p<0.05). In the training cohort, the calibration index of the nomogram was 0.725, while the AUC values for nomogram, age, T stage, N stage, surgery and radiation therapy were 0.878, 0.639, 0.781, 0.661, 0.724 and 0.354, respectively. At the same time, in the verification queue, the calibration index of the nomogram was 0.726, while the AUC values for nomogram, age, T stage, N stage, surgery and radiation therapy were 0.859,0.612,0.826,0.675,0.758 and 0.303, respectively. Ideal uniformity of the models from the training and validation cohorts was demonstrated in the calibration and DCA curves. Univariate survival analysis showed that age, T stage, N stage, surgery, and radiotherapy were statistically significant for prognosis (p<0.05). CONCLUSION Age, T stage, N stage, surgery, and radiation therapy are independently associated with the OS, and the established nomogram is an effective visualization tool for predicting the OS of OTKSCC patients.
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Affiliation(s)
- Zishun Qin
- The First Clinical Medical College, Lanzhou University, Lanzhou,730000, China; School/Hospital of Stomatology, Lanzhou university, Lanzhou,730000, China.
| | - Zonghao Hu
- School/Hospital of Stomatology, Lanzhou university, Lanzhou,730000, China.
| | - Minqin Lai
- School/Hospital of Stomatology, Lanzhou university, Lanzhou,730000, China.
| | - Feng Wang
- School/Hospital of Stomatology, Lanzhou university, Lanzhou,730000, China
| | - Xiaoyuan Liu
- School/Hospital of Stomatology, Lanzhou university, Lanzhou,730000, China
| | - Lihua Yin
- The First Clinical Medical College, Lanzhou University, Lanzhou,730000, China; School/Hospital of Stomatology, Lanzhou university, Lanzhou,730000, China.
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Sun Y, Xiong Y, Wang Q, Qiao W, Zhang H, Zhang Y. Development and validation of a nomogram to predict the recurrence of hepatocellular carcinoma patients with dynamic changes in AFP undergoing locoregional treatments. Front Oncol 2023; 13:1206345. [PMID: 37700838 PMCID: PMC10494718 DOI: 10.3389/fonc.2023.1206345] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 08/14/2023] [Indexed: 09/14/2023] Open
Abstract
Background Serum alpha-fetoprotein (AFP) is an important clinical indicator for screening, diagnosis, and prognosis of primary hepatocellular carcinoma (HCC). Our team's previous study showed that patients with negative AFP at baseline and positive AFP at relapse had a worse prognosis (N-P). Therefore, the aim of our study was to develop and validate a nomogram for this group of patients. Methods A total of 513 patients with HCC who received locoregional treatments at Beijing You'an Hospital, Capital Medical University, from January 2012 to December 2019 were prospectively enrolled. Patients admitted from 2012 to 2015 were assigned to the training cohort (n = 335), while 2016 to 2019 were in the validation cohort (n =183). The clinical and pathological features of patients were collected, and independent risk factors were identified using univariate and multivariate Cox regression analysis as a basis for developing a nomogram. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) curves in the training and validation cohorts. Results The content of the nomogram includes gender, tumor number, tumor size, lymphocyte, direct bilirubin (DBIL), gamma-glutamyl transferase (GGT), and prealbumin. The C-index (0.717 and 0.752) and 1-, 3-, and 5-year AUCs (0.721, 0.825, 0.845, and 0.740, 0.868, 0.837) of the training and validation cohorts proved the good predictive performance of the nomogram. Calibration curves and DCA curves suggested accuracy and net clinical benefit rates. The nomogram enabled to classify of patients with dynamic changes in AFP into three groups according to the risk of recurrence: low risk, intermediate risk, and high risk. There was a statistically significant difference in RFS between the three groups in the training and validation cohorts (P<0.001). Conclusion The nomogram developed and validated in this study had good predictive power for patients with dynamic changes in AFP.
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Affiliation(s)
- Yu Sun
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Yiqi Xiong
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Qi Wang
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Wenying Qiao
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Honghai Zhang
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Yonghong Zhang
- Interventional Therapy Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing, China
- Research Center for Biomedical Resources, Beijing You’an Hospital, Capital Medical University, Beijing, China
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Wu JL, Luo JY, Jiang ZB, Huang SB, Chen GR, Ran HY, Liang QY, Huang MS, Lai LS, Chen JW. Inflammation-related nomogram for predicting survival of patients with unresectable hepatocellular carcinoma received conversion therapy. World J Gastroenterol 2023; 29:3168-3184. [PMID: 37346152 PMCID: PMC10280795 DOI: 10.3748/wjg.v29.i20.3168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 04/02/2023] [Accepted: 04/24/2023] [Indexed: 05/26/2023] Open
Abstract
BACKGROUND The efficacy of conversion therapy for patients with unresectable hepatocellular carcinoma (HCC) is a common clinical concern.
AIM To analyse the prognostic factors of overall survival (OS) in patients with unresectable HCC who received conversion therapy.
METHODS One hundred and fifty patients who met the inclusion criteria were enrolled and divided into a training cohort (n = 120) and a validation cohort (n = 30). Using the independent risk factors in the training cohort, a nomogram model was constructed to predict OS for patients treated with transarterial chemoembolization following hepatic resection. The nomogram was internally validated with the bootstrapping method. The predictive performance of nomogram was assessed by Harrell’s concordance index (C-index), calibration plot and time-dependent receiver operating characteristic curves and compared with six other conventional HCC staging systems.
RESULTS Multivariate Cox analysis identified that albumin, blood urea nitrogen, gamma-glutamyl transpeptidase to platelet ratio, platelet to lymphocyte ratio, macrovascular invasion and tumour number were the six independent prognostic factors correlated with OS in nomogram model. The C-index in the training cohort and validation cohort were 0.752 and 0.807 for predicting OS, which were higher than those of the six conventional HCC staging systems (0.563 to 0.715 for the training cohort and 0.458 to 0.571 for the validation cohort). The calibration plots showed good consistency between the nomogram prediction of OS and the actual observations of OS. Decision curve analyses indicated satisfactory clinical utility. With a total nomogram score of 196, patients were accurately classified into low-risk and high-risk groups. Furthermore, we have deployed the model into online calculators that can be accessed for free at https://ctmodelforunresectablehcc.shinyapps.io/DynNomapp/.
CONCLUSION The nomogram achieved optimal individualized prognostication of OS in HCC patients who received conversion therapy, which could be a useful clinical tool to help guide postoperative personalized interventions and prognosis judgement.
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Affiliation(s)
- Jia-Lin Wu
- Department of Interventional Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, Guangdong Province, China
| | - Jun-Yang Luo
- Department of Interventional Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, Guangdong Province, China
| | - Zai-Bo Jiang
- Department of Interventional Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, Guangdong Province, China
| | - Si-Bo Huang
- The First Clinical Medical College, Guangdong Medical University, Zhanjiang 524000, Guangdong Province, China
| | - Ge-Run Chen
- The First Clinical Medical College, Guangdong Medical University, Zhanjiang 524000, Guangdong Province, China
| | - Hui-Ying Ran
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, Guangdong Province, China
| | - Qi-Yue Liang
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, Guangdong Province, China
| | - Ming-Sheng Huang
- Department of Interventional Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, Guangdong Province, China
| | - Li-Sha Lai
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou 510010, Guangdong Province, China
| | - Jun-Wei Chen
- Department of Interventional Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, Guangdong Province, China
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An S, Zhan X, Liu M, Li L, Wu J. Diagnostic and Prognostic Nomograms for Hepatocellular Carcinoma Based on PIVKA-II and Serum Biomarkers. Diagnostics (Basel) 2023; 13:diagnostics13081442. [PMID: 37189543 DOI: 10.3390/diagnostics13081442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/06/2023] [Accepted: 04/07/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND The aim of the present study was to develop an improved diagnostic and prognostic model for HBV-associated HCC by combining AFP with PIVKA-II and other potential serum/plasma protein biomarkers. METHODS A total of 578 patients, including 352 patients with HBV-related HCC, 102 patients with HBV-associated liver cirrhosis (LC), 124 patients with chronic HBV, and 127 healthy subjects (HS), were enrolled in the study. The serum levels of AFP, PIVKA-II, and other laboratory parameters were collected. Univariate and multivariate logistic regression and Cox regression analyses were performed to identify independent diagnostic and prognostic factors, respectively. The diagnostic efficacy of the nomogram was evaluated using receiver operator curve (ROC) analysis and the prognostic performance was measured by Harrell's concordance index (C-index). RESULTS AFP and PIVKA-II levels were significantly increased in HBV-related HCC, compared with those in HBV-associated LC and chronic HBV participants (p < 0.05 and p < 0.001, respectively). The diagnostic nomogram, which included age, gender, AFP, PIVKA-II, prothrombin time (PT), and total protein (TP), discriminated patients with HBV-HCC from those with HBV-LC or chronic HBV with an AUC of 0.970. In addition, based on the univariate and multivariate Cox regression analysis, PIVKA-II, γ-glutamyl transpeptidase, and albumin were found to be significantly associated with the prognosis of HBV-related HCC and were incorporated into a nomogram. The C-index of the nomogram for predicting 3-year survival in the training and validation groups was 0.75 and 0.78, respectively. The calibration curves for the probability of 3-year OS showed good agreement between the nomogram prediction and the actual observation in the training and the validation groups. Furthermore, the nomogram had a higher C-index (0.74) than that of the Child-Pugh grade (0.62), the albumin-bilirubin (ALBI) score (0.64), and Barcelona Clinic Liver Cancer (0.56) in all follow-up cases. CONCLUSION Our study suggests that the nomograms based on AFP, PIVKA-II, and potential serum protein biomarkers showed a better performance in the diagnosis and prognosis of HCC, which may help to guide therapeutic strategies and assess the prognosis of HCC.
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Affiliation(s)
- Shu An
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiaoxia Zhan
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - Min Liu
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - Laisheng Li
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - Jian Wu
- Center of Hepato-Pancreato-Biliary Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
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Wu Q, Zeng J, Zeng J. Inflammation-Related Marker NrLR Predicts Prognosis in AFP-Negative HCC Patients After Curative Resection. J Hepatocell Carcinoma 2023; 10:193-202. [PMID: 36789253 PMCID: PMC9922487 DOI: 10.2147/jhc.s393286] [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] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 01/20/2023] [Indexed: 02/10/2023] Open
Abstract
Background The role of inflammation-related markers in alpha-fetoprotein (AFP) negative hepatocellular carcinoma (HCC) is not well known. This study aimed to investigate the clinical significance of inflammation-related markers in AFP-negative HCC patients after curative resection. Methods One thousand one hundred and seventy-nine AFP-negative HCC patients after curative resection were included. Survival rate and prognostic analysis were performed using Kaplan-Meier and Cox regression analysis. Propensity score matching (PSM) was used for patient selection. Results Multivariate Cox regression showed that neutrophil times γ-glutamyl transpeptidase to lymphocyte ratio (NrLR) was the independent risk factor associated with OS (p = 0.002) and RFS (p = 0.017). Low NrLR groups (n = 628) had lower rates of albumin-bilirubin (ALBI) grade 2 (p < 0.001), lower rates of bleeding and blood transfusion (p < 0.001) than high NrLR groups. Considering tumor features, low NrLR groups had lower AFP levels (p < 0.001), smaller tumor size (p < 0.001), and lower rates of Edmondson grade III-IV (p = 0.024) than high NrLR groups. After PSM, the 1-year, 3 year-, and 5-year OS rates in the low NrLR and high NrLR groups were 96.3%, 86.9%, 64.9%, and 91.4%, 76.7%, 59.5% (p < 0.001), respectively. The 1-year, 3-year, and 5-year RFS rates in the low NrLR and high NrLR groups were 80.0%, 62.9%, 47.5%, and 71.7%, 52.6%, 39.5% (p < 0.001), respectively. Conclusion NrLR was a poor prognostic factor for mortality and tumor recurrence in AFP-negative HCC patients after curative resection. The simple and low-cost marker could help physician to determine patients at high risk of tumor recurrence for frequent clinical surveillance.
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Affiliation(s)
- Qionglan Wu
- Department of Pathology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China,Hepatobiliary Medical Center of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China
| | - Jinhua Zeng
- Hepatobiliary Medical Center of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China,Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China,Department of Hepatobiliary Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China
| | - Jianxing Zeng
- Hepatobiliary Medical Center of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China,Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, Fujian, People’s Republic of China,Correspondence: Jianxing Zeng, Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350005, People’s Republic of China, Tel/Fax +86 591 8811 6010, Email
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Xu L, Chen L, Zhang B, Liu Z, Liu Q, Liang H, Chen Y, Chen X, Leng C, Zhang B. Alkaline phosphatase combined with γ-glutamyl transferase is an independent predictor of prognosis of hepatocellular carcinoma patients receiving programmed death-1 inhibitors. Front Immunol 2023; 14:1115706. [PMID: 36761721 PMCID: PMC9905229 DOI: 10.3389/fimmu.2023.1115706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 01/09/2023] [Indexed: 01/27/2023] Open
Abstract
Background Immunotherapy plays an increasingly critical role in the systemic treatment of HCC. This current study aimed to establish a novel prognostic predictor of Programmed death 1 (PD-1) inhibitor therapy in hepatocellular carcinoma (HCC) independent of Child-Pugh grade. Methods Our study screened patients with HCC who received PD-1 inhibitors at Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology from January 2018 to December 2020. ALG grade was determined by the patient's serum ALP and GGT levels before the initiation of PD-1 inhibitors. The endpoints of our study were overall survival (OS) and progression free survival (PFS). Follow-up ended at May 31, 2022. Results Eighty- five patients (77 with Child-Pugh grade A, 8 with Child-Pugh grade B at baseline) were enrolled according to the inclusion criteria. Patients with Child-Pugh grade A achieved longer PFS and OS than those with Child-Pugh grade B. Patients with ALG grade 3 at baseline showed worse tumor response and poorer survival, and ALG grade could stratify patients with Child-Pugh grade A into subgroups with significantly different prognosis. Conclusions ALG grade, combining ALP and GGT, is a novel and readily available prognostic marker and the predictive effect of ALG grade on patient prognosis is independent of Child-Pugh grade.
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Affiliation(s)
- Lei Xu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Lin Chen
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Bin Zhang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhichen Liu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qiumeng Liu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huifang Liang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yifa Chen
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaoping Chen
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China,Department of Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China,*Correspondence: Xiaoping Chen, ; Chao Leng, ; Bixiang Zhang,
| | - Chao Leng
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China,*Correspondence: Xiaoping Chen, ; Chao Leng, ; Bixiang Zhang,
| | - Bixiang Zhang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China,*Correspondence: Xiaoping Chen, ; Chao Leng, ; Bixiang Zhang,
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Liu L, Wang Q, Zhao X, Huang Y, Feng Y, Zhang Y, Fang Z, Li S. Establishment and validation of nomogram model for the diagnosis of AFP-negative hepatocellular carcinoma. Front Oncol 2023; 13:1131892. [PMID: 36890811 PMCID: PMC9986420 DOI: 10.3389/fonc.2023.1131892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 02/07/2023] [Indexed: 02/22/2023] Open
Abstract
Introduction As one of the most common malignant tumors in clinical practice, hepatocellular carcinoma (HCC) is a major threat to human health, where alpha-fetoprotein (AFP) is widely used for early screening and diagnoses. However, the level of AFP would not elevate in about 30-40% of HCC patients, which is clinically referred to as AFP-negative HCC, with small tumors at an early stage and atypical imaging features, making it difficult to distinguish benign from malignant by imaging alone. Methods A total of 798 patients, with the majority being HBV-positive, were enrolled in the study and were randomized 2:1 to the training and validation groups. Univariate and multivariate binary logistic regression analyses were used to determine the ability of each parameter to predict HCC. A nomogram model was constructed based on the independent predictors. Results A unordered multicategorical logistic regression analyses showed that the age, TBIL, ALT, ALB, PT, GGT and GPR help identify non-hepatic disease, hepatitis, cirrhosis, and hepatocellular carcinoma. A multivariate logistic regression analyses showed that the gender, age, TBIL, GAR, and GPR were independent predictors for the diagnosis of AFP-negative HCC. And an efficient and reliable nomogram model (AUC=0.837) was constructed based on independent predictors. Discussion Serum parameters help reveal intrinsic differences between non-hepatic disease, hepatitis, cirrhosis, and HCC. The nomogram based on clinical and serum parameters could be used as a marker for the diagnosis of AFP-negative HCC, providing an objective basis for the early diagnosis and individualized treatment of hepatocellular carcinoma patients.
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Affiliation(s)
- Long Liu
- Department of Hepatobiliary Surgery, Taizhou Hospital of Zhejiang Province, Zhejiang University, Linhai, Zhejiang, China
| | - Qi Wang
- Department of Hepatobiliary Surgery, Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Linhai, Zhejiang, China
| | - Xiaohong Zhao
- Department of Pharmacy, Taizhou Hospital of Zhejiang Province, Zhejiang University, Linhai, Zhejiang, China
| | - Yuxi Huang
- Department of Hepatobiliary Surgery, Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Linhai, Zhejiang, China
| | - Yuyi Feng
- Department of Gastroenterology, Taizhou Hospital of Zhejiang Province, Linhai, Zhejiang, China
| | - Yu Zhang
- Department of Oncology, The First Hospital of the University of Science and Technology of China, Hefei, Anhui, China
| | - Zheping Fang
- Department of Hepatobiliary Surgery, Taizhou Hospital of Zhejiang Province, Zhejiang University, Linhai, Zhejiang, China.,Department of Hepatobiliary Surgery, Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Linhai, Zhejiang, China
| | - Shaowei Li
- Department of Gastroenterology, Taizhou Hospital of Zhejiang Province, Linhai, Zhejiang, China
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Yan T, Huang C, Lei J, Guo Q, Su G, Wu T, Jin X, Peng C, Cheng J, Zhang L, Liu Z, Kin T, Ying F, Liangpunsakul S, Li Y, Lu Y. Development and Validation of a nomogram for forecasting survival of alcohol related hepatocellular carcinoma patients. Front Oncol 2022; 12:976445. [PMID: 36439435 PMCID: PMC9692070 DOI: 10.3389/fonc.2022.976445] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 10/20/2022] [Indexed: 10/10/2023] Open
Abstract
BACKGROUND With the increasing incidence and prevalence of alcoholic liver disease, alcohol-related hepatocellular carcinoma has become a serious public health problem worthy of attention in China. However, there is currently no prognostic prediction model for alcohol-related hepatocellular carcinoma. METHODS The retrospective analysis research of alcohol related hepatocellular carcinoma patients was conducted from January 2010 to December 2014. Independent prognostic factors of alcohol related hepatocellular carcinoma were identified by Lasso regression and multivariate COX proportional model analysis, and the nomogram model was constructed. The reliability and accuracy of the model were assessed using the concordance index(C-Index), receiver operating characteristic (ROC) curve and calibration curve. Evaluate the clinical benefit and application value of the model through clinical decision curve analysis (DCA). The prognosis was assessed by the Kaplan-Meier (KM) survival curve. RESULTS In sum, 383 patients were included in our study. Patients were stochastically assigned to training cohort (n=271) and validation cohort (n=112) according to 7:3 ratio. The predictors included in the nomogram were splenectomy, platelet count (PLT), creatinine (CRE), Prealbumin (PA), mean erythrocyte hemoglobin concentration (MCHC), red blood cell distribution width (RDW) and TNM. Our nomogram demonstrated excellent discriminatory power (C-index) and good calibration at 1-year, 3-year and 5- year overall survival (OS). Compared to TNM and Child-Pugh model, the nomogram had better discriminative ability and higher accuracy. DCA showed high clinical benefit and application value of the model. CONCLUSION The nomogram model we established can precisely forcasting the prognosis of alcohol related hepatocellular carcinoma patients, which would be helpful for the early warning of alcohol related hepatocellular carcinoma and predict prognosis in patients with alcoholic hepatocellular carcinoma.
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Affiliation(s)
- Tao Yan
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Chenyang Huang
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Jin Lei
- The First Affiliated Hospital, Guizhou Medical University, Guiyang, China
| | - Qian Guo
- The First Affiliated Hospital, Guizhou Medical University, Guiyang, China
| | - Guodong Su
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Tong Wu
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Xueyuan Jin
- Medical Quality Control Department, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Caiyun Peng
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Jiamin Cheng
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Linzhi Zhang
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Zherui Liu
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Terence Kin
- Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China
| | - Fan Ying
- Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China
| | - Suthat Liangpunsakul
- Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Yinyin Li
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Yinying Lu
- Comprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China
- Center for Synthetic and Systems Biology (CSSB), Tsinghua University, Beijing, China
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Zhen J, Ke Y, Pan J, Zhou M, Zeng H, Song G, Yu Z, Fu B, Liu Y, Huang D, Wu H. ZNF320 is a hypomethylated prognostic biomarker involved in immune infiltration of hepatocellular carcinoma and associated with cell cycle. Aging (Albany NY) 2022; 14:8411-8436. [PMID: 36287187 PMCID: PMC9648795 DOI: 10.18632/aging.204350] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/03/2022] [Indexed: 11/26/2022]
Abstract
Hepatocellular carcinoma (HCC) is one of the most deadly and common malignant cancers around the world, and the prognosis of HCC patients is not optimistic. ZNF320 belongs to Krüppel like zinc finger gene family. However, no studies have focused on the influence of ZNF320 in HCC. We first analyzed ZNF320 expression in HCC by using data from TCGA and ICGC, then conducted a joint analysis with TIMER and UALCAN, and validated by immunohistochemistry in clinical HCC samples. Then we applied UALCAN to explore the correlation between ZNF320 expression and clinicopathological characteristics. Consequently, using Kaplan-Meier Plotter analysis and the Cox regression, we can predict the prognostic value of ZNF320 for HCC patients. Next, the analysis by GO, KEGG, and GSEA revealed that ZNF320 was significantly correlated to cell cycle and immunity. Finally, TIMER and GEPIA analysis verified that ZNF320 expression is closely related to tumor infiltrating immune cells (TIIC), including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. The analysis of the TCGA and ICGC data sets revealed that ZNF320 expression was significantly correlated with m6A related genes (RBMX, YTHDF1, and METTL3). In conclusion, ZNF320 may be a prognostic biomarker related to immunity as a candidate for liver cancer.
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Affiliation(s)
- Jing Zhen
- Second Affiliated Hospital of Nanchang University, Nanchang, China
- Second College of Clinical Medicine, Nanchang University, Nanchang, China
| | - Yun Ke
- Second College of Clinical Medicine, Nanchang University, Nanchang, China
| | - Jingying Pan
- Second College of Clinical Medicine, Nanchang University, Nanchang, China
| | - Minqin Zhou
- Second College of Clinical Medicine, Nanchang University, Nanchang, China
| | - Hong Zeng
- Second College of Clinical Medicine, Nanchang University, Nanchang, China
| | - Gelin Song
- Second College of Clinical Medicine, Nanchang University, Nanchang, China
| | - Zichuan Yu
- Second College of Clinical Medicine, Nanchang University, Nanchang, China
| | - Bidong Fu
- Second College of Clinical Medicine, Nanchang University, Nanchang, China
| | - Yue Liu
- Second College of Clinical Medicine, Nanchang University, Nanchang, China
| | - Da Huang
- Department of Thyroid Surgery, Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Honghu Wu
- Department of Science and Technology, Second Affiliated Hospital of Nanchang University, Nanchang, China
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Gu Z, Li X, Shi J, Wu Y, Zhang J, Zhang C, Yan H, Leng J. The Development of Predictive Nomogram of Recurrence for Patients With Endometrioma After Cystectomy Who Were Younger Than 45 Years Old and Received Postoperative Therapy. Front Med (Lausanne) 2022; 9:872481. [PMID: 35755050 PMCID: PMC9218256 DOI: 10.3389/fmed.2022.872481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 05/06/2022] [Indexed: 11/29/2022] Open
Abstract
Objective: This study aimed to establish an effective prognostic nomogram for the postoperative recurrence of endometrioma or endometriosis-related pain for patients with endometrioma after long-term follow-up, who were younger than 45 years old and received postoperative therapy. Methods The predictive nomogram was based on 323 patients who underwent cystectomy for endometrioma at Perking Union Medical College Hospital from January 2009 to April 2013, and the last follow-up occurred in September 2018. We collected information on all included patients, including preoperative data, intraoperative data, and long-term follow-up data after surgery. The Cox proportional hazards regression model was used to evaluate the prognostic effects of multiple clinical parameters on recurrence. The survival curve was depicted based on Kaplan-Meier method and compared by log-rank method. The Index of concordance (C-index) and calibration curves were used to access the discrimination ability and predictive accuracy of the nomogram respectively, and the results were further validated via bootstrap resampling. In addition, calculating the area under the curve (AUC) via risk scores of patients aimed to further access the prediction ability of the model. Results On multivariate analysis of derivation cohort, independent factors for recurrence such as dysmenorrhea degree, sum of both cyst diameters, presence of adenomyosis, and other essential factors for recurrence such as age at surgery, presence of uterine fibroids were all selected into the nomogram. The C-index of the nomogram for predicting recurrence was 0.683 (95% CI, 0.610- 0.755). The calibration curve for probability of recurrence for 7 years and 9 years showed great agreement between prediction by nomogram and actual observation. Furthermore, the AUCs of risk score for 7-year and 9-year were 0.680 and 0.790 respectively. Conclusion This research tried to develop the predictive nomogram of recurrence for patients with endometrioma after cystectomy. The C-index and calibration curve of nomogram, as well as the AUC of the nomogram was potential to predict the recurrence probability. In addition, this predictive nomogram needs external data sets to further validate its prognostic accuracy in the future.
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Affiliation(s)
- Zhiyue Gu
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China
| | - Xiaoyan Li
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China
| | - Jinghua Shi
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China
| | - Yushi Wu
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China
| | - Jing Zhang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China
| | - Chenyu Zhang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China
| | - Hailan Yan
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China
| | - Jinhua Leng
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China
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Shi H, Chen Z, Dong S, He R, Du Y, Qin Z, Zhou W. A nomogram for predicting survival in patients with advanced (stage III/IV) pancreatic body tail cancer: a SEER-based study. BMC Gastroenterol 2022; 22:279. [PMID: 35658912 PMCID: PMC9164315 DOI: 10.1186/s12876-022-02362-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/30/2022] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE Pancreatic body tail carcinoma (PBTC) is a relatively few pancreatic cancer in clinical practice, and its specific clinicopathological features and prognosis have not been fully described. In this study, we aimed to create a nomogram to predict the overall survival (OS) of patients with advanced PBTC. METHODS We extracted clinical and related prognostic data of advanced PBTC patients from 2000 to 2018 from the Surveillance, Epidemiology, and End Results database. Independent prognostic factors were selected using univariate and multivariate Cox analyses, and a nomogram was constructed using R software. The C-index, area under the curve (AUC) of receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA) were used to assess the clinical utility of the nomogram. Finally, OS was assessed using the Kaplan-Meier method. RESULTS A total of 1256 patients with advanced PBTC were eventually included in this study. Age, grade, N stage, M stage, surgery, and chemotherapy were identified as independent risk factors using univariate and multivariate Cox regression analyses (p < 0.05). In the training cohort, the calibration index of the nomogram was 0.709, while the AUC values of the nomogram, age, grade, N stage, M stage, surgery, and chemotherapy were 0.777, 0.562, 0.621, 0.5, 0.576, 0.632, and 0.323, respectively. Meanwhile, in the validation cohort, the AUC values of the nomogram, age, grade, N stage, M stage, surgery, and chemotherapy were 0.772, 0.551, 0.629, 0.534, 0.577, 0.606, and 0.639, respectively. Good agreement of the model in the training and validation cohorts was demonstrated in the calibration and DCA curves. Univariate survival analysis showed a statistically significant effect of age, grade, M stage, and surgery on prognosis (p < 0.05). CONCLUSION Age, grade, M stage, and surgery were independently associated with OS, and the established nomogram was a visual tool to effectively predict OS in advanced PBTC patients.
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Affiliation(s)
- Huaqing Shi
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Zhou Chen
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Shi Dong
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Ru He
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Yan Du
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Zishun Qin
- School of Stomatology, Lanzhou University, Lanzhou, China
| | - Wence Zhou
- The First Clinical Medical College, Lanzhou University, Lanzhou, China.
- Department of General Surgery, Lanzhou University Second Hospital, Lanzhou, Gansu, 730000, China.
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Chi X, Jiang L, Yuan Y, Huang X, Yang X, Hochwald S, Liu J, Huang H. A comparison of clinical pathologic characteristics between alpha-fetoprotein negative and positive hepatocellular carcinoma patients from Eastern and Southern China. BMC Gastroenterol 2022; 22:202. [PMID: 35461226 PMCID: PMC9034573 DOI: 10.1186/s12876-022-02279-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 04/11/2022] [Indexed: 11/30/2022] Open
Abstract
Background Alpha-fetoprotein (AFP) is a biomarker used in clinical management of hepatocellular carcinoma (HCC), however, approximately 40% of HCC patients do not present with elevated serum AFP levels. This study aimed to investigate the clinical and pathologic characteristics between AFP positive and negative HCC patients to allow for improved clinical management and prognostication of the disease. Methods This study observed a cohort of HCC patients from Eastern and Southern China with comparisons of the clinical and pathologic features between serum AFP positive and negative patient groups; patients with decompensated hepatic cirrhosis, those with chronic hepatitis B, and hepatitis B virus (HBV) asymptomatic carrier patients were used as controls. Data included the laboratory results, pathology diagnosis, clinical staging and scores were obtained from routine clinical diagnostic methods. Results Patients with HCC, larger tumor sizes, liver cancer with hepatic cirrhosis, portal vein thrombosis, metastasis, high Child–Pugh score, high Barcelona-Clínic Liver Cancer (BCLC) stage, and advanced clinical stage had significantly higher serum AFP levels. Also, patients with HBsAg and HBeAg positive, high HBV DNA levels had significantly higher serum AFP levels. Patients with high serum AFP levels had higher protein induced by vitamin K absence or antagonist-II (PIVKA-II), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alpha-l-fucosidase (AFU), gamma-glutamyl transpeptidase (γ-GT), γ-GT /ALT, direct bilirubin (DBIL), indirect bilirubin (IDBIL), fibrinogen, and D-dimer levels. Patients with AFP positive had higher white blood cells (WBC), neutrophil, monocyte, and platelet count and neutrophil to lymphocyte ratio (NLR). Conclusions The are significant differences in clinical pathologic characteristics between AFP positive and negative HCC patients which may be helpful for the management and prognostication of the disease. Supplementary Information The online version contains supplementary material available at 10.1186/s12876-022-02279-w.
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Hu X, Chen R, Wei Q, Xu X. The Landscape Of Alpha Fetoprotein In Hepatocellular Carcinoma: Where Are We? Int J Biol Sci 2022; 18:536-551. [PMID: 35002508 PMCID: PMC8741863 DOI: 10.7150/ijbs.64537] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 10/15/2021] [Indexed: 12/13/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver cancer and has been acknowledged as a leading cause of death among cirrhosis patients. Difficulties in early diagnosis and heterogeneity are obstacles to effective treatment, especially for advanced HCC. Liver transplantation (LT) is considered the best therapy for HCC. Although many biomarkers are being proposed, alpha-fetoprotein (AFP), which was identified over 60 years ago, remains the most utilized. Recently, much hope has been placed in the immunogenicity of AFP to develop novel therapies, such as AFP vaccines and AFP-specific adoptive T-cell transfer (ACT). This review summarizes the performance of AFP as a biomarker for HCC diagnosis and prognosis, as well as its correlation with molecular classes. In addition, the role of AFP in LT is also described. Finally, we highlight the mechanism and application prospects of two immune therapies (AFP vaccine and ACT) for HCC. In general, our review points out the prevalence of AFP in HCC, accompanied by some controversies and novel directions for future research.
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Affiliation(s)
- Xin Hu
- Department of Hepatobiliary and Pancreatic Surgery, The Center for Integrated Oncology and Precision Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China.,Zhejiang University Cancer Center, Hangzhou, 310058, China.,Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou, 310003, China
| | - Ronggao Chen
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou, 310003, China
| | - Qiang Wei
- Department of Hepatobiliary and Pancreatic Surgery, The Center for Integrated Oncology and Precision Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
| | - Xiao Xu
- Department of Hepatobiliary and Pancreatic Surgery, The Center for Integrated Oncology and Precision Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China.,Zhejiang University Cancer Center, Hangzhou, 310058, China.,Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou, 310003, China.,Institute of Organ Transplantation, Zhejiang University, Hangzhou, 310003, China
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Tang J, Zhu L, Huang Y, Yang L, Ge D, Hu Z, Wang C. Development and Validation of Prognostic Survival Nomograms for Patients with Anal Canal Cancer: A SEER-Based Study. Int J Gen Med 2022; 14:10065-10081. [PMID: 34984027 PMCID: PMC8709559 DOI: 10.2147/ijgm.s346381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 12/07/2021] [Indexed: 11/23/2022] Open
Abstract
Objective Anal canal cancer is a rare malignancy with increasing incidence in recent times. This study aimed to develop two nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with anal canal cancer. Methods Information of patients with anal canal cancer from 2004 to 2015 was extracted from the surveillance, epidemiology, and end results (SEER) database. Cox analysis was used to select the risk factors for prognosis, and nomograms were constructed using the R software. The C-index, area under the curve (AUC) of time-dependent receiver operating characteristic (ROC) curves, calibration plot and decision curve analysis (DCA) were used to assess the clinical utility of the nomograms. Results A total of 2458 patients with malignant tumours of the anal canal were screened out. Sex, age, marital status, histological type, grade, tumour size, AJCC stage, SEER stage and chemotherapy were independent prognostic factors for OS, whereas sex, age, race, histological type, grade, tumour size, AJCC stage, SEER stage and radiotherapy were independent prognostic factors for CSS. In the training cohort, the C-index value for OS nomogram was 0.73 (95% CI, 0.69-0.77), and the AUC values that predicted the 1-, 3- and 5-year survival rates were 0.764, 0.758 and 0.760, respectively, whereas the C-index value for CSS nomogram model was 0.74 (95% CI, 0.69-0.79), and the AUC values were 0.763, 0.769 and 0.763, respectively. The calibration plot and DCA curves demonstrated good prediction performance of the model in both the training and validation cohorts. Conclusion The established nomogram is a visualisation tool that can effectively predict the OS and CSS of patients with anal canal cancer.
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Affiliation(s)
- Jie Tang
- Department of Oncology, Liyang People's Hospital, Liyang, 213300, People's Republic of China
| | - Liqun Zhu
- Department of Oncology, Liyang People's Hospital, Liyang, 213300, People's Republic of China
| | - Yuejiao Huang
- Medical School, Nantong University, Nantong, 226019, People's Republic of China.,Department of Medical Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226399, People's Republic of China
| | - Lixiang Yang
- Department of Neurosurgery, Affiliated Zhongda Hospital of Southeast University, Nanjing, 210009, People's Republic of China
| | - Dangen Ge
- Department of Pharmacy, Liyang People's Hospital, Liyang, 213300, People's Republic of China
| | - Zhengyu Hu
- Department of General Surgery, Shanghai Tenth People's Hospital, Affiliated to Tongji University School of Medicine, Shanghai, 200072, People's Republic of China
| | - Chun Wang
- Department of Oncology, Liyang People's Hospital, Liyang, 213300, People's Republic of China
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A novel nomogram based on the nutritional risk screening 2002 score to predict survival in hepatocellular carcinoma treated with transarterial chemoembolization. NUTR HOSP 2022; 39:835-842. [DOI: 10.20960/nh.03983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
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Pu T, Li ZH, Jiang D, Chen JM, Guo Q, Cai M, Chen ZX, Xie K, Zhao YJ, Liu FB. Nomogram based on inflammation-related markers for predicting survival of patients undergoing hepatectomy for hepatocellular carcinoma. World J Clin Cases 2021; 9:11193-11207. [PMID: 35071550 PMCID: PMC8717490 DOI: 10.12998/wjcc.v9.i36.11193] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 06/16/2021] [Accepted: 08/24/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Previous nomograms for hepatocellular carcinoma (HCC) did not include the neutrophil-to-lymphocyte ratio (NLR) or platelet-to-lymphocyte ratio (PLR). This study aimed to establish an effective nomogram capable of estimating the association between preoperative inflammatory factors and overall survival (OS) of HCC patients after hepatectomy.
AIM To analyse the factors affecting the prognosis of HCC and establish a nomogram.
METHODS A total of 626 HCC patients (410 training set patients from the First Affiliated Hospital of Anhui Medical University and 216 validation set patients from the First Affiliated Hospital of University of Science and Technology of China) underwent hepatectomy from January 2014 to December 2017 and were followed up every 3–6 mo. The nomogram was based on OS-related independent risk factors identified by Cox regression analysis. The C-index, calibration curve, and area under the curve (AUC) were used to evaluate the nomogram’s accuracy.
RESULTS The 1-, 2- and 3-year OS rates were 79.0%, 68.0% and 45.4% in the training cohort (median OS = 34 mo) and 92.1%, 73.9% and 51.2% in the validation cohort (median OS = 38 mo). Higher α-fetoprotein [hazard ratio (HR) = 1.812, 95% confidence interval (CI): 1.343–2.444], NLR (HR = 2.480, 95%CI: 1.856–3.312) and PLR (HR = 1.974, 95%CI: 1.490–2.616), tumour size ≥ 5 cm (HR = 1.323, 95%CI: 1.002–1.747), and poor differentiation (HR = 3.207, 95%CI: 1.944–5.290) were significantly associated with shortened OS. The developed nomogram integrating these variables showed good reliability in both the training (C-index = 0.71) and validation cohorts (C-index = 0.75). For predicting 1-, 2- and 3-year OS, the nomogram had AUCs of 0.781, 0.743 and 0.706 in the training cohort and 0.789, 0.815 and 0.813 in the validation cohort. The nomogram was more accurate in predicting prognosis than the AJCC TNM staging system.
CONCLUSION The prognostic nomogram combining pathological characteristics and inflammation indicators could provide a more accurate individualized risk estimate for the OS of HCC patients with hepatectomy.
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Affiliation(s)
- Tian Pu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
| | - Zi-Han Li
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
| | - Dong Jiang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
| | - Jiang-Ming Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
| | - Qi Guo
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
| | - Ming Cai
- Department of General Surgery, The First Affiliated Hospital of University of Science and Technology of China, Hefei 230022, Anhui Province, China
| | - Zi-Xiang Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
| | - Kun Xie
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
| | - Yi-Jun Zhao
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
| | - Fu-Bao Liu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China
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Liu YY, Xu BS, Pan QZ, Weng DS, Zhang X, Peng RQ. New nomograms to predict overall and cancer-specific survival of angiosarcoma. Cancer Med 2021; 11:74-85. [PMID: 34786885 PMCID: PMC8704180 DOI: 10.1002/cam4.4425] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 10/12/2021] [Accepted: 10/14/2021] [Indexed: 12/25/2022] Open
Abstract
Objective This study was designed to establish and validate promising and reliable nomograms for predicting the survival of angiosarcoma (AS) patients. Methods The Surveillance, Epidemiology, and End Results database was queried to collect the clinical information of 785 AS patients between 2004 and 2015. Data were split into a training cohort (n = 549) and a validation cohort (n = 236) without any preference. Univariate Cox and multivariate Cox regression analyses were performed to analyze the clinical parameters. Independent prognostic factors were then identified. Two nomograms were constructed to predict overall survival (OS) and cancer‐specific survival (CSS) at 3 and 5 years. Finally, the models were evaluated using concordance indices (C‐indices), calibration plots, and decision curve analysis (DCA). Results Based on the inclusion and exclusion criteria, 785 individuals were included in this analysis. Univariate and multivariate Cox regression analyses revealed that age, tumor size, and stage were prognostic factors independently associated with the OS of AS. Tumor site, tumor size, and stage were associated with the CSS of AS. Based on the statistical results and clinical significance of variables, nomograms were built. The nomograms for OS and CSS had C‐indices of 0.666 and 0.654, respectively. The calibration curves showed good agreement between the predictive values and the actual values. DCA also indicated that the nomograms were clinically useful. Conclusion We established nomograms with good predictive ability that could provide clinicians with better predictions about the clinical outcomes of AS patients.
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Affiliation(s)
- Yuan-Yuan Liu
- Melanoma and Sarcoma Medical Oncology Unit, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Bu-Shu Xu
- Melanoma and Sarcoma Medical Oncology Unit, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Qiu-Zhong Pan
- Melanoma and Sarcoma Medical Oncology Unit, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - De-Sheng Weng
- Melanoma and Sarcoma Medical Oncology Unit, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Xing Zhang
- Melanoma and Sarcoma Medical Oncology Unit, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Rui-Qing Peng
- Melanoma and Sarcoma Medical Oncology Unit, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China
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Zang Y, Long P, Wang M, Huang S, Chen C. Development and validation of prognostic nomograms in patients with hepatocellular carcinoma: a population-based study. Future Oncol 2021; 17:5053-5066. [PMID: 34676798 DOI: 10.2217/fon-2020-1065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. The existing staging system has a limited budget capacity for HCC recurrence. The authors aimed to establish and verify two nomogram models to predict disease-free survival (DFS) and overall survival (OS) in patients with HCC. Methods: Patients diagnosed with HCC between August 2011 and March 2016 were recruited. Data were randomly divided into a training cohort and a validation cohort. Based on univariate and multivariate Cox regression analysis, independent risk factors for DFS and OS were identified, and two nomogram models were established to predict patient survival. Results: Sex, tumor size, Barcelona Clinic Liver Cancer (BCLC) stage, tumor capsule, macrovascular invasion, AST-to-platelet ratio index, AST-to-lymphocyte ratio index, neutrophil-lymphocyte ratio and alpha-fetoprotein (AFP) were used to build the nomogram for DFS, while age, tumor size, BCLC stage, tumor capsule, macrovascular invasion, systemic immune-inflammation index, AST, total bilirubin and AFP were used to build the nomogram for OS. Calibration curves showed good agreement between the nomogram prediction and actual observation. C-indices in both nomograms were significantly higher than BCLC. Conclusion: The two nomograms improved the accuracy of individualized prediction of DFS and OS, which may help doctors screen patients with a high risk of recurrence to formulate individualized treatment plans.
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Affiliation(s)
- Youya Zang
- Department of Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Peiyun Long
- Department of Oncology, Yue Bei People's Hospital, Shaoguang, Guangdong 512000, China
| | - Ming Wang
- Department of Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Shan Huang
- Department of Oncological Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Chuang Chen
- Department of Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
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Zhang R, Xu M, Liu X, Wang M, Jia Q, Wang S, Zheng X, He X, Huang C, Fan Y, Wu H, Xu K, Li D, Meng Z. Establishment and validation of a nomogram model for predicting the survival probability of differentiated thyroid carcinoma patients: a comparison with the eighth edition AJCC cancer staging system. Endocrine 2021; 74:108-119. [PMID: 33822318 DOI: 10.1007/s12020-021-02717-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 03/25/2021] [Indexed: 12/29/2022]
Abstract
PURPOSE This study aimed to develop a clinically predictive nomogram model to predict the survival probability of differentiated thyroid carcinoma patients and compare the value of this model with that of the eighth edition AJCC cancer staging system. METHODS We selected 59,876 differentiated thyroid carcinoma patients diagnosed between 2004 and 2015 from the SEER database and separated those patients into a training set (70%) and a validation set (30%) randomly. We used Cox regression analysis to build the nomogram model (model 1) and the eighth edition AJCC cancer staging model (model 2). Then we compared the predictive accuracy, discrimination, and clinical usage of both models by calculating AUC (Area under the curve), C-index, as well as analyzing DCA (Decision Curve Analysis) performance respectively. RESULTS AUCs of all predicted time points (12-month, 36-month, 60-month, and 120-month) of model 1 were 0.933, 0.913, 0.879, and 0.868 for the training set; 0.933, 0.926, 0.916, and 0.894 for the validation set. As for model 2, data were 0.938, 0.906, 0.866, and 0.847 for the training set; 0.924, 0.925, 0.912, and 0.867 for the validation set. C-indices of model 1 were higher than those of model 2 (0.923 vs. 0.918 for the training set, 0.938 vs. 0.930 for the validation set). DCA comparison showed that the net benefit of model 1 was bigger when comparing with that of model 2. CONCLUSIONS Model 1 provided with both better predictive accuracy and clinical usage compared with those of model 2 and might be able to predict the survival probability of differentiated thyroid carcinoma patients visually and accurately with a higher net benefit.
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Affiliation(s)
- Ruyi Zhang
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China
| | - Mei Xu
- Department of Pediatric, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiangxiang Liu
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China
| | - Miao Wang
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China
| | - Qiang Jia
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China
| | - Shen Wang
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiangqian Zheng
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin City, Tianjin, China
| | - Xianghui He
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Chao Huang
- Hull York Medical School, University of Hull, Hull, UK
| | - Yaguang Fan
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Heng Wu
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Ke Xu
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China.
| | - Dihua Li
- Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Institute of Acute Abdominal Diseases, Tianjin Nankai Hospital, Tianjin, China.
| | - Zhaowei Meng
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China.
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Kyei-Barffour I, Kwarkoh RKB, Acheampong DO, Brah AS, Akwetey SA, Aboagye B. Alkaloidal extract from Carica papaya seeds ameliorates CCl 4-induced hepatocellular carcinoma in rats. Heliyon 2021; 7:e07849. [PMID: 34471716 PMCID: PMC8387916 DOI: 10.1016/j.heliyon.2021.e07849] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 07/22/2021] [Accepted: 08/18/2021] [Indexed: 01/06/2023] Open
Abstract
Background Hepatocellular carcinoma (HCC) is the third cause of cancer-related mortality globally. However, available treatments are expensive and are associated with adverse effects or poor treatment outcomes in advanced disease. Meanwhile, plants like Carica papaya have demonstrated various biological activities that further studies may lead to the identification of newer and safer treatment options for HCC. Aim To evaluate the anticancer activity of an alkaloidal extract derived from Carica papaya seeds using rodent models of HCC. Experimental procedure Carica Papaya fruits were collected and authenticated. The seeds were isolated and air-dried. Alkaloidal extract was prepared from a 70% ethanol soxhlet crude extract and referred to as Carica papaya alkaloidal extract (CPAE). HCC was induced in 68 out of 84 healthy male Sprague Dawley rats by intraperitoneal injection of carbon tetrachloride (CCl4) for 16 weeks. These rats were put into five groups of 10; Carica papaya alkaloidal extract [(CPAE) (50, 100, and 200 mg/kg), Lenvatinib (4 mg/kg)], 1% dimethyl sulphoxide (DMSO), and 2 untreated groups (control and model). A prophylaxis study was performed with 10 rats by co-administration of CPAE (200 mg/kg) and CCl4 six hours apart for 16 weeks. Rats were sacrificed after a twelve-week treatment program under anesthesia for histological, hematological, and biochemical analyses. Results and conclusion CPAE (100 and 200 mg/kg) significantly restored weight loss (48.44 and 51.75% respectively), reduced tumor multiplicity, and dose-dependently reversed liver histomorphological changes induced by CCl4 compared to the model group. The CPAE (100 and 200 mg/kg) further reduced bleeding time, improved prothrombin time and restored platelet count (p < 0.01) compared to the model. The CPAE (200 mg/kg) again significantly (p < 0.0001) reduced serum alpha-fetoprotein levels compared to the model group and prevented the establishment of HCC in rats when concerrently administered with CCl4 in 16 weeks prophylactic study.
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Affiliation(s)
- Isaac Kyei-Barffour
- Department of Biomedical Sciences, School of Allied Health Sciences, College of Health and Allied Sciences, University of Cape Coast, Ghana
| | - Roselind Kyei Baah Kwarkoh
- Department of Physician Assistant Studies, School of Allied Health Sciences, College of Health and Allied Sciences, University of Cape Coast, Ghana
| | - Desmond Omane Acheampong
- Department of Biomedical Sciences, School of Allied Health Sciences, College of Health and Allied Sciences, University of Cape Coast, Ghana
| | - Augustine Suurinobah Brah
- Department of Biomedical Sciences, School of Allied Health Sciences, College of Health and Allied Sciences, University of Cape Coast, Ghana
| | - Samuel Addo Akwetey
- Department of Biomedical Sciences, School of Allied Health Sciences, College of Health and Allied Sciences, University of Cape Coast, Ghana
| | - Benjamin Aboagye
- Department of Forensic Sciences, School of Biological Sciences, College of Agricultural and Natural Sciences, University of Cape Coast, Ghana
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Peng RR, Liang ZG, Chen KH, Li L, Qu S, Zhu XD. Nomogram Based on Lactate Dehydrogenase-to-Albumin Ratio (LAR) and Platelet-to-Lymphocyte Ratio (PLR) for Predicting Survival in Nasopharyngeal Carcinoma. J Inflamm Res 2021; 14:4019-4033. [PMID: 34447260 PMCID: PMC8385134 DOI: 10.2147/jir.s322475] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 07/28/2021] [Indexed: 12/29/2022] Open
Abstract
Purpose The prognosis of inflammation-related indicators like lactate dehydrogenase/albumin ratio (LAR) and the platelet/lymphocyte ratio (PLR) in nasopharyngeal carcinoma (NPC) is not yet clear. Our objective is to establish and verify the nomogram using LAR and PLR ratio for the first time to explore the prognostic value in NPC. Patients and Methods This was a retrospective collection of 1661 patients with non-metastatic NPC admitted to our hospital from 2010 to 2017. The final variables of overall survival (OS) and progression-free survival (PFS) were selected by Cox regression analysis to establish nomograms, and the methods to verify the prediction precision and discriminative ability of the nomograms were concordance index (C index), the receiver operating characteristic (ROC) curve and calibration curve. The risk stratification was carried out through the nomograms and compared with the current staging system by the Kaplan–Meier methods. Results Multivariate Cox analysis resulted that age, plasma Epstein–Barr Virus (EBV) DNA, T stage, N stage, white blood cells (WBC), PLR and LAR were independent prognostic risk factors for OS and PFS, and sex is an independent prognostic risk factor for OS. The C-indexes of OS nomogram were 0.722 (95% CI: 0.706–0.738) and 0.747 (95% CI: 0.717–0.777) in the training cohort and validation cohort, which were statistically higher than the current 8th AJCC staging system (0.646 and 0.688). The C-indexes of PFS nomogram were 0.696 (95% CI: 0.680–0.713) and 0.690 (95% CI: 0.660–0.720), which were also statistically higher than the current 8th AJCC staging system (0.632 and 0.666). Otherwise, ROC curves and the calibration curve for probability also confirmed satisfied consistency with actual observations. Conclusion LAR is a novel useful independent factor in NPC. The proposed nomogram LAR and PLR resulted in more accurate prognostic prediction than current staging system for NPC patients.
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Affiliation(s)
- Ru-Rong Peng
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Zhong-Guo Liang
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Kai-Hua Chen
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Ling Li
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Song Qu
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Xiao-Dong Zhu
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.,Department of Oncology, Affiliated Wu-Ming Hospital of Guangxi Medical University, Nanning, People's Republic of China
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Tian S, Li J, Guo Y, Dong W, Zheng X. Expression Status and Prognostic Significance of Gamma-Glutamyl Transpeptidase Family Genes in Hepatocellular Carcinoma. Front Oncol 2021; 11:731144. [PMID: 34513707 PMCID: PMC8426663 DOI: 10.3389/fonc.2021.731144] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 07/30/2021] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Gamma-glutamyl transpeptidase (GGT) family genes play crucial roles in the formation and progression of several solid tumors. However, the expression patterns and the prognostic significance of GGT members in hepatocellular carcinoma (HCC) remain unknown. This study was designed to determine the expression profiles of GGT family members in HCC and validate the prognostic value of serum GGT protein in patients with HCC. METHOD We comprehensively searched public resources based on the LIHC dataset to determine the expression patterns, prognostic significance, DNA methylation status, immune infiltration, and biological pathways of GGT family genes in HCC. Subsequently, we validated the prognostic value of serum GGT protein in 85 patients with early-stage HCC subjected to curative hepatectomy from the Renmin Hospital of Wuhan University. RESULTS Except for GGT1, other GGT family members (GGT5, GGT6, and GGT7) were found to be differentially expressed in primary HCC samples (N = 371) and normal control tissues (N = 50). Furthermore, a positive relationship was not only observed between GGT1 and GGT5 (Spearman coefficient: 0.24, P = 5.143 × 10-6) but also between GGT5 and GGT6 (Spearman coefficient: 0.38, P = 1.24 × 10-13). The expression of GGT1, GGT5, and GGT7 was correlated with overall survival (OS), and GGT7 was associated with disease-free survival (DFS) in patients with HCC. Negative associations between DNA methylation and expression of mRNA were observed for GGT1 (Spearman coefficient: -0.38, P = 6.24e-14), GGT6 (Spearman coefficient: -0.29, P = 1.23e-8), and GGT7 (Spearman coefficient: -0.34, P=6.7e-11). GGT family genes were well correlated with the infiltration levels of immune cells in HCC, especially CD4+ T cells, macrophages, and dendritic cells. Finally, when validated with clinical data from the Renmin cohort, a high expression of serum GGT protein was identified as a strong prognostic element of unfavorable OS (HR = 3.114, P = 0.025), but not of DFS (HR = 1.198, P = 0.05) in patients with HCC subjected to curative hepatectomy. CONCLUSION To our knowledge, this is the first comprehensive analysis of the expression patterns and clinical value of GGT family genes in patients with HCC. Our study laid the foundation for the clinical application of the GGT protein in the survival assessment of patients with HCC.
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Affiliation(s)
- Shan Tian
- Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiao Li
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Yingyun Guo
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Weiguo Dong
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Xin Zheng
- Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Liu Z, Pu Y, Bao Y, He S. Investigation of Potential Molecular Biomarkers for Diagnosis and Prognosis of AFP-Negative HCC. Int J Gen Med 2021; 14:4369-4380. [PMID: 34408477 PMCID: PMC8364386 DOI: 10.2147/ijgm.s323868] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 08/02/2021] [Indexed: 01/04/2023] Open
Abstract
Background Alpha-fetoprotein (AFP) is the most important diagnostic and prognostic index of hepatocellular carcinoma (HCC). AFP-positive HCC can be easily diagnosed based on the serum AFP level and typical imaging features, but a number of HCC patients are negative (AFP < 20 ng/mL) for AFP. Therefore, it is necessary to develop novel diagnostic and prognostic biomarkers for AFP-negative HCC. Methods RNA data from TCGA and differential expression of lncRNAs, miRNAs, and mRNAs were downloaded to analyze the differential RNA expression patterns between AFP-negative HCC tissues and normal tissues. A lncRNA-miRNA-mRNA ceRNA regulatory network was constructed to elucidate the interaction mechanism of RNAs. Functional enrichment analysis of these DEmRNAs was performed to indirectly reveal the mechanism of action of lncRNAs. A PPI network was built using STRING, and the hub genes were identified with Cytoscape. The diagnostic value of hub genes was assessed with receiver operating characteristic (ROC) analysis. And the prognostic value of RNAs in the ceRNA was estimated with Kaplan-Meier curve analysis. Results A total of 131 lncRNAs, 185 miRNA, and 1309 mRNAs were found to be differentially expressed in AFP-negative HCC. A ceRNA network consisting of 12 lncRNA, 23 miRNA, and 74 mRNA was constructed. The top ten hub genes including EZH2, CCNB1, E2F1, PBK, CHAF1A, ESR1, RRM2, CCNE1, MCM4, and ATAD2 showed good diagnostic power under the ROC curve; and 2 lncRNAs (LINC00261, LINC00482), 3 miRNAs (hsa-miR-93, hsa-miR-221, hsa-miR-222), and 2 mRNAs (EGR2, LPCAT1) were found to be associated with the overall survival of AFP-negative patients. Conclusion This study could provide a novel insight into the molecular pathogenesis of AFP-negative HCC and reveal some candidate diagnostic and prognostic biomarkers for AFP-negative HCC.
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Affiliation(s)
- Zijing Liu
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, People's Republic of China
| | - Youwei Pu
- Department of Clinical Laboratory, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, People's Republic of China
| | - Yixi Bao
- Department of Clinical Laboratory, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, People's Republic of China
| | - Song He
- Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, People's Republic of China
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Kwon Y, Kim JR, Park YM, Choi BK, Kim C, Young Kim H, Yoon M. Predicting survival time of Korean hepatocellular carcinoma patients using the Cox proportional hazards model: a retrospective study based on big data analysis. Eur J Gastroenterol Hepatol 2021; 33:1001-1008. [PMID: 33470702 DOI: 10.1097/meg.0000000000002058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
AIM To predict survival time of Korean hepatocellular carcinoma (HCC) patients by analyzing big data using Cox proportional hazards model. METHODS Big data of the patients who underwent treatment for HCC from 2008 to 2015, provided by Korea Central Cancer Registry, National Cancer Center, and Ministry of Health and Welfare, were analyzed. A total of 10 742 patients with HCC were divided into two groups, with Group I (3021 patients) confirmed on biopsy and Group II (5563 patients) diagnosed as HCC according to HCC diagnostic criteria as outlined in Korean Liver Cancer Association guidelines. Univariate and multivariate Cox regression analyses were performed to identify independent risk factors of recurrence after treatment and survival status. RESULTS A total of 3021 patients in Group I and 5563 patients in Group II were included in the study and the difference in survival time between the two groups was statistically significant (P < 0.05). Recurrence was only included in intrahepatic cases, and the rates were 21.2 and 19.8% while the periods from the first treatment to recurrence were 15.57 and 14.19 months, respectively. Age, diabetes, BMI, platelet, alpha-fetoprotein, histologic tumor maximum size, imaging T stage, presence of recurrence, and duration of recurrence were included in multivariate analysis. CONCLUSION By using nationwide, multicenter big data, it is possible to predict recurrence rate and survival time which can provide the basis for treatment response to develop a predictive program.
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Affiliation(s)
- Yujin Kwon
- Department of Surgery, Seoul Medical Center, Seoul, Korea
| | - Jae Ri Kim
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Pusan National University College of Medicine, Busan, Korea
| | - Young Mok Park
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Pusan National University College of Medicine, Busan, Korea
| | - Byung Kwan Choi
- Department of Neurosurgery, Pusan National University College of Medicine, Busan, Korea
| | - Choongrak Kim
- Department of Statistics, Pusan National University, Busan, Korea
| | - Hae Young Kim
- Division of Pediatric Surgery, Department of Surgery, Pusan National University College of Medicine, Busan, Korea
| | - Myunghee Yoon
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Pusan National University College of Medicine, Busan, Korea
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Li J, Tao H, Zhang E, Huang Z. Diagnostic value of gamma-glutamyl transpeptidase to alkaline phosphatase ratio combined with gamma-glutamyl transpeptidase to aspartate aminotransferase ratio and alanine aminotransferase to aspartate aminotransferase ratio in alpha-fetoprotein-negative hepatocellular carcinoma. Cancer Med 2021; 10:4844-4854. [PMID: 34145988 PMCID: PMC8290252 DOI: 10.1002/cam4.4057] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 04/23/2021] [Accepted: 05/14/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The purpose of the study was to evaluate the diagnostic value of gamma-glutamyl transpeptidase to alkaline phosphatase ratio (GAPR) combined with gamma-glutamyl transpeptidase to aspartate aminotransferase ratio (GAR) and alanine aminotransferase to aspartate aminotransferase ratio (AAR) in alpha-fetoprotein (AFP)-negative hepatocellular carcinoma (HCC). METHODS A total of 925 AFP-negative patients, including 235 HCC patients, 213 chronic hepatitis (CH) patients, and 218 liver cirrhosis (LC) patients, as well as 259 healthy controls were enrolled in this study. The differences of laboratory parameters and clinical characteristics were analyzed by Mann-Whitney U or Kruskal-Wallis H-test. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of GAPR, GAR, and AAR in AFP-negative HCC (AFP-NHCC) patients. RESULTS GAPR, GAR, and AAR were important parameters closely related to AFP-NHCC. The combination of GAPR, GAR, and AAR was most effective in differentiating AFP-NHCC group from control group (AUC = 0.875), AFP-negative CH group (AUC = 0.733), and AFP-negative LC group (AUC = 0.713). GAPR combined with GAR and AAR exhibited a larger AUC than single ratio or pairwise combination for distinguishing AFP-NHCC group with TNMⅠstage, BCLC stage A, and tumor size less than 3 cm. The diagnostic value of GAPR combined with GAR and AAR was higher in AFP-NHCC and was also reflected in the TNM stage, Barcelona Clinic Liver Cancer (BCLC) stage and tumor size. CONCLUSIONS GAPR combined with GAR and AAR were effective diagnostic markers of AFP-NHCC, especially in patients with good liver function, early stage or small size.
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Affiliation(s)
- Jiang Li
- Hepatic Surgery CenterTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Haisu Tao
- Hepatic Surgery CenterTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Erlei Zhang
- Hepatic Surgery CenterTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Zhiyong Huang
- Hepatic Surgery CenterTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
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Zhou D, Liu X, Wang X, Yan F, Wang P, Yan H, Jiang Y, Yang Z. A prognostic nomogram based on LASSO Cox regression in patients with alpha-fetoprotein-negative hepatocellular carcinoma following non-surgical therapy. BMC Cancer 2021; 21:246. [PMID: 33685417 PMCID: PMC7938545 DOI: 10.1186/s12885-021-07916-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Accepted: 02/15/2021] [Indexed: 12/14/2022] Open
Abstract
Background Alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) (< 8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of patients with AFP-NHCC. Methods A total of 410 AFP-negative patients with clinical diagnosed with HCC following non-surgical therapy as a primary cohort; 148 patients with AFP-NHCC following non-surgical therapy as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by Forward Stepwise Cox regression were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort. Results The C-index of nomogram1was 0.708 (95%CI: 0.673–0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606–0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690–0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691–0.813; AUC: 0.784, 95%CI: 0.709–0.847). The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively. Conclusions Novel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-NHCC following non-surgical therapy. This model could help patients with AFP-NHCC following non-surgical therapy facilitate a personalized prognostic evaluation.
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Affiliation(s)
- Dongdong Zhou
- Center for Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, People's Republic of China
| | - Xiaoli Liu
- Center for Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, People's Republic of China
| | - Xinhui Wang
- Center for Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, People's Republic of China
| | - Fengna Yan
- Center for Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, People's Republic of China
| | - Peng Wang
- Center for Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, People's Republic of China
| | - Huiwen Yan
- Center for Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, People's Republic of China.,First Clinical Medical College, Beijing University of Chinese Medicine, Chaoyang District, Beijing, 100029, People's Republic of China
| | - Yuyong Jiang
- Center for Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, People's Republic of China
| | - Zhiyun Yang
- Center for Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, People's Republic of China.
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