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Yang D, Du J, Nie W, Wang C, Ma Z. Combination treatment of transcatheter arterial chemoembolization, intensity-modulated radiotherapy, and sorafenib for hepatocellular carcinoma with macrovascular invasion. Medicine (Baltimore) 2023; 102:e35713. [PMID: 37960807 PMCID: PMC10637514 DOI: 10.1097/md.0000000000035713] [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: 07/10/2023] [Accepted: 09/28/2023] [Indexed: 11/15/2023] Open
Abstract
This study evaluated the therapeutic effects and toxic reactions of combining transcatheter arterial chemoembolization (TACE) and intensity-modulated radiotherapy (IMRT) with sorafenib for the treatment of advanced hepatocellular carcinoma (HCC) patients with macrovascular invasion (MVI). We retrospectively analyzed the clinical data of 82 HCC patients with MVI, among whom 35 were treated with TACE plus IMRT alone, and 47 were treated with the combined therapy of TACE, IMRT, and sorafenib. The progression-free survival (PFS), overall survival (OS), and adverse events were assessed. The baseline characteristics were comparable between the 2 groups (all P > .05). In the TACE plus IMRT plus sorafenib group, the median PFS was 17.2 months (95% confidence interval, 14.1-19.9), significantly longer than the 9.4 months (95% confidence interval, 6.8-11.2) observed in the TACE plus IMRT group (P < .001). Additionally, patients treated with the TACE plus IMRT plus sorafenib showed a longer median OS than those treated with TACE plus IMRT alone (24.1 vs 17.3 months; P < .001). The occurrence rates of grade 1 to 2 hand-foot syndrome, other skin reactions, diarrhea, and hair loss were higher in the TACE plus IMRT plus sorafenib group (all P < .05). There were no grade 4 or higher adverse events in either group. The combination of TACE plus IMRT with sorafenib provided substantial clinical benefits in the treatment of HCC patients with MVI, increasing the tumor response rate and prolonging both PFS and OS. This approach demonstrated a tolerable and manageable safety profile.
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Affiliation(s)
- Dan Yang
- Department of Gastroenterology, 3201 Hospital, Hanzhong, China
| | - Jiaojiao Du
- Department of Gastroenterology, 3201 Hospital, Hanzhong, China
| | - Weijie Nie
- Department of Gastroenterology, 3201 Hospital, Hanzhong, China
| | - Chaozhi Wang
- Department of Gastroenterology, 3201 Hospital, Hanzhong, China
| | - Zhufang Ma
- Department of Gastroenterology, 3201 Hospital, Hanzhong, China
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Luo PQ, Ye ZH, Zhang LX, Song ED, Wei ZJ, Xu AM, Lu Z. Prognostic factors for disease-free survival in postoperative patients with hepatocellular carcinoma and construction of a nomogram model. World J Clin Cases 2022; 10:13250-13263. [PMID: 36683638 PMCID: PMC9850999 DOI: 10.12998/wjcc.v10.i36.13250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 09/15/2022] [Accepted: 11/25/2022] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is the most common type of liver cancer and has a high risk of invasion and metastasis along with a poor prognosis. AIM To investigate the independent predictive markers for disease-free survival (DFS) in patients with HCC and establish a trustworthy nomogram. METHODS In this study, 445 patients who were hospitalized in The First Affiliated Hospital of Anhui Medical College between December 2009 and December 2014 were retrospectively examined. The survival curve was plotted using the Kaplan-Meier method and survival was determined using the log-rank test. To identify the prognostic variables, multivariate Cox regression analyses were carried out. To predict the DFS in patients with HCC, a nomogram was created. C-indices and receiver operator characteristic curves were used to evaluate the nomogram's performance. Decision curve analysis (DCA) was used to evaluate the clinical application value of the nomogram. RESULTS Longer DFS was observed in patients with the following characteristics: elderly, I-II stage, and no history of hepatitis B. The calibration curve showed that this nomogram was reliable and had a higher area under the curve value than the tumor node metastasis (TNM) stage. Moreover, the DCA curve revealed that the nomogram had good clinical applicability in predicting 3- and 5-year DFS in HCC patients after surgery. CONCLUSION Age, TNM stage, and history of hepatitis B infection were independent factors for DFS in HCC patients, and a novel nomogram for DFS of HCC patients was created and validated.
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Affiliation(s)
- Pan-Quan Luo
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230031, Anhui Province, China
| | - Zheng-Hui Ye
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230031, Anhui Province, China
| | - Li-Xiang Zhang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230031, Anhui Province, China
| | - En-Dong Song
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230031, Anhui Province, China
| | - Zhi-Jian Wei
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230031, Anhui Province, China
| | - A-Man Xu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230031, Anhui Province, China
| | - Zhen Lu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230011, Anhui Province, China
- Anhui Public Health Clinical Center, Hefei 230011, Anhui Province, 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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He YY, Wu XJ, Zhou DH, Yang LH, Mai HR, Wan WQ, Luo XQ, Zheng MC, Zhang JL, Ye ZL, Chen HQ, Chen QW, Long XJ, Sun XF, Liu RY, Li QR, Wu BY, Wang LN, Kong XL, Chen GH, Tang XY, Fang JP, Liao N. A Nomogram for Predicting Event-Free Survival in Childhood Acute Lymphoblastic Leukemia: A Multicenter Retrospective Study. Front Oncol 2022; 12:854798. [PMID: 35425700 PMCID: PMC9002097 DOI: 10.3389/fonc.2022.854798] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 02/28/2022] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVE Even though childhood acute lymphoblastic leukemia (ALL) has an encouraging survival rate in recent years, some patients are still at risk of relapse or even death. Therefore, we aimed to construct a nomogram to predict event-free survival (EFS) in patients with ALL. METHOD Children with newly diagnosed ALL between October 2016 and July 2021 from 18 hospitals participating in the South China children's leukemia Group (SCCLG) were recruited and randomly classified into two subsets in a 7:3 ratio (training set, n=1187; validation set, n=506). Least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were adopted to screen independent prognostic factors. Then, a nomogram can be build based on these prognostic factors to predict 1-, 2-, and 3-year EFS. Concordance index (C-index), area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the performance and clinical utility of nomogram. RESULT The parameters that predicted EFS were age at diagnosis, white blood cell at diagnosis, immunophenotype, ETV6-RUNX1/TEL-AML1 gene fusion, bone marrow remission at day 15, and minimal residual disease at day 15. The nomogram incorporated the six factors and provided C-index values of 0.811 [95% confidence interval (CI) = 0.792-0.830] and 0.797 (95% CI = 0.769-0.825) in the training and validation set, respectively. The calibration curve and AUC revealed that the nomogram had good ability to predict 1-, 2-, and 3-year EFS. DCA also indicated that our nomogram had good clinical utility. Kaplan-Meier analysis showed that EFS in the different risk groups stratified by the nomogram scores was significant differentiated. CONCLUSION The nomogram for predicting EFS of children with ALL has good performance and clinical utility. The model could help clinical decision-making.
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Affiliation(s)
- Yun-yan He
- Department of Pediatrics, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xiao-jing Wu
- Department of Pediatrics, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Graduate School, Guangxi Medical University, Nanning, China
| | - Dun-hua Zhou
- Children’s Medical Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Li-hua Yang
- Department of Pediatrics, Southern Medical University Zhujiang Hospital, Guangzhou, China
| | - Hui-rong Mai
- Department of Hematology and Oncology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Wu-qing Wan
- Department of Pediatrics, Second Xiangya Hospital of Central South University, Changsha, China
| | - Xue-qun Luo
- Department of Pediatrics, Sun Yat-Sen University First Affiliated Hospital, Guangzhou, China
| | - Min-cui Zheng
- Department of Hematology, Hunan Children’s Hospital, Changsha, China
| | - Jun-lin Zhang
- Graduate School, Guangxi Medical University, Nanning, China
| | - Zhong-lv Ye
- Department of Pediatrics, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Hui-qin Chen
- Department of Pediatrics, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Qi-wen Chen
- Department of Pediatrics, First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xing-jiang Long
- Department of Pediatrics, Liuzhou People’s Hospital, Liuzhou, China
| | - Xiao-fei Sun
- Department of Pediatrics, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Ri-yang Liu
- Department of Pediatrics, Huizhou Central People’s Hospital, Huizhou, China
| | - Qiao-ru Li
- Department of Pediatrics, Zhongshan People’s Hospital, Zhongshan, China
| | - Bei-yan Wu
- Department of Pediatrics, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Li-na Wang
- Department of Pediatrics, Guangzhou First People’s Hospital, Guangzhou, China
| | - Xian-ling Kong
- Department of Pediatrics, Boai Hospital of Zhongshan, Zhongshan, China
| | - Guo-hua Chen
- Department of Pediatrics, Huizhou First People’s Hospital, Huizhou, China
| | - Xian-yan Tang
- School of Public Health, Guangxi Medical University, Nanning, China
| | - Jian-pei Fang
- Children’s Medical Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- *Correspondence: Ning Liao, ; Jian-pei Fang,
| | - Ning Liao
- Department of Pediatrics, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- *Correspondence: Ning Liao, ; Jian-pei Fang,
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Xu W, Liu F, Shen X, Li R. Prognostic Nomograms for Patients with Hepatocellular Carcinoma After Curative Hepatectomy, with a Focus on Recurrence Timing and Post-Recurrence Management. J Hepatocell Carcinoma 2020; 7:233-256. [PMID: 33154956 PMCID: PMC7606947 DOI: 10.2147/jhc.s271498] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 10/10/2020] [Indexed: 12/25/2022] Open
Abstract
Background Prognoses of patients with hepatocellular carcinoma (HCC) after curative hepatectomy remain unsatisfactory because of the high incidence of postoperative recurrence. Published predictive systems focus on pre-resection oncological characteristics, ignoring post-recurrence factors. Purpose This study aimed to develop prognostic nomograms for 3- and 5-year overall survival (OS) of patients with HCC after curative hepatectomy, focusing on potentially influential post-recurrence factors. Patients and Methods Clinicopathological and postoperative follow-up data were extracted from 494 patients with HCC who underwent curative hepatectomy between January 2012 and June 2019. Early recurrence (ER) and late recurrence (LR) were defined as recurrence at ≤2 and >2 years, respectively, after curative hepatectomy. Nomograms for the prediction of 3- and 5-year OS were established based on multivariate analysis. The areas under time-dependent receiver operating characteristic curves (AUCs) for the nomograms were calculated independently to verify predictive accuracy. The nomograms were internally validated based on 2000 bootstrap resampling of 75% of the original data. Results In total, 494 patients with HCC who underwent curative hepatectomy met the eligibility criteria. Cox proportional hazard regression analysis identified factors potentially influencing 3- and 5-year OS. Multivariate analysis indicated that patient age, Hong Kong Liver Cancer stage, γ-glutamyl transferase (γ-GGT) level, METAVIR inflammation activity grade, ER and post-recurrence treatment modality were influencing factors for 3-year OS (AUC, 0.891; 95% CI, 0.8364-0.9447). γ-GGT > 60 U/L, hepatectomy extent, LR and post-recurrence treatment modality were influencing factors for 5-year OS (AUC, 0.864; 95% CI, 0.8041-0.9237). Calibration plots showed satisfactory concordance between the predicted and actual observation cohorts. Conclusion We propose new prognostic nomograms for OS prediction with a focus on the differentiation of recurrence timing and post-recurrence management. These nomograms overcome the shortcomings of previous predictive nomograms and significantly improve predictive accuracy.
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Affiliation(s)
- Wei Xu
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, People's Republic of China
| | - Fei Liu
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, People's Republic of China
| | - Xianbo Shen
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, People's Republic of China
| | - Ruineng Li
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha, People's Republic of China
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Xu W, Li R, Liu F. Novel Prognostic Nomograms for Predicting Early and Late Recurrence of Hepatocellular Carcinoma After Curative Hepatectomy. Cancer Manag Res 2020; 12:1693-1712. [PMID: 32214844 PMCID: PMC7082541 DOI: 10.2147/cmar.s241959] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 02/25/2020] [Indexed: 01/27/2023] Open
Abstract
Aim Hepatectomy is the main curative method for patients with hepatocellular carcinoma (HCC) in China. Unfortunately, high recurrence rate after hepatectomy poses negative impact on the prognosis of patients. This study aimed to develop prognostic nomograms to predict early recurrence (ER) and late recurrence (LR) of HCC after curative hepatectomy. Patients and Methods Total of 318 HCC patients undergoing curative hepatectomy from January 2012 to January 2018 were retrospectively recruited. Potential risk factors that were significant for predicting ER and LR in univariate analysis were selected for multivariate survival model analysis using the backward stepwise method. Risk factors identified in multivariate analysis were used to develop nomograms to predict ER and LR. The nomogram was internally validated using 2,000 bootstrap samples from 75% of the original data. Results Among 318 patients, 164 showed postoperative recurrence, of which 140 and 24 had ER (≤2 years) and LR (>2 years), respectively. Multivariate analysis showed that age, Hong Kong Liver Cancer Stage, albumin-bilirubin, METAVIR fibrosis grade, and microvascular invasion were risk factors of ER for HCC after curative hepatectomy. The AUC of the ROC curve for ER in the development set (D-set) was 0.888 while that in the validation set (V-set) was 0.812. Neutrophil/lymphocyte ratio and glypican-3 (+) were risk factors for LR in HCC patients after curative hepatectomy. The AUC of the ROC curve for LR predictive nomogram that integrated all independent predictors was 0.831. The AUC of the ROC curve for LR in the D-set was 0.833, while that for LR in the V-set was 0.733. The C-index and AUC of ROC for the proposed nomograms were more satisfactory than three conventional HCC staging systems used in this study. Conclusion We developed novel nomograms to predict ER and LR of HCC patients after curative hepatectomy for clinical use to individualize follow-up and therapeutic strategies.
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Affiliation(s)
- Wei Xu
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha 410005, People's Republic of China
| | - Ruineng Li
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha 410005, People's Republic of China
| | - Fei Liu
- Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Hospital Affiliated with Hunan Normal University, Changsha 410005, People's Republic of China
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Yang J, Pan Z, Zhou Q, Liu Q, Zhao F, Feng X, Lyu J. Nomogram for predicting the survival of patients with malignant melanoma: A population analysis. Oncol Lett 2019; 18:3591-3598. [PMID: 31516573 PMCID: PMC6732986 DOI: 10.3892/ol.2019.10720] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Accepted: 07/10/2019] [Indexed: 12/26/2022] Open
Abstract
The aim of the current study was to develop and validate a nomogram based on a large population to estimate the 3- and 5-year survival rates of patients with malignant melanoma (MM). Patients were selected from the Surveillance, Epidemiology and End Results database and randomly divided into the training and validation cohorts. A nomogram was developed, and was used to assess the accuracy of the model. Independent prognostic factors associated with overall survival (OS) rate were identified through multivariate analysis, and were included in the internal validation of the nomogram. The nomogram provided high C-indexes for the training cohort [area under the time-dependent receiver operating characteristic curve (AUC) of 0.877 for 3-year OS rate and 0.872 for 5-year OS rate] and the validation cohort (AUC of 0.880 for 3-year OS rate and 0.874 for 5-year OS rate), indicating that the model had good discrimination ability. Calibration plots showed that the predicted 3- and 5-year OS rates probabilities for the training and validation groups were almost identical to the actual observations. The 3- and 5-year decision curves indicated net benefits for both the training and validation cohorts. The nomogram may aid clinicians to provide more accurate prognosis prediction in patient consultations and more personalized postoperative management plans.
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Affiliation(s)
- Jin Yang
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
| | - Zhenyu Pan
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
- Department of Pharmacy, The Affiliated Children Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
| | - Quan Zhou
- Department of Science and Education, The First People's Hospital of Changde City, Changde, Hunan 415003, P.R. China
| | - Qingqing Liu
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
| | - Fanfan Zhao
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
| | - Xiaojie Feng
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
| | - Jun Lyu
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
- Institute of Evidence-Based Medicine and Knowledge Translation, Henan University, Kaifeng, Henan 475000, P.R. China
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