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Li Y, Shao X, Dai LJ, Yu M, Cong MD, Sun JY, Pan S, Shi GF, Zhang AD, Liu H. Development of a prognostic nomogram for esophageal squamous cell carcinoma patients received radiotherapy based on clinical risk factors. Front Oncol 2024; 14:1429790. [PMID: 39239271 PMCID: PMC11374629 DOI: 10.3389/fonc.2024.1429790] [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: 05/08/2024] [Accepted: 07/29/2024] [Indexed: 09/07/2024] Open
Abstract
Purpose The goal of the study was to create a nomogram based on clinical risk factors to forecast the rate of locoregional recurrence-free survival (LRFS) in patients with esophageal squamous cell carcinoma (ESCC) who underwent radiotherapy (RT). Methods In this study, 574 ESCC patients were selected as participants. Following radiotherapy, subjects were divided into training and validation groups at a 7:3 ratio. The nomogram was established in the training group using Cox regression. Performance validation was conducted in the validation group, assessing predictability through the C-index and AUC curve, calibration via the Hosmer-Lemeshow (H-L) test, and evaluating clinical applicability using decision curve analysis (DCA). Results T stage, N stage, gross tumor volume (GTV) dose, location, maximal wall thickness (MWT) after RT, node size (NS) after RT, Δ computer tomography (CT) value, and chemotherapy were found to be independent risk factors that impacted LRFS by multivariate cox analysis, and the findings could be utilized to create a nomogram and forecast LRFS. the area under the receiver operating characteristic (AUC) curve and C-index show that for training and validation groups, the prediction result of LRFS using nomogram was more accurate than that of TNM. The LRFS in both groups was consistent with the nomogram according to the H-L test. The DCA curve demonstrated that the nomogram had a good prediction effect both in the groups for training and validation. The nomogram was used to assign ESCC patients to three risk levels: low, medium, or high. There were substantial variations in LRFS between risk categories in both the training and validation groups (p<0.001, p=0.003). Conclusions For ESCC patients who received radiotherapy, the nomogram based on clinical risk factors could reliably predict the LRFS.
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Affiliation(s)
- Yang Li
- Department of Computed Tomography and Magnetic Resonance Imaging, The Fourth Hospital of Hebei Medical University, Hebei, Shijiazhuang, China
| | - Xian Shao
- Department of Anesthesiology, The Fourth Hospital of Shijiazhuang, Hebei, Shijiazhuang, China
| | - Li-Juan Dai
- Department of Computed Tomography and Magnetic Resonance Imaging, The Fourth Hospital of Hebei Medical University, Hebei, Shijiazhuang, China
| | - Meng Yu
- The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Meng-Di Cong
- Department of Computed Tomography and Magnetic Resonance Imaging, Hebei Children's Hospital, Shijiazhuang, Hebei, China
| | - Jun-Yi Sun
- Department of Radiology, First Hospital of Qinhuangdao, Hebei, Qinhuangdao, China
| | - Shuo Pan
- Department of Radiotherapy, The Fourth Hospital of Hebei Medical University, Hebei, Shijiazhuang, China
| | - Gao-Feng Shi
- Department of Computed Tomography and Magnetic Resonance Imaging, The Fourth Hospital of Hebei Medical University, Hebei, Shijiazhuang, China
| | - An-Du Zhang
- Department of Radiotherapy, The Fourth Hospital of Hebei Medical University, Hebei, Shijiazhuang, China
| | - Hui Liu
- Department of Computed Tomography and Magnetic Resonance Imaging, The Fourth Hospital of Hebei Medical University, Hebei, Shijiazhuang, China
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Lin XW, Chen H, Xie XY, Liu CT, Lin YW, Xu YW, Wang XJ, Wu FC. Nomogram based on pretreatment hepatic and renal function indicators for survival prediction of locally advanced esophageal squamous cell carcinoma with treatment of neoadjuvant chemoradiotherapy plus surgery. Updates Surg 2024; 76:1377-1388. [PMID: 37957531 DOI: 10.1007/s13304-023-01693-3] [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: 06/05/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023]
Abstract
The parameters for survival prediction of esophageal squamous cell carcinoma (ESCC) patients treated with neoadjuvant chemoradiotherapy (NCRT) combined with surgery are unclear. Here, we aimed to construct a nomogram for survival prediction of ESCC patients treated with NCRT combined with surgery based on pretreatment serological hepatic and renal function tests. A total of 174 patients diagnosed as ESCC were enrolled as a training cohort from July 2007 to June 2019, and approximately 50% of the cases (n = 88) were randomly selected as an internal validation cohort. Univariate and multivariate Cox survival analyses were performed to identify independent prognostic factors to establish a nomogram. Predictive accuracy of the nomogram was evaluated by Harrell's concordance index (C-index) and calibration curve. ALT, ALP, TBA, TP, AST, TBIL and CREA were identified as independent prognostic factors and incorporated into the construction of the hepatic and renal function test nomogram (HRFTNomogram). The C-index of the HRFTNomogram for overall survival (OS) was 0.764 (95% CI 0.701-0.827) in the training cohort, which was higher than that of the TNM staging system (0.507 (95% CI 0.429-0.585), P < 0.001). The 5-year OS calibration curve of the training cohort demonstrated that the predictive accuracy of the HRFTNomogram was satisfactory. Moreover, patients in the high-risk group stratified by the HRFTNomogram had poorer 5-year OS than those in the low-risk group in the training cohort (27.4% vs. 80.3%, P < 0.001). Similar results were observed in the internal validation cohort. A novel HRFTNomogram might help predict the survival of locally advanced ESCC patients treated with NCRT followed by esophagectomy.
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Affiliation(s)
- Xiao-Wen Lin
- Department of Clinical Laboratory Medicine, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China
- Department of Clinical Laboratory Medicine, Maternity and Child, Healthcare Hospital of Nanshan District, Shenzhen, Guangdong, People's Republic of China
| | - Hao Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China
- Guangdong Esophageal Cancer Institute, Guangzhou, Guangdong, People's Republic of China
| | - Xiu-Ying Xie
- Guangdong Esophageal Cancer Institute, Guangzhou, Guangdong, People's Republic of China
| | - Can-Tong Liu
- Department of Clinical Laboratory Medicine, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China
- Guangdong Esophageal Cancer Institute, Guangzhou, Guangdong, People's Republic of China
- Esophageal Cancer Prevention and Control Research Center, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, People's Republic of China
| | - Yi-Wei Lin
- Department of Clinical Laboratory Medicine, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China
- Guangdong Esophageal Cancer Institute, Guangzhou, Guangdong, People's Republic of China
- Esophageal Cancer Prevention and Control Research Center, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, People's Republic of China
| | - Yi-Wei Xu
- Department of Clinical Laboratory Medicine, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China.
- Guangdong Esophageal Cancer Institute, Guangzhou, Guangdong, People's Republic of China.
- Esophageal Cancer Prevention and Control Research Center, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, People's Republic of China.
| | - Xin-Jia Wang
- Esophageal Cancer Prevention and Control Research Center, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, People's Republic of China.
- Department of Orthopedics, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China.
| | - Fang-Cai Wu
- Esophageal Cancer Prevention and Control Research Center, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, People's Republic of China.
- Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China.
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Yehan Z, Ying L, Peng G, Zongyao H, Chengmin Z, Hong Y, Sheng Q, Jie Z, Yi W, Xuefeng L, Wenwu H, Qifeng W, Yang L. Prognostic significance of positive lymph node regression grade to neoadjuvant chemoradiation for esophageal squamous cell carcinoma. J Surg Oncol 2024; 129:708-717. [PMID: 38124398 DOI: 10.1002/jso.27555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/25/2023] [Accepted: 11/26/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND AND PURPOSE To assess the relationship between metastatic lymph node (LN) responder status and recurrence-free survival (RFS) in patients undergoing neoadjuvant chemoradiotherapy (NCRT). MATERIALS AND METHODS We retrospectively reviewed 304 patients with local advanced esophageal squamous cell carcinoma received NCRT followed by esophagectomy. For 112 patients with positive node, according to the proportion of residual viable tumor cells area within the whole tumor beds of all metastatic LNs, we classified LN-tumor regression grade (LN-TRG) into four categories: grade 1, 0%; 2, <10%; 3, 10%-50%; 4, >50%. Patients with grade 1-2 LN-TRG of were considered LN responders, and those with grades 3-4, as LN nonresponders. Univariate and multivariate analyses of RFS were estimated by a Cox regression model, Kaplan-Meier curve, and log-rank test. RESULTS The median follow-up time of a total of 112 patients was 29.6 months. Fifty-two (46.4%) patients have experienced recurrence. In Cox univariate analysis, differentiation, AJCC stage LN responder status, nerve invasion, and lymphovascular invasion significantly correlated with RFS. Multivariate analysis for RFS revealed that LN responder status and AJCC stage (p < 0.05) were independent prognostic factor. The 3-year RFS rates for patients with LN-TRG of 1-4 grades were 72.7%, 76.5%, 37.4%, and 28.5%, respectively, and the median RFS times were not reach, 43.56, 28.09, and 22.77, respectively. CONCLUSIONS LN responder status is an independent prognostic factor for RFS in esophageal cancer patients who received NCRT.
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Affiliation(s)
- Zhou Yehan
- Department of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Liu Ying
- Graduate School, Chengdu Medical College, Chengdu, China
| | - Guo Peng
- Department of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Huang Zongyao
- Department of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhou Chengmin
- Department of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Yang Hong
- Department of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Qin Sheng
- Department of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhu Jie
- Department of Radiotherapy, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Wang Yi
- Department of Radiotherapy, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Leng Xuefeng
- Department of Thoracic Surgery, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - He Wenwu
- Department of Thoracic Surgery, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Wang Qifeng
- Department of Radiotherapy, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Liu Yang
- Department of Pathology, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
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Zhou Y, He W, Guo P, Zhou C, Luo M, Liu Y, Yang H, Qin S, Leng X, Huang Z, Liu Y. Development and Validation of a Recurrence-Free Survival Prediction Model for Locally Advanced Esophageal Squamous Cell Carcinoma with Neoadjuvant Chemoradiotherapy. Ann Surg Oncol 2024; 31:178-191. [PMID: 37751117 PMCID: PMC10695895 DOI: 10.1245/s10434-023-14308-3] [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: 02/27/2023] [Accepted: 08/30/2023] [Indexed: 09/27/2023]
Abstract
BACKGROUND A recurrence-free survival (RFS) prediction model was developed and validated for patients with locally advanced esophageal squamous cell carcinoma treated with neoadjuvant chemoradiotherapy (NCRT) in combination with surgery. PATIENTS AND METHODS We included 282 patients with esophageal squamous cell carcinoma who received neoadjuvant chemoradiotherapy (NCRT) combined with surgery, constructed three models incorporating pathological factors, investigated the discrimination and calibration of each model, and compared the clinical utility of each model using the net reclassification index (NRI) and the integrated discrimination index (IDI). RESULTS Multivariable analysis showed that pathologic complete response (pCR) and lymph node tumor regression grading (LN-TRG) (p < 0.05) were independent prognostic factors for RFS. LASSO regression screened six correlates of LN-TRG, vascular invasion, nerve invasion, degree of differentiation, platelet grade, and a total diameter of residual cancer in lymph nodes to build model three, which was consistent in terms of efficacy in the training set and validation set. Kaplan-Meier (K-M) curves showed that all three models were able to distinguish well between high- and low-risk groups (p < 0.01). The NRI and IDI showed that the clinical utility of model 2 was slightly better than that of model 1 (p > 0.05), and model 3 was significantly better than that of model 2 (p < 0.05). CONCLUSIONS Clinical prediction models incorporating LN-TRG factors have high predictive efficacy, can help identify patients at high risk of recurrence after neoadjuvant therapy, and can be used as a supplement to the AJCC/TNM staging system while offering a scientific rationale for early postoperative intervention.
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Affiliation(s)
- Yehan Zhou
- Department of Pathology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Wenwu He
- Department of Thoracic Surgery, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Peng Guo
- Department of Pathology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Chengmin Zhou
- Department of Pathology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Min Luo
- School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Ying Liu
- Graduate School, Chengdu Medical College, Chengdu, China
| | - Hong Yang
- Department of Pathology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Sheng Qin
- Department of Pathology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xuefeng Leng
- Department of Thoracic Surgery, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Zongyao Huang
- Department of Pathology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
| | - Yang Liu
- Department of Pathology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
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He Q, Luo Z, Zou H, Ye B, Wu L, Deng Y, Yang M, Wang D, Wang Q, Zhang K. A prognostic nomogram that includes MPV in esophageal squamous cell carcinoma. Cancer Med 2023; 12:20266-20276. [PMID: 37807972 PMCID: PMC10652314 DOI: 10.1002/cam4.6551] [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: 02/15/2023] [Revised: 08/13/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023] Open
Abstract
BACKGROUND Mean platelet volume (MPV), as a marker of platelet activity, has been shown to be an efficient prognostic biomarker in several types of cancer. Using MPV, this study aimed to create and validate a prognostic nomogram to the overall survival in esophageal squamous cell carcinoma (ESCC) patients. METHODS The nomogram was constructed and tested using data from a retrospective study of 1893 patients who were randomly assigned to the training and testing cohorts with a 7:3 randomization. In order to screen out the optimal predictors for overall survival (OS), we conducted the LASSO-cox regression, univariate, and multivariate cox regression analyses. Subsequently, the predictive accuracy of the nomogram was validated in both the training and the testing cohorts. Finally, decision curve analysis (DCA) was used to confirm clinical validity. RESULTS Age, MPV, nerve invasion, T stage, and N stage were found as independent prognostic variables for OS and were further developed into a nomogram. The nomogram's prediction accuracy for 1-, 3-, and 5-year OS was 0.736, 0.749, 0.774, and 0.724, 0.719, 0.704 in the training and testing cohorts, respectively. Furthermore, DCA results indicated that nomograms outperformed the AJCC 8th and conventional T, N staging systems in both the training and testing cohorts. CONCLUSIONS The nomogram, in conjunction with MPV and standard clinicopathological markers, could improve the accuracy of prediction of OS in ESCC patients.
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Affiliation(s)
- Qiao He
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Zhenglian Luo
- Department of Transfusion Medicine, West China HospitalSichuan UniversityChengduChina
| | - Haiming Zou
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Bo Ye
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Lichun Wu
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Yao Deng
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Mu Yang
- Centre for Translational Research in CancerSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Dongsheng Wang
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Qifeng Wang
- Department of Radiation OncologySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Kaijiong Zhang
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
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Liu T, Li M, Cheng W, Yao Q, Xue Y, Wang X, Jin H. A clinical prognostic model for patients with esophageal squamous cell carcinoma based on circulating tumor DNA mutation features. Front Oncol 2023; 12:1025284. [PMID: 36686833 PMCID: PMC9850098 DOI: 10.3389/fonc.2022.1025284] [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: 08/22/2022] [Accepted: 12/14/2022] [Indexed: 01/07/2023] Open
Abstract
Background Few predictive models have included circulating tumor DNA (ctDNA) indicators to predict prognosis of esophageal squamous cell carcinoma (ESCC) patients. Here, we aimed to explore whether ctDNA can be used as a predictive biomarker in nomogram models to predict the prognosis of patients with ESCC. Methods We included 57 patients who underwent surgery and completed a 5-year follow-up. With next-generation sequencing, a 61-gene panel was used to evaluate plasma cell-free DNA and white blood cell genomic DNA from patients with ESCC. We analyzed the relationship between the mutation features of ctDNA and the prognosis of patients with ESCC, identified candidate risk predictors by Cox analysis, and developed nomogram models to predict the 2- and 5-year disease-free survival (DFS) and overall survival (OS). The area under the curve of the receiver operating characteristic (ROC) curve, concordance index (C-index), calibration plot, and integrated discrimination improvement (IDI) were used to evaluate the performance of the nomogram model. The model was compared with the traditional tumor-nodes-metastasis (TNM) staging system. Results The ROC curve showed that the average mutant allele frequency (MAF) of ctDNA variants and the number of ctDNA variants were potential biomarkers for predicting the prognosis of patients with ESCC. The predictors included in the models were common candidate predictors of ESCC, such as lymph node stage, angiolymphatic invasion, drinking history, and ctDNA characteristics. The calibration curve demonstrated consistency between the observed and predicted results. Moreover, our nomogram models showed clear prognostic superiority over the traditional TNM staging system (based on C-index, 2-year DFS: 0.82 vs. 0.64; 5-year DFS: 0.78 vs. 0.65; 2-year OS: 0.80 vs. 0.66; 5-year OS: 0.77 vs. 0.66; based on IDI, 2-year DFS: 0.33, p <0.001; 5-year DFS: 0.18, p = 0.04; 2-year OS: 0.28, p <0.001; 5-year OS: 0.15, p = 0.04). The comprehensive scores of the nomogram models could be used to stratify patients with ESCC. Conclusions The novel nomogram incorporating ctDNA features may help predict the prognosis of patients with resectable ESCC. This model can potentially be used to guide the postoperative management of ESCC patients in the future, such as adjuvant therapy and follow-up.
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Affiliation(s)
- Tao Liu
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Mengxing Li
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Wen Cheng
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Qianqian Yao
- Department of Medical Science, Shanghai AccuraGen Biotechnology Co., Ltd., Shanghai, China
| | - Yibo Xue
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Xiaowei Wang
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China,*Correspondence: Hai Jin, ; Xiaowei Wang,
| | - Hai Jin
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China,*Correspondence: Hai Jin, ; Xiaowei Wang,
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Wang Y, Song T, Li K, Liu H, Han Y, Xu T, Cao F, Li Y, Yu Y. Heparanase is a prognostic biomarker independent of tumor purity and hypoxia based on bioinformatics and immunohistochemistry analysis of esophageal squamous cell carcinoma. World J Surg Oncol 2022; 20:236. [PMID: 35840985 PMCID: PMC9288057 DOI: 10.1186/s12957-022-02698-9] [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: 01/01/2022] [Accepted: 07/02/2022] [Indexed: 11/10/2022] Open
Abstract
Background Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive tract with a poor prognosis. The tumor microenvironment (TME) is mainly composed of tumor cells, stromal cells, and immune cells and plays an important role in ESCC development. There are substantial differences in tumor purity among different parts of ESCC tissues, consisting of distinct immune and stromal cells and variations in the status of hypoxia. Thus, prognostic models of ESCC based on bioinformatic analysis of tumor tissues are unreliable. Method Differentially expressed genes (DEGs) independent of tumor purity and hypoxia were screened by Spearman correlation analysis of public ESCC cohorts. Subsequently, the DEGs were subjected to Cox regression analysis. Then, we constructed a protein–protein interaction (PPI) network of the DEGs using Cytoscape. Intersection analysis of the univariate Cox and PPI results indicated that heparanase (HPSE), an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains, was a predictive factor. Gene set enrichment analysis (GSEA) was used to reveal the potential function of HPSE, and single-cell sequencing data were analyzed to evaluate the distribution of HPSE in immune cells. Furthermore, a human ESCC tissue microarray was used to validate the expression and prognostic value of HPSE. Result We found that HPSE was downregulated in ESCC tissues and was not correlated with tumor purity or hypoxia status. HPSE is involved in multiple biological processes. ESCC patients with low HPSE expression in cancerous tissues exhibited poor prognosis. Conclusions These results indicate that low HPSE expression in cancerous tissues correlates with poor prognosis in patients with ESCC. HPSE is a novel prognostic biomarker independent of tumor purity and hypoxia status in ESCC. Supplementary Information The online version contains supplementary material available at 10.1186/s12957-022-02698-9.
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Affiliation(s)
- Yu Wang
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, 442000, People's Republic of China
| | - Tongjun Song
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, 442000, People's Republic of China
| | - Kai Li
- Department of Pathology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, 442000, People's Republic of China
| | - Hao Liu
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, 442000, People's Republic of China
| | - Yan Han
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, 442000, People's Republic of China
| | - Tao Xu
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, 442000, People's Republic of China
| | - Fengjun Cao
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, 442000, People's Republic of China
| | - Yong Li
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, 442000, People's Republic of China.
| | - Yuandong Yu
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, 442000, People's Republic of China.
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Chen M, Hong Z, Shen Z, Gao L, Kang M. Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based Study. Front Surg 2022; 9:927457. [PMID: 35693314 PMCID: PMC9174609 DOI: 10.3389/fsurg.2022.927457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 05/03/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveNeoadjuvant chemoradiotherapy (nCRT) plays an important role in patients with locally advanced esophageal cancer (EC). We aim to determine the prognostic risk factors and establish a reliable nomogram to predict overall survival (OS) based on SEER population.MethodsPatients with EC coded by 04–15 in the SEER database were included. The data were divided into training group and verification group (7:3). The Cox proportional-risk model was evaluated by using the working characteristic curve (receiver operating characteristic curve, ROC) and the area under the curve (AUC), and a nomogram was constructed. The calibration curve was used to measure the consistency between the predicted and the actual results. Decision curve analysis (DCA) was used to evaluate its clinical value. The best cut-off value of nomogram score in OS was determined by using X-tile software, and the patients were divided into low-risk, medium-risk, and high-risk groups.ResultsA total of 2,209 EC patients who underwent nCRT were included in further analysis, including 1,549 in the training cohort and 660 in the validation group. By Cox analysis, sex, marital status, T stage, N stage, M stage, and pathological grade were identified as risk factors. A nomogram survival prediction model was established to predict the 36-, 60-, and 84-month survival. The ROC curve and AUC showed that the model had good discrimination ability. The correction curve was in good agreement with the prediction results. DCA further proved the effective clinical value of the nomogram model. The results of X-tile analysis showed that the long-term prognosis of patients in the low-risk subgroup was better in the training cohort and the validation cohort (p < 0.001).ConclusionThis study established an easy-to-use nomogram risk prediction model consisting of independent prognostic factors in EC patients receiving nCRT, helping to stratify risk, identify high-risk patients, and provide personalized treatment options.
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Affiliation(s)
- Mingduan Chen
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
| | - Zhinuan Hong
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
| | - Zhimin Shen
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
| | - Lei Gao
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
- Correspondence: Mingqiang Kang Lei Gao
| | - Mingqiang Kang
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
- Correspondence: Mingqiang Kang Lei Gao
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