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Zeng R, Zhou X, Ou K, Chen W, Yang C, Wang T, Li Y, Zha Y, Li M, Zhang J. Case report: Long-term survival in synchronous double primary malignancies of lung adenocarcinomas and esophageal squamous cell carcinoma treated with definitive chemoradiotherapy and SBRT combined with anti-PD-1. Front Immunol 2025; 16:1548176. [PMID: 40028319 PMCID: PMC11867956 DOI: 10.3389/fimmu.2025.1548176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2024] [Accepted: 01/29/2025] [Indexed: 03/05/2025] Open
Abstract
Background The occurrence of multiple primary cancers has become common, and the treatment of such patients is very complex, so it is necessary to combine a variety of individualized treatment methods to achieve better treatment results. Case description This report describes a patient with double primary tumors of lung and esophageal cancer had more than 36 months survival with non-operation treatment. The patient diagnosed as lung adenocarcinomas (LADC) and esophageal squamous cell carcinoma (ESCC), was treated with albumin-bound paclitaxel, nedaplatin, and anti-programmed death 1 (anti-PD-1). The esophageal lesions achieved complete response (CR) after finishing two courses of induction chemotherapy combined with anti-PD-1 followed by definitive chemoradiotherapy (CRT). Radiation pneumonitis (RP) occurred one month after the completion of CRT. The pneumonia was relieved after dexamethasone and moxifloxacin treatment. Then, the lung lesion was treated with oral chemotherapy followed by stereotactic body radiation therapy (SBRT). As of July 2024, the patient has survived for more than 3 years after the above treatments, and the current efficacy evaluation is CR of esophageal lesions, PR of pulmonary lesions. Conclusion The multi-modality approach of systemic therapy combined with localized radiotherapy is an effective treatment in the patients of the double primary malignant tumors of LADC and ESCC. The safety and toxicity of radiotherapy for the thoracic double primary tumors demonstrate acceptability.
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Affiliation(s)
- Rui Zeng
- The First Clinical Medical College, Guangdong Medical University, Zhanjiang, Guangdong, China
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
| | - Xiaoyun Zhou
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
- Department of Radiation Oncology, Shenzhen University Medical School, Shenzhen, Guangdong, China
| | - Kexin Ou
- The First Clinical Medical College, Guangdong Medical University, Zhanjiang, Guangdong, China
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
| | - Wei Chen
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
| | - Chen Yang
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
| | - Ting Wang
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
| | - Yani Li
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
| | - Yawen Zha
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
| | - Minying Li
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
| | - Jingjing Zhang
- The First Clinical Medical College, Guangdong Medical University, Zhanjiang, Guangdong, China
- Department of Radiotherapy, People’s Hospital of Zhongshan, Zhongshan, Guangdong, China
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Gu Y, Zou X, Zhu J, Wu G. Efficacy and safety of camrelizumab combined with chemotherapy as second-line treatment for locally advanced, recurrent, or metastatic esophageal squamous cell carcinoma. World J Surg Oncol 2025; 23:38. [PMID: 39905538 DOI: 10.1186/s12957-025-03690-9] [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: 10/06/2024] [Accepted: 01/28/2025] [Indexed: 02/06/2025] Open
Abstract
BACKGROUND This study aims to evaluate the efficacy and safety of camrelizumab in combination with chemotherapy as a second-line treatment for patients with locally advanced, recurrent, or metastatic esophageal squamous cell carcinoma (ESCC). METHODS In this retrospective, single-center observational study, we collected medical records of patients with locally advanced, recurrent, or metastatic ESCC who received either camrelizumab combined with chemotherapy or chemotherapy alone as second-line treatment between July 1, 2019, and May 31, 2023. We evaluated short-term efficacy, including overall response rate (ORR) and disease control rate (DCR), as well as survival outcomes, including progression-free survival (PFS) and overall survival (OS). Safety was also assessed. Additionally, factors influencing OS in ESCC patients were analyzed. RESULTS A total of 60 patients with locally advanced, recurrent, or metastatic ESCC were included, with 30 receiving camrelizumab combined with chemotherapy and 30 receiving chemotherapy alone as second-line treatment. There were no statistically significant differences in ORR (33.33% vs. 13.33%) and DCR (73.33% vs. 56.67%) between the combination therapy and chemotherapy-alone groups (P > 0.05). However, the median PFS was significantly longer in the combination therapy group compared to the chemotherapy group (4.7 months vs. 3.4 months, P = 0.048). Additionally, the median OS was significantly improved in the combination therapy group compared to the chemotherapy group (11.7 months vs. 6.5 months, P = 0.003). Age and history of radical surgery were significantly associated with OS in patients receiving camrelizumab combined with chemotherapy as second-line treatment (P < 0.05). CONCLUSION Second-line treatment with camrelizumab combined with chemotherapy is well-tolerated and associated with favorable oncological outcomes in patients with locally advanced, recurrent, or metastatic ESCC. Furthermore, younger patients and those who have undergone radical surgery may derive greater benefit from camrelizumab combined with chemotherapy as a second-line treatment.
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Affiliation(s)
- Yinfang Gu
- Department of Oncology, Cancer Center, Meizhou People's Hospital (Huangtang Hospital, Meizhou Academy of Medical Sciences, 63 Huangtang Road, Meizhou, 514031, Guangdong, People's Republic of China.
- Guangdong Provincial Engineering and Technological Research Center for Clinical Molecular Diagnosis and Antibody Drugs, 63 Huangtang Road, Meizhou, 514031, Guangdong, People's Republic of China.
| | - Xiaofang Zou
- Department of Oncology, Cancer Center, Meizhou People's Hospital (Huangtang Hospital, Meizhou Academy of Medical Sciences, 63 Huangtang Road, Meizhou, 514031, Guangdong, People's Republic of China
- Guangdong Provincial Engineering and Technological Research Center for Clinical Molecular Diagnosis and Antibody Drugs, 63 Huangtang Road, Meizhou, 514031, Guangdong, People's Republic of China
| | - Junlin Zhu
- Department of Oncology, Cancer Center, Meizhou People's Hospital (Huangtang Hospital, Meizhou Academy of Medical Sciences, 63 Huangtang Road, Meizhou, 514031, Guangdong, People's Republic of China
- Guangdong Provincial Engineering and Technological Research Center for Clinical Molecular Diagnosis and Antibody Drugs, 63 Huangtang Road, Meizhou, 514031, Guangdong, People's Republic of China
| | - Guowu Wu
- Department of Oncology, Cancer Center, Meizhou People's Hospital (Huangtang Hospital, Meizhou Academy of Medical Sciences, 63 Huangtang Road, Meizhou, 514031, Guangdong, People's Republic of China.
- Guangdong Provincial Engineering and Technological Research Center for Clinical Molecular Diagnosis and Antibody Drugs, 63 Huangtang Road, Meizhou, 514031, Guangdong, People's Republic of China.
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Wang R, Liu X, Cai H, Li B, Li Y. A nomogram to predict long-term survival after resection for esophageal cancer: An observational study in northeast China. Surgery 2025; 178:108968. [PMID: 39689614 DOI: 10.1016/j.surg.2024.108968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 10/08/2024] [Accepted: 11/13/2024] [Indexed: 12/19/2024]
Abstract
OBJECTIVE This study aims to create a prognostic nomogram by combining clinicopathologic variables that are linked to the overall survival following the surgical removal of esophageal squamous cell carcinoma. METHODS A total of 224 patients with esophageal cancer who underwent surgical R0 resection were included. The construction of the nomogram involved using a multivariable Cox proportional hazards regression model. To evaluate the model's effectiveness, Kaplan-Meier curves and calibration plots were used for discrimination and calibration, respectively. RESULTS Nearly half of the patients were >60 years old (45.1%), and 95.5% of the patients were male. After esophageal cancer resection, 35.7% of patients experienced complications, with 23.7% developing anastomotic stenosis and 4.5% developing a fistula. Using the backward selection of clinically relevant variables, we found that tumor located in middle thoracic (hazard ratio 2.299, 95% confidence interval 1.008-5.244), anastomotic fistula (3.028, 1.436-6.384), and vascular invasion (2.175, 1.496-3.108) were independently associated with mortality (all P < .05), whereas lymph node clearance ≥15 nodes is associated with longer survival (0.444, 0.278-0.710) (P = .001). On the basis of these factors, a nomogram was created to predict survival of esophageal squamous cell carcinoma after resection. Discrimination using Kaplan-Meier curves, calibration curves, and bootstrap cross-validation revealed good predictive abilities (C index, 0.673). CONCLUSIONS A nomogram was created based on the experience from northeast China to forecast overall survival following resection for esophageal squamous cell carcinoma. The validation process demonstrated accurate distinction and calibration, indicating the practical value of the nomogram in enhancing personalized survival predictions for patients who undergo esophageal squamous cell carcinoma resection in this study population.
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Affiliation(s)
- Rui Wang
- Department of Thoracic Surgery, Organ Transplantation Center, First Hospital of Jilin University, Changchun, China
| | - Xin Liu
- Department of Thoracic Surgery, Organ Transplantation Center, First Hospital of Jilin University, Changchun, China
| | - Hongfei Cai
- Department of Thoracic Surgery, Organ Transplantation Center, First Hospital of Jilin University, Changchun, China
| | - Bo Li
- School of Public Health, Jilin University, Changchun, China
| | - Yang Li
- Department of Thoracic Surgery, Organ Transplantation Center, First Hospital of Jilin University, Changchun, China.
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Zheng H, Wu R, Zhang G, Wang Q, Li Q, Zhang L, Li H, Wang Y, Xie L, Guo X. Nomograms for prognosis prediction in esophageal adenocarcinoma: realities and challenges. Clin Transl Oncol 2025; 27:449-457. [PMID: 39083141 DOI: 10.1007/s12094-024-03589-z] [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: 04/01/2024] [Accepted: 06/30/2024] [Indexed: 02/01/2025]
Abstract
Prognostic assessment is of great significance for individualized treatment and care of cancer patients. Although the TNM staging system is widely used as the primary prognostic classifier for solid tumors in clinical practice, the complexity of tumor occurrence and development requires more personalized probability prediction models than an ordered staging system. By integrating clinical, pathological, and molecular factors into digital models through LASSO and Cox regression, a nomogram could provide more accurate personalized survival estimates, helping clinicians and patients develop more appropriate treatment and care plans. Esophageal adenocarcinoma (EAC) is a common pathological subtype of esophageal cancer with poor prognosis. Here, we screened and comprehensively reviewed the studies on EAC nomograms for prognostic prediction, focusing on performance evaluation and potential prognostic factors affecting survival. By analyzing the strengths and limitations of the existing nomograms, this study aims to provide assistance in constructing high-quality prognostic models for EAC patients.
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Affiliation(s)
- Hong Zheng
- School of Basic Medical Sciences, Henan University, Kaifeng, China
- Institute of Biomedical Informatics, Henan University, Kaifeng, China
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
| | - Rong Wu
- School of Basic Medical Sciences, Henan University, Kaifeng, China
- Institute of Biomedical Informatics, Henan University, Kaifeng, China
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
| | - Guosen Zhang
- School of Basic Medical Sciences, Henan University, Kaifeng, China
- Institute of Biomedical Informatics, Henan University, Kaifeng, China
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
| | - Qiang Wang
- Institute of Biomedical Informatics, Henan University, Kaifeng, China
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
- School of Software, Henan University, Kaifeng, China
| | - Qiongshan Li
- School of Basic Medical Sciences, Henan University, Kaifeng, China
- Institute of Biomedical Informatics, Henan University, Kaifeng, China
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
| | - Lu Zhang
- School of Basic Medical Sciences, Henan University, Kaifeng, China
- Institute of Biomedical Informatics, Henan University, Kaifeng, China
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
| | - Huimin Li
- School of Basic Medical Sciences, Henan University, Kaifeng, China
- Institute of Biomedical Informatics, Henan University, Kaifeng, China
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
| | - Yange Wang
- School of Basic Medical Sciences, Henan University, Kaifeng, China
- Institute of Biomedical Informatics, Henan University, Kaifeng, China
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
| | - Longxiang Xie
- School of Basic Medical Sciences, Henan University, Kaifeng, China
- Institute of Biomedical Informatics, Henan University, Kaifeng, China
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
| | - Xiangqian Guo
- School of Basic Medical Sciences, Henan University, Kaifeng, China.
- Institute of Biomedical Informatics, Henan University, Kaifeng, China.
- Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China.
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Liu QW, Liu L, Hu JX, Hou JQ, He WB, Shu YS, Wang XL. Nomogram based on a novel nutritional immune-inflammatory status score to predict postoperative outcomes in esophageal squamous cell carcinoma. World J Gastroenterol 2025; 31:101749. [PMID: 39877711 PMCID: PMC11718640 DOI: 10.3748/wjg.v31.i4.101749] [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: 09/25/2024] [Revised: 11/13/2024] [Accepted: 12/06/2024] [Indexed: 12/30/2024] Open
Abstract
BACKGROUND The relationship between patient nutritional, immune, and inflammatory status is linked to tumor progression and prognosis. However, there are limited studies on the prognosis of esophageal squamous cell carcinoma (ESCC) after surgery based on the comprehensive indicators of these factors. AIM To develop and validate a novel nomogram based on a nutritional immune-inflammatory status (NIIS) score for predicting postoperative outcomes in ESCC. METHODS This retrospective study examined 829 patients with ESCC who underwent radical surgery between June 2016 and June 2020, with 568 patients in the training cohort and 261 patients in the validation cohort. We incorporated comprehensive indicators related to nutrition, immunity, and inflammation to develop the NIIS score, using LASSO regression. Subsequently, a nomogram combining the NIIS score and other clinicopathological parameters was developed and validated using calibration curves, time-dependent area under curves, and decision curve analysis. RESULTS We identified eight indicators that constitute the NIIS score. High-risk scores emerged as an independent risk factor for overall survival [training set HR 2.497 (1.802, 3.458), P < 0.001]. A NIIS nomogram for personalized prognostic prediction was developed by integrating the NIIS score with clinicopathological variables, yielding enhanced predictive value relative to individual indicators and the UICC/TNM staging system. CONCLUSION The NIIS score provides strong predictive value for postoperative outcomes in ESCC, thus offering a valuable tool for clinical decision-making.
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Affiliation(s)
- Qing-Wen Liu
- Department of Graduate School, Dalian Medical University, Dalian 116000, Liaoning Province, China
| | - Lin Liu
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi 214000, Jiangsu Province, China
| | - Jun-Xi Hu
- Clinical Medical College, Yangzhou University, Yangzhou 225000, Jiangsu Province, China
| | - Jia-Qi Hou
- Department of Graduate School, Dalian Medical University, Dalian 116000, Liaoning Province, China
| | - Wen-Bo He
- Clinical Medical College, Yangzhou University, Yangzhou 225000, Jiangsu Province, China
| | - Yu-Sheng Shu
- Department of Thoracic Surgery, Northern Jiangsu People's Hospital, Yangzhou 225000, Jiangsu Province, China
| | - Xiao-Lin Wang
- Department of Thoracic Surgery, Northern Jiangsu People's Hospital, Yangzhou 225000, Jiangsu Province, China
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Bangolo A, Nagesh VK, Simonson G, Thapa A, Ram A, Santhakumari NJ, Chamroukh R, Varughese VJ, Nareeba S, Menon A, Sridharan K, Chacko AA, Mansour C, Elias D, Singh GR, Rambaransingh A, Mendez LR, Levy C, Kianifar Aguilar I, Hamad I, Sharma U, Salcedo J, Tran HHV, Haq A, Geleto TB, Jean K, Periel L, Bravin S, Weissman S. The Impact of Tumor Stage and Histopathology on Survival Outcomes in Esophageal Cancer Patients over the Past Decade. Med Sci (Basel) 2024; 12:70. [PMID: 39728419 DOI: 10.3390/medsci12040070] [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: 09/26/2024] [Revised: 11/04/2024] [Accepted: 12/05/2024] [Indexed: 12/28/2024] Open
Abstract
BACKGROUND Esophageal cancer (EC) is the sixth leading cause of cancer-related mortality worldwide, continuing to be a significant public health concern. The purpose of this study is to assess the impact of staging and histopathology of EC on associated mortality. The study also aims to further investigate clinical characteristics, prognostic factors, and survival outcomes in patients diagnosed with EC between 2010 and 2017. Furthermore, we analyzed the interaction between tumor histology and staging and the risk of mortality. METHODS A total of 24,011 patients diagnosed with EC between 2010 and 2017 in the United States were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database. Demographic parameters, tumor stage, and histologic subtypes were analyzed and associated overall mortality (OM) and cancer-specific mortality (CSM) were measured across all subgroups. Covariates reaching the level of statistical significance, demonstrable by a p-value equal to or less than 0.01, were incorporated into a multivariate Cox proportional hazards model. A hazard ratio greater than 1 was indicative of an increased risk of mortality in the presence of the variable under discussion. Additionally, the study explores the interaction between histology and tumor stage on outcomes. RESULTS The majority of patients were male (80.13%) and non-Hispanic white (77.87%), with a predominant age at diagnosis of between 60 and 79 years (59.86%). Adenocarcinoma was the most common tumor subtype (68.17%), and most patients were diagnosed at a distant stage (41.29%). Multivariate analysis revealed higher mortality risks for males, older patients, unmarried individuals, and those with advanced-stage tumors. Higher income, receiving radiation or chemotherapy, and undergoing surgery were associated with lower mortality. Tumor subtype significantly influenced mortality, with squamous cell carcinoma and neuroendocrine tumors showing higher hazard ratios compared to adenocarcinoma. Adenocarcinoma is linked to a poorer prognosis at advanced stages, whereas the opposite trend is observed for SCC. CONCLUSIONS The study identifies significant demographic and clinicopathologic factors influencing mortality in esophageal cancer patients, highlighting the importance of early diagnosis and treatment intervention. Future research should focus on tailored treatment strategies to improve survival outcomes in high-risk groups and to understand the interaction between tumor histology and tumor stage.
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Affiliation(s)
- Ayrton Bangolo
- Department of Hematology and Oncology, John Theurer Cancer Center, Hackensack University Medical Center, Hackensack, NJ 07601, USA
| | - Vignesh Krishnan Nagesh
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Grace Simonson
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Abhishek Thapa
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Arun Ram
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | | | - Rayan Chamroukh
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | | | - Shallot Nareeba
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Aiswarya Menon
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Kousik Sridharan
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Angel Ann Chacko
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Charlene Mansour
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Daniel Elias
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Gurinder R Singh
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Aaron Rambaransingh
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Luis Roman Mendez
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Charlotte Levy
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Izage Kianifar Aguilar
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Ibrahim Hamad
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Urveesh Sharma
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Jose Salcedo
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Hadrian Hoang-Vu Tran
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Abdullah Haq
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Tahir B Geleto
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Kaysha Jean
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Luis Periel
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Sara Bravin
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
| | - Simcha Weissman
- Department of Internal Medicine, Hackensack Palisades Medical Center, North Bergen, NJ 07047, USA
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Huang J, Li T, Tang L, Hu Y, Hu Y, Gu Y. Development and Validation of an 18F-FDG PET/CT-based Radiomics Nomogram for Predicting the Prognosis of Patients with Esophageal Squamous Cell Carcinoma. Acad Radiol 2024; 31:5066-5077. [PMID: 38845294 DOI: 10.1016/j.acra.2024.05.029] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/02/2024] [Accepted: 05/16/2024] [Indexed: 11/30/2024]
Abstract
RATIONALE AND OBJECTIVES The aim of this study was to develop and validate a nomogram, integrating clinical factors and radiomics features, capable of predicting overall survival (OS) in patients diagnosed with esophageal squamous cell carcinoma (ESCC). METHODS In this study, we retrospectively analyzed the case data of 130 patients with ESCC who underwent 18F-FDG PET/CT before treatment. Radiomics features associated with OS were screened by univariate Cox regression (p < 0.05). Further selection was performed by applying the least absolute shrinkage and selection operator Cox regression to generate the weighted Radiomics-score (Rad-score). Independent clinical risk factors were obtained by multivariate Cox regression, and a nomogram was constructed by combining Rad-score and independent risk factors. The predictive performance of the model for OS was assessed using the time-dependent receiver operating characteristic curve, concordance index (C-index), calibration curve, and decision curve analysis. RESULTS Five radiomics features associated with prognosis were finally screened, and a Rad-score was established. Multivariate Cox regression analysis revealed that surgery and clinical M stage were identified as independent risk factors for OS in ESCC. The combined clinical-radiomics nomogram exhibited C-index values of 0.768 (95% CI: 0.699-0.837) and 0.809 (95% CI: 0.695-0.923) in the training and validation cohorts, respectively. Ultimately, calibration curves and decision curves for the 1-, 2-, and 3-year OS demonstrated the satisfactory prognostic prediction and clinical utility of the nomogram. CONCLUSION The developed nomogram, leveraging 18F-FDG PET/CT radiomics and clinically independent risk factors, demonstrates a reliable prognostic prediction for patients with ESCC, potentially serving as a valuable tool for guiding and optimizing clinical treatment decisions in the future.
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Affiliation(s)
- Jiahui Huang
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing 210029, China
| | - Tiannv Li
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing 210029, China
| | - Lijun Tang
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing 210029, China
| | - Yuxiao Hu
- Department of PET/CT Center, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and the Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, China
| | - Yao Hu
- Department of PET/CT Center, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and the Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, China
| | - Yingying Gu
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing 210029, China.
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Li X, Li D, Qin S, Ye H, Lin M. Nomogram model for predicting long-term survival in esophageal cancer patients with metastasis after treatment: a SEER-based study. J Thorac Dis 2024; 16:6452-6461. [PMID: 39552912 PMCID: PMC11565330 DOI: 10.21037/jtd-24-742] [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: 05/07/2024] [Accepted: 09/06/2024] [Indexed: 11/19/2024]
Abstract
Background There is a large variance in the long-term survival of esophageal cancer (EC) patients with metastasis after treatment. This study was designed to analyze long-term survival of metastatic EC patients after surgery, radiotherapy and chemotherapy. Methods A retrospective cohort of EC patients with metastasis received surgery, radiotherapy and chemotherapy from 2004 to 2015 was obtained from the Surveillance, Epidemiology and End Results (SEER) database. Univariate Cox and complete subset regression analyses were performed to select prognostic factors. Nomograms were established to predict 3-, 5-, and 8-year overall survival (OS), and their performance was evaluated by receiver operating characteristic (ROC) curve and calibration curve. Results Age at diagnosis [hazard ratio (HR): 1.01; 95% confidence interval (CI): 1.00, 1.02; P=0.04], EC of other sites (HR: 1.78; 95% CI: 1.29, 2.45; P<0.001), lymph node involvement (HR: 1.37; 95% CI: 1.08, 1.37; P=0.009), and poorly differentiated or undifferentiated (grade III or IV) (HR: 1.39; 95% CI: 1.20, 1.76; P=0.006) was the independent risk factors for poor OS in EC patients. Female (HR: 0.58; 95% CI: 0.38, 0.88; P=0.01) showed reduced risks of showing poor OS compared with male population. The established nomograms based on these predictors showed satisfactory discrimination efficacy for predicting 3-, 5-, and 8-year OS in metastatic EC patients after treatment. Conclusions The nomograms showed good efficacy in predicting 3-, 5-, and 8-year OS among metastatic EC patients after surgery, radiotherapy and chemotherapy.
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Affiliation(s)
| | | | - Shuming Qin
- Department of Pathology, The Affiliated Taian City Central Hospital of Qingdao University, Taian, China
| | - Hong Ye
- Department of Pathology, The Affiliated Taian City Central Hospital of Qingdao University, Taian, China
| | - Min Lin
- Department of Pathology, The Affiliated Taian City Central Hospital of Qingdao University, Taian, China
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Yang R, Wei M, Yu X, Su W, Zhou X, Chen H, Zhang G. A Long-term Survival Risk Prediction Model for Patients with Superficial Esophageal Squamous Cell Carcinoma. J Cancer 2024; 15:6204-6212. [PMID: 39513114 PMCID: PMC11540495 DOI: 10.7150/jca.99042] [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: 05/29/2024] [Accepted: 09/04/2024] [Indexed: 11/15/2024] Open
Abstract
Objectives: Given the data regarding the long-term prognosis of superficial esophageal squamous cell carcinoma (SESCC) is still lacking, we aimed to identify reliable prognostic factors and establish a high-precision prognosis model for patients with SESCC. Methods: A retrospective cohort study was conducted including patients with SESCC at a high-volume tertiary medical center. The primary outcome was disease-specific survival (DSS) at the end of follow-up (minimum of 29 months). Independent prognostic factors including innovative hematological and clinicopathological parameters were identified using comprehensive and novel statistical methods including best subset regression (BSR), the univariate and multivariate Cox analysis, lasso regression, and a dynamic nomogram model was established. Results: A total of 1,171 patients were finally enrolled. The median follow-up time is 83 months (range 29-149 months). Ten independent prognostic risk factors for a poor DSS were identified as follows: male (P=0.127), higher Charlson Comorbidity Index (CCI) (P=0.006), poorly differentiated tumor (P<0.001), lymphovascular invasion (LVI) (P<0.001), lymph node metastasis (LNM) (P<0.001), additional treatment (P=0.007), neutrophils over 32.2x109/L (P=0.003), red blood cell (RBC) lower than 4.45x1012/L (P<0.001), hemoglobin (Hb) lower than or equal to 98 g/L (P=0.023), alpha-fetoprotein (AFP) higher than 3.24 ng/ml (P=0.034). Subsequently, an online dynamic nomogram was established (https://yryouzu-tools.shinyapps.io/DynNomapp/). This prediction model showed favourable discrimination ability (area under the curve (AUC) was 0.913 (95% CI: 88.0 - 94.6) and a well-fitted calibration curve. Conclusions: We successfully established a long-term prognosis model for SESCC, which can be applied to effectively predict survival risks for patients, thus strengthening follow-up strategies.
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Affiliation(s)
- Ruoyun Yang
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- The First Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Min Wei
- The First Clinical Medical College, Nanjing Medical University, Nanjing, China
- Department of Gastroenterology, Nanjing Jiangning Hospital, Nanjing, China
| | - Xin Yu
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- The First Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Wei Su
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- The First Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Xiaoying Zhou
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- The First Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Han Chen
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- The First Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Guoxin Zhang
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- The First Clinical Medical College, Nanjing Medical University, Nanjing, China
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10
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Lu F, Yang L, Luo Z, He Q, Shangguan L, Cao M, Wu L. Laboratory blood parameters and machine learning for the prognosis of esophageal squamous cell carcinoma. Front Oncol 2024; 14:1367008. [PMID: 38638851 PMCID: PMC11024676 DOI: 10.3389/fonc.2024.1367008] [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: 01/08/2024] [Accepted: 03/18/2024] [Indexed: 04/20/2024] Open
Abstract
Background In contemporary study, the death of esophageal squamous cell carcinoma (ESCC) patients need precise and expedient prognostic methodologies. Objective To develop and validate a prognostic model tailored to ESCC patients, leveraging the power of machine learning (ML) techniques and drawing insights from comprehensive datasets of laboratory-derived blood parameters. Methods Three ML approaches, including Gradient Boosting Machine (GBM), Random Survival Forest (RSF), and the classical Cox method, were employed to develop models on a dataset of 2521 ESCC patients with 27 features. The models were evaluated by concordance index (C-index) and time receiver operating characteristics (Time ROC) curves. We used the optimal model to evaluate the correlation between features and prognosis and divide patients into low- and high-risk groups by risk stratification. Its performance was analyzed by Kaplan-Meier curve and the comparison with AJCC8 stage. We further evaluate the comprehensive effectiveness of the model in ESCC subgroup by risk score and KDE (kernel density estimation) plotting. Results RSF's C-index (0.746) and AUC (three-year AUC 0.761, five-year AUC 0.771) had slight advantage over GBM and the classical Cox method. Subsequently, 14 features such as N stage, T stage, surgical margin, tumor length, age, Dissected LN number, MCH, Na, FIB, DBIL, CL, treatment, vascular invasion, and tumor grade were selected to build the model. Based on these, we found significant difference for survival rate between low-(3-year OS 81.8%, 5-year OS 69.8%) and high-risk (3-year OS 25.1%, 5-year OS 11.5%) patients in training set, which was also verified in test set (all P < 0.0001). Compared with the AJCC8th stage system, it showed a greater discriminative ability which is also in good agreement with its staging ability. Conclusion We developed an ESCC prognostic model with good performance by clinical features and laboratory blood parameters.
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Affiliation(s)
- Feng Lu
- Department of Experimental Medicine, The People’s Hospital of Jianyang City, Jianyang, Sichuan, China
| | - Linlan Yang
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhenglian Luo
- Department of Transfusion Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Qiao He
- Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Lijuan Shangguan
- Outpatient Department, People’s Hospital of Jianyang, Jianyang, Sichuan, China
| | - Mingfei Cao
- Department of Clinical Laboratory, Chuankong Hospital of Jianyang, Jianyang, Sichuan, China
| | - Lichun Wu
- Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
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11
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Deng M, Li X, Mu H, Wei M, Sun L. Case report: Efficacy of icotinib treatment in lung adenocarcinoma with esophageal squamous cell carcinoma: a rare case of double primary malignant tumors. Front Med (Lausanne) 2024; 11:1266062. [PMID: 38606154 PMCID: PMC11006962 DOI: 10.3389/fmed.2024.1266062] [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: 07/24/2023] [Accepted: 03/14/2024] [Indexed: 04/13/2024] Open
Abstract
Background Lung adenocarcinoma with esophageal squamous cell carcinoma is rare and the prognosis is poor, therefore there is an urgent need to improve this situation. The objective of this study was to explore the effect of first-generation tyrosine kinase inhibitors (TKIs) in the patient of the double primary malignant tumors. Case report We report a case of lung adenocarcinoma with esophageal squamous cell carcinoma treated by icotininb after five-year follow-up. A 71-year-old Chinese woman complaining of swallowing obstruction, heartburn, regurgitation of gastric acid for more than 2 months. An esophageal lesion was found by chest CT scans in T7 vertebral level. The diagnosis by gastroscopic biopsy was squamous cell carcinoma (SCC) with EGFR over-expression. Simultaneously, chest CT showed a 2 cm x 1 cm solitary lesion in the right superior pulmonary. The histological diagnosis by percutaneous lung Biopsy was "adenocarcinoma." Epidermal growth factor receptor (EGFR) gene mutation status was evaluated by Sanger sequencing, and an exon 21 point mutation (L858R) was identified. When the double primary malignant tumors were diagnosed, the patient refused operation and received a tyrosine kinase inhibitor (TKI), icotinib, at the dose of 125 mg, three times per day. All serum tumor biomarkers such as CEA and cancer antigen 125 (CA125) were in the normal range during the treatment period. After five-year follow-up, the patient has no evidence of recurrence or metastasis. The lung cancer was stable, meanwhile the esophageal lesion was almost cured. Conclusion Icotininb is an effective treatment in the patients of the double primary malignant tumors of lung adenocarcinoma with EGFR gene mutation and esophageal squamous cell carcinoma with EGFR over-expression.
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Affiliation(s)
| | | | | | | | - Lan Sun
- Department of Oncology, Bishan Hospital of Chongqing Medical University, Chongqing, China
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12
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Lu G, Fang W, Lin Y, Huang H. Development of a Survival Nomogram for Esophageal Squamous Cell Carcinoma Patients: a Population-Based Analysis. J Gastrointest Cancer 2024; 55:391-401. [PMID: 37804459 DOI: 10.1007/s12029-023-00975-8] [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] [Accepted: 09/27/2023] [Indexed: 10/09/2023]
Abstract
PURPOSE In this study, we developed a prognostic nomogram for esophageal squamous cell carcinoma (ESCC) patients. METHODS Patients diagnosed with ESCC from the Surveillance, Epidemiology, and End Results (SEER) database (1975-2017) and a local hospital were enrolled in this retrospective cohort study. Prognoses were analyzed using the R language software, and the predictive power of the model was then assessed by the Harrell concordance index (C-index) and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. RESULTS In total, 2915 ESCC patients from SEER database were divided into training and validation cohorts. Multivariate analysis revealed that sex, marital status, tumor-node-metastasis (TNM) stage, surgery, chemotherapy, and radiation all showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (also with tumor grade). These characteristics were employed to build a nomogram. The C-index of the nomogram for OS and CSS prediction was 0.743 and 0.748 for the training cohort, which were superior to the predictive power of the 7th TNM staging system. The AUCs of the nomogram for predicting 2- and 5-year OS were 0.805 and 0.812, respectively, and the AUCs for CSS were 0.811 and 0.821, respectively. ROC and calibration curves of data from the SEER internal validation set and of data from our hospital showed that this model had good accuracy for predicting the prognosis of ESCC patient. CONCLUSION The nomogram developed in this study provides a useful tool for accurately estimating OS and CSS for ESCC patients.
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Affiliation(s)
- Guangrong Lu
- Department of Gastroenterology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
| | - Weiyue Fang
- Department of Hematology and Oncology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 109 Xueyuan Western Road, Wenzhou, 325000, Zhejiang, China
| | - Ying Lin
- Department of Hematology and Oncology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 109 Xueyuan Western Road, Wenzhou, 325000, Zhejiang, China
| | - He Huang
- Department of Hematology and Oncology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 109 Xueyuan Western Road, Wenzhou, 325000, Zhejiang, China.
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13
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Xie L, Zhang Z. Survival benefit of combined immunotherapy and chemoradiotherapy in locally advanced unresectable esophageal cancer: an analysis based on the SEER database. Front Immunol 2024; 15:1334992. [PMID: 38292873 PMCID: PMC10825045 DOI: 10.3389/fimmu.2024.1334992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 01/02/2024] [Indexed: 02/01/2024] Open
Abstract
Background While simultaneous chemoradiotherapy remains the established therapeutic modality for patients afflicted with locally advanced esophageal cancer, the effectiveness of this radical approach falls short of the desired outcome. Numerous investigations have illuminated the prospect of enhancing therapeutic efficacy through the amalgamation of chemoradiotherapy and immunotherapeutic interventions. Consequently, we embarked on an examination to scrutinize the potential survival advantages conferred by the confluence of chemoradiotherapy and immunotherapy in relation to locally advanced unresectable esophageal carcinoma, drawing upon the extensive SEER database for our analysis. Methods We extracted clinicopathological attributes and survival statistics of patients afflicted with locally advanced unresectable esophageal carcinoma, diagnosed within the temporal span encompassing the years 2004-2014 and 2019-2020, from the extensive SEER database. To discern disparities in both overall survival (OS) and cancer-specific survival (CSS) between the cohorts subjected to chemoradiotherapy combined with immunotherapy and chemoradiotherapy alone, we employed analytical tools such as Kaplan-Meier analysis, the Log-rank test, the Cox regression proportional risk model, and propensity-matched score (PSM) methodology. Results A total of 7,758 eligible patients were encompassed in this research, with 6,395 individuals having undergone chemoradiotherapy alone, while 1,363 patients received the combined treatment of chemoradiotherapy and immunotherapy. After 1:4 propensity score matching, 6,447 patients were successfully harmonized, yielding a well-balanced cohort. The Kaplan-Meier curves demonstrated a substantial enhancement in OS (P = 0.0091) and CSS (P < 0.001) for the group subjected to chemoradiotherapy combined with immunotherapy as compared to chemoradiotherapy alone. Further multivariable analysis with PSM confirmed that chemoradiotherapy combined with immunotherapy benefits OS(HR=0.89, 95% CI 0.81-0.98) and CSS (HR=0.68, 95% CI 0.61-0.76). In addition, Univariable and multivariable Cox regression analyses of the matched patient groups unveiled several independent prognostic factors for OS and CSS, including sex, age, marital status, tumor location, tumor size, pathologic grade, SEER historic staging, and treatment modality. Among these factors, being female, married, and receiving chemoradiotherapy combined with immunotherapy emerged as independent protective factors, while age exceeding 75 years, non-superior segment tumor location, tumor size greater than 6 cm, Grade 3-4 pathology, and regional SEER historic staging were all found to be independent risk factors. The survival advantage of the chemoradiotherapy combined with the immunotherapy group over the chemoradiotherapy alone group was substantial. Conclusions This investigation furnishes compelling evidence that the integration of immunotherapy with chemoradiotherapy confers a noteworthy survival advantage when contrasted with conventional chemoradiotherapy for individuals grappling with locally advanced unresectable esophageal carcinoma.
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Affiliation(s)
- Liangyun Xie
- Hebei Medical University, Shijiazhuang, China
- Department of Radiation Oncology, Affiliated Tangshan Worker’s Hospital, Hebei Medical University, Tangshan, China
| | - Zhi Zhang
- Department of Radiation Oncology, Affiliated Tangshan Worker’s Hospital, Hebei Medical University, Tangshan, China
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GUO JING, TONG CHANGYONG, SHI JIANGUANG, LI XINJIAN, CHEN XUEQIN. A prognosis model for predicting immunotherapy response of esophageal cancer based on oxidative stress-related signatures. Oncol Res 2023; 32:199-212. [PMID: 38196829 PMCID: PMC10774069 DOI: 10.32604/or.2023.030969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 06/20/2023] [Indexed: 01/11/2024] Open
Abstract
Oxidative stress (OS) is intimately associated with tumorigenesis and has been considered a potential therapeutic strategy. However, the OS-associated therapeutic target for esophageal squamous cell carcinoma (ESCC) remains unconfirmed. In our study, gene expression data of ESCC and clinical information from public databases were downloaded. Through LASSO-Cox regression analysis, a risk score (RS) signature map of prognosis was constructed and performed external verification with the GSE53625 cohort. The ESTIMATE, xCell, CIBERSORT, TIMER, and ImmuCellAI algorithms were employed to analyze infiltrating immune cells and generate an immune microenvironment (IM). Afterward, functional enrichment analysis clarified the underlying mechanism of the model. Nomogram was utilized for forecasting the survival rate of individual ESCC cases. As a result, we successfully constructed an OS-related genes (OSRGs) model and found that the survival rate of high-risk groups was lower than that of low-risk groups. The AUC of the ROC verified the strong prediction performance of the signal in these two cohorts further. According to independent prognostic analysis, the RS was identified as an independent risk factor for ESCC. The nomogram and follow-up data revealed that the RS possesses favorable predictive value for the prognosis of ESCC patients. qRT-PCR detection demonstrated increased expression of MPC1, COX6C, CYB5R3, CASP7, and CYCS in esophageal cancer patients. In conclusion, we have constructed an OSRGs model for ESCC to predict patients' prognosis, offering a novel insight into the potential application of the OSRGs model in ESCC.
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Affiliation(s)
- JING GUO
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China
| | - CHANGYONG TONG
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China
| | - JIANGUANG SHI
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China
| | - XINJIAN LI
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China
| | - XUEQIN CHEN
- Department of Chinese Traditional Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, China
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15
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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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Sun D, Yi J, Gong L, Wu Y, Liu X. Prognostic analysis and nomogram establishment in patients with early esophageal cancer receiving endoscopic therapy: a population-based study. Therap Adv Gastroenterol 2023; 16:17562848231170470. [PMID: 37163166 PMCID: PMC10164252 DOI: 10.1177/17562848231170470] [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: 04/25/2022] [Accepted: 04/01/2023] [Indexed: 05/11/2023] Open
Abstract
Background The growing numbers of early esophageal cancer (EEC) have increased the demand for endoscopic therapy. Objectives To clarify the influential factors for the prognosis of patients with EEC receiving endoscopic surgery, and to construct a nomogram to evaluate the prognostic value of endoscopic therapy. Design Prognostic analysis study. Methods Clinical data of EEC patients who received endoscopic therapy between 2004 and 2015 were collected from the Surveillance, Epidemiology, and End Results database and used to construct the nomogram. The prognosis was analyzed by R language; the nomogram was constructed by Cox survival analysis; and the accuracy of the nomogram was verified by C index and the receiver operating characteristic (ROC) and calibration curves. X-Tile software was used to stratify the risk of patients. Results Our study constructed the nomogram of the prognosis of patients with EEC treated by endoscopic surgery, including 1118 patients and 5 independent prognostic factors of esophageal cancer-specific survival. The C index and the area under the ROC curve (AUC) of the training and verification cohorts were all >0.75. The calibration curve also reflected the good consistency of the model in predicting survival. Significant difference in the risk of patients from different stratifications with the same T staging existed, and the model had a better C index than that of the T staging. Conclusion Our study reports potential influential factors affecting the prognosis of EEC patients who received endoscopic therapy and establishes a reliable nomogram to predict the risk and prognosis, which has certain advantages compared with traditional TNM staging system.
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Affiliation(s)
- Danping Sun
- Department of Gastroenterology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jun Yi
- Department of Gastroenterology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Artificial Intelligence Computer Aided Diagnosis and Treatment for Digestive Disease, Changsha, Hunan, China
| | - Lingqi Gong
- Department of Gastroenterology, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Yu Wu
- Department of Gastroenterology, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Kaifu District, Changsha, Hunan 410000 China
- Hunan International Scientific and Technological Cooperation Base of Artificial Intelligence Computer Aided Diagnosis and Treatment for Digestive Disease, Changsha, Hunan, China
| | - Xiaowei Liu
- Department of Gastroenterology, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Kaifu District, Changsha, Hunan 410000, China
- Hunan International Scientific and Technological Cooperation Base of Artificial Intelligence Computer Aided Diagnosis and Treatment for Digestive Disease, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan, China
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Nie Y, Yao G, Li L, Feng A, Zhang W, Xu X, Li Q, Yang Z. Effects of Radiotherapy on Survival of Esophageal Cancer Patients Receiving Immunotherapy: Propensity Score Analysis and Nomogram Construction. Cancer Manag Res 2022; 14:2357-2371. [PMID: 35967755 PMCID: PMC9369108 DOI: 10.2147/cmar.s375821] [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: 06/09/2022] [Accepted: 07/27/2022] [Indexed: 12/24/2022] Open
Abstract
Purpose The present study assessed the effects of radiotherapy on overall survival (OS) and progression-free survival time (PFS) in patients with stage II or higher esophageal cancer receiving immunotherapy; evaluated factors independently prognostic of OS and PFS in these patients; and utilized these factors to establish a prognostic nomogram. Patients and Methods This study enrolled 134 patients with stage II or higher esophageal cancer treated with chemotherapy (platinum-based agents plus paclitaxel or fluorouracil) and immunotherapy. These patients were divided into two groups, a radiotherapy (RT) group (n = 55) and a non-radiotherapy (non-RT) group (n = 79). Following 1:1 propensity score matching, OS and PFS were compared by the Kaplan-Meier method, and factors associated with survival were determined by univariate and multifactorial Cox regression analyses. These factors were used to construct a prognostic nomogram. Results After propensity matching, all covariates were well balanced in the two groups (all P > 0.05). After matching, both median PFS (15.70 months [95% confidence interval (CI) 8.68-22.72 months] vs 5.70 months [95% CI 3.38-8.02 months], P = 0.002) and median OS (15.72 months [95% CI 12.94-18.46 months] vs 12.06 months [95% CI 9.91-14.20 months], P = 0.036) were significantly longer in the RT than in the non-RT group. Univariate and multifactorial analyses showed that RT, neutrophil-lymphocyte ratios, and tumor differentiation were independently prognostic of OS, with all hazard ratios (HRs) <1 and all P-values <0.05. A nomogram based on these factors was constructed, and its accuracy was verified. Conclusion Immunotherapy plus RT resulted in better survival outcomes than immunotherapy alone. A nomogram based on prognostic factors can guide personalized treatment and monitor prognosis.
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Affiliation(s)
- Yuanliu Nie
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, 250021, People’s Republic of China
| | - Guangyue Yao
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, 250021, People’s Republic of China
| | - Liang Li
- Department of Thoracic Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, 250021, People’s Republic of China
| | - Alei Feng
- Tumor Research and Therapy Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, People’s Republic of China
| | - Wentao Zhang
- Shandong First Medical University, Jinan, Shandong, 250021, People’s Republic of China
| | - Xiaoying Xu
- Shandong First Medical University, College of Basic Medicine, Shandong First Medical University-Shandong Academy of Medical Sciences, Jinan, Shandong, 250000, People’s Republic of China
| | - Qiang Li
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, 250021, People’s Republic of China
- Tumor Research and Therapy Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, People’s Republic of China
| | - Zhe Yang
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, 250021, People’s Republic of China
- Tumor Research and Therapy Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, People’s Republic of China
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LncRNA OIP5-AS1 Knockdown Facilitated the Ferroptosis and Immune Evasion by Modulating the GPX4 in Oesophageal Carcinoma. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:8103198. [PMID: 35872956 PMCID: PMC9307385 DOI: 10.1155/2022/8103198] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 05/23/2022] [Accepted: 06/13/2022] [Indexed: 11/18/2022]
Abstract
Objective Oesophageal cancer (EC) is an extremely invasive malignancy, which has bad prognosis that requires safe and effective treatment modalities. Immunotherapy has provided new ideas for the treatment of EC in recent years. This project was conducted to probe into the role and mechanism of lncRNA OIP5-AS1 in ferroptosis and immunotherapy of EC. Methods Cell viability and multiplication were assessed through CCK-8, colony formation assays. Levels of Fe2+, MDA, and lipid ROS were applied to determine ferroptosis. GPX4 and OIP5-AS1 levels were examined through real-time PCR assay. The relationship between OIP5-AS1 and GPX4 was estimated through RNA immunoprecipitation assay. Flow cytometry was applied to examine the effect of OIP5-AS1 on CD8+ T cells. Results OIP5-AS1 inhibition significantly inhibited EC cell viability and proliferation, induced ferroptosis, and downregulated GPX4 levels, while GPX4 reversed these effects. OIP5-AS1/GPX4 induced CD8+ T cell interaction and induced apoptosis through PD-1/PD-L1 immune checkpoints of CD8+ T cells. Conclusion OIP5-AS1/GPX4 promotes EC development and relieved ferroptosis; furthermore, OIP5-AS1/GPX4 facilitated immune evasion via modulation of PD-1/PD-L1, suggesting aiming at OIP5-AS1 is a possible route which might enhance the effectiveness of immunotherapy.
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Leng C, Cui Y, Chen J, Wang K, Yang H, Wen J, Fu J, Liu Q. A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection. Front Oncol 2022; 12:925685. [PMID: 35875105 PMCID: PMC9300830 DOI: 10.3389/fonc.2022.925685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 06/16/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundEsophageal squamous cell carcinoma (ESCC) is characterized clinically by frequent recurrence, leading to a poor prognosis after radical surgery. The aim of this study was to identify a prognostic nomogram to predict the post-progression survival (PPS) of ESCC patients based on the features of primary tumor and recurrence.MethodsA total of 234 ESCC patients who underwent recurrence after radical surgery were enrolled in this study. The independent prognostic factors screened by the univariate and multivariate Cox regression analysis were subsequently used to construct a nomogram. The predictive performance of the nomogram was evaluated with the concordance index (C-index), decision curve, and the area under the receiver operating characteristic curve (AUC) and validated in two validation cohorts. The Kaplan-Meier curves of different recurrence patterns were analyzed.ResultsThe prognostic nomogram of PPS was established by integrating independent prognostic factors, including age, body mass index, number of lymph node dissection, recurrence pattern, and recurrence treatment. The nomogram demonstrated good performance, with C-index values of 0.756, 0.817, and 0.730 for the training and two validation cohorts. The 1-year AUC values were 0.773, 0.798, and 0.735 and 3-year AUC values were 0.832, 0.871, and 0.791, respectively. Furthermore, we found that patients with bone metastasis displayed the worst PPS compared to other isolated recurrence patterns.ConclusionWe constructed a nomogram to reliably predict PPS, which would be valuable to provide individual managements for ESCC patients after radical surgery.
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Affiliation(s)
- Changsen Leng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
| | - Yingying Cui
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Junying Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
| | - Kexi Wang
- Department of Thoracic Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Hong Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
| | - Jing Wen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
- *Correspondence: Qianwen Liu, ; Jianhua Fu, ; Jing Wen,
| | - Jianhua Fu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
- *Correspondence: Qianwen Liu, ; Jianhua Fu, ; Jing Wen,
| | - Qianwen Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
- *Correspondence: Qianwen Liu, ; Jianhua Fu, ; Jing Wen,
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Wang Q, Sun Z, Xu X, Ma X, Zhao X, Ye Q. The Evaluation of a SEER-Based Nomogram in Predicting the Survival of Patients Treated with Neoadjuvant Therapy Followed by Esophagectomy. Front Surg 2022; 9:853093. [PMID: 35846961 PMCID: PMC9276989 DOI: 10.3389/fsurg.2022.853093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/13/2022] [Indexed: 11/13/2022] Open
Abstract
Background A novel nomogram based on the Surveillance, Epidemiology, and End Results (SEER) database has been developed to predict the survival of patients with esophageal carcinoma who received neoadjuvant therapy followed by surgery. We aimed to evaluate the accuracy and value of the nomogram with an external validation cohort. Methods A total of 2,224 patients in SEER database were divided into the training cohort (n = 1556) and the internal validation cohort (n = 668), while 77 patients in our institute were enrolled in the external validation cohort. A Cox proportional hazards regression model was used to develop a nomogram based on the training cohort, while the C-indexes, the calibration curves, receiver operating characteristics curve (ROC), and Kaplan-Meier survival curve were applied in the internal and external validation cohort. Results Five independent risk factors were identified and integrated into the nomogram (C-index = 0.645, 95%CI 0.627–0.663). The nomogram exhibited good prognostic value in the internal validation cohort (C-index = 0.648 95%CI 0.622–0.674). However, the C-index, calibration plot, receiver operating characteristics curve (ROC) analysis, Kaplan-Meier survival curve of the nomogram in the external validation cohort were not as good as the training and internal validation cohort (C-index = 0.584 95%CI 0.445–0.723). Further analysis demonstrated that the resection margin involvement (R0, R1, or R2 resection) was an independent risk factor for the patients, which was not included in the SEER cohort. Conclusions the nomogram based on the SEER database fails to accurately predict the prognosis of the patients in the external validation cohort, which can be caused by the absence of essential information from the SEER database.
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Affiliation(s)
- Qing Wang
- Department of Thoracic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, ShanghaiChina
| | - Zhiyong Sun
- Department of Thoracic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, ShanghaiChina
| | - Xin Xu
- Department of Radiation Oncology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Xiumei Ma
- Department of Radiation Oncology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaojing Zhao
- Department of Thoracic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, ShanghaiChina
- Correspondence: Qing Ye Xiaojing Zhao
| | - Qing Ye
- Department of Thoracic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, ShanghaiChina
- Correspondence: Qing Ye Xiaojing Zhao
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Construction of long non-coding RNA- and microRNA-mediated competing endogenous RNA networks in alcohol-related esophageal cancer. PLoS One 2022; 17:e0269742. [PMID: 35704638 PMCID: PMC9200351 DOI: 10.1371/journal.pone.0269742] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 02/16/2022] [Indexed: 12/13/2022] Open
Abstract
The current study aimed to explore the lncRNA–miRNA–mRNA networks associated with alcohol-related esophageal cancer (EC). RNA-sequencing and clinical data were downloaded from The Cancer Genome Atlas and the differentially expressed genes (DEGs), long non-coding RNAs (lncRNAs, DELs), and miRNAs (DEMs) in patients with alcohol-related and non-alcohol-related EC were identified. Prognostic RNAs were identified by performing Kaplan–Meier survival analyses. Weighted gene co-expression network analysis was employed to build the gene modules. The lncRNA–miRNA–mRNA competing endogenous RNA (ceRNA) networks were constructed based on our in silico analyses using data from miRcode, starBase, and miRTarBase databases. Functional enrichment analysis was performed for the genes in the identified ceRNA networks. A total of 906 DEGs, 40 DELs, and 52 DEMs were identified. There were eight lncRNAs and miRNAs each, including ST7-AS2 and miR-1269, which were significantly associated with the survival rate of patients with EC. Of the seven gene modules, the blue and turquoise modules were closely related to disease progression; the genes in this module were selected to construct the ceRNA networks. SNHG12–miR-1–ST6GAL1, SNHG3–miR-1–ST6GAL1, SPAG5-AS1–miR-133a–ST6GAL1, and SNHG12–hsa-miR-33a–ST6GA interactions, associated with the N-glycan biosynthesis pathway, may have key roles in alcohol-related EC. Thus, the identified biomarkers provide a novel insight into the molecular mechanism of alcohol-related EC.
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Gong XQ, Zhang Y. Develop a nomogram to predict overall survival of patients with borderline ovarian tumors. World J Clin Cases 2022; 10:2115-2126. [PMID: 35321187 PMCID: PMC8895192 DOI: 10.12998/wjcc.v10.i7.2115] [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: 11/29/2021] [Revised: 01/17/2022] [Accepted: 02/23/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The prognosis of borderline ovarian tumors (BOTs) has been the concern of clinicians and patients. It is urgent to develop a model to predict the survival of patients with BOTs.
AIM To construct a nomogram to predict the likelihood of overall survival (OS) in patients with BOTs.
METHODS A total of 192 patients with histologically verified BOTs and 374 patients with epithelial ovarian cancer (EOC) were retrospectively investigated for clinical characteristics and survival outcomes. A 1:1 propensity score matching (PSM) analysis was performed to eliminate selection bias. Survival was analyzed by using the log-rank test and the restricted mean survival time (RMST). Next, univariate and multivariate Cox regression analyses were used to identify meaningful independent prognostic factors. In addition, a nomogram model was developed to predict the 1-, 3-, and 5-year overall survival of patients with BOTs. The predictive performance of the model was assessed by using the concordance index (C-index), calibration curves, and decision curve analysis (DCA).
RESULTS For clinical data, there was no significant difference in body mass index, preoperative CA199 concentration, or tumor localization between the BOTs group and EOC group. Women with BOTs were significantly younger than those with EOC. There was a significant difference in menopausal status, parity, preoperative serum CA125 concentration, Federation International of gynecology and obstetrics (FIGO) stage, and whether patients accepted postoperative adjuvant therapy between the BOT and EOC group. After PSM, patients with BOTs had better overall survival than patients with EOC (P value = 0.0067); more importantly, the 5-year RMST of BOTs was longer than that of EOC (P value = 0.0002, 95%CI -1.137 to -0.263). Multivariate Cox regression analysis showed that diagnosed age and surgical type were independent risk factors for BOT patient OS (P value < 0.05). A nomogram was developed based on diagnosed age, preoperative serum CA125 and CA199 Levels, surgical type, FIGO stage, and tumor size. Moreover, the c-index (0.959, 95% confidence interval 0.8708–1.0472), calibration plot of 1-, 3-, and 5-year OS, and decision curve analysis indicated the accurate predictive ability of this model.
CONCLUSION Patients with BOTs had a better prognosis than patients with EOC. The nomogram we constructed might be helpful for clinicians in personalized treatment planning and patient counseling.
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Affiliation(s)
- Xiao-Qin Gong
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China
| | - Yan Zhang
- Department of Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China
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Shi M, Zhai GQ. Models for Predicting Early Death in Patients With Stage IV Esophageal Cancer: A Surveillance, Epidemiology, and End Results-Based Cohort Study. Cancer Control 2022; 29:10732748211072976. [PMID: 35037487 PMCID: PMC8777366 DOI: 10.1177/10732748211072976] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Background Despite enormous progress in the stage IV esophageal cancer (EC) treatment,
some patients experience early death after diagnosis. This study aimed to
identify the early death risk factors and construct models for predicting
early death in stage IV EC patients. Methods Stage IV EC patients diagnosed between 2010 and 2015 in the Surveillance,
Epidemiology, and End Results (SEER) database were selected. Early death was
defined as death within 3 months of diagnosis, with or without therapy.
Early death risk factors were identified using logistic regression analyses
and further used to construct predictive models. The concordance index
(C-index), calibration curves, and decision curve analyses (DCA) were used
to assess model performance. Results Out of 4411 patients enrolled, 1779 died within 3 months. Histologic grade,
therapy, the status of the bone, liver, brain and lung metastasis, marriage,
and insurance were independent factors for early death in stage IV EC
patients. Histologic grade and the status of the bone and liver metastases
were independent factors for early death in both chemoradiotherapy and
untreated groups. Based on these variables, predictive models were
constructed. The C-index was .613 (95% confidence interval (CI),
[.573–.653]) and .635 (95% CI, [.596–.674]) in the chemoradiotherapy and
untreated groups, respectively, while calibration curves and DCA showed
moderate performance. Conclusions More than 40% of stage IV EC patients suffered from an early death. The
models could help clinicians discriminate between low and high risks of
early death and strategize individually-tailed therapeutic interventions in
stage IV EC patients.
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Affiliation(s)
- Min Shi
- Department of Gastroenterology, Changzhou Maternal and Child Health Care Hospital, Changzhou, China
| | - Guo-Qing Zhai
- Department of Gastroenterology, Liyang People's Hospital, Liyang Branch of Jiangsu Province Hospital, Liyang, China
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Gong X, Zheng B, Xu G, Chen H, Chen C. Application of machine learning approaches to predict the 5-year survival status of patients with esophageal cancer. J Thorac Dis 2022; 13:6240-6251. [PMID: 34992804 PMCID: PMC8662490 DOI: 10.21037/jtd-21-1107] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/24/2021] [Indexed: 01/15/2023]
Abstract
Background Accurate prognostic estimation for esophageal cancer (EC) patients plays an important role in the process of clinical decision-making. The objective of this study was to develop an effective model to predict the 5-year survival status of EC patients using machine learning (ML) algorithms. Methods We retrieved the information of patients diagnosed with EC between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) Program, including 24 features. A total of 8 ML models were applied to the selected dataset to classify the EC patients in terms of 5-year survival status, including 3 newly developed gradient boosting models (GBM), XGBoost, CatBoost, and LightGBM, 2 commonly used tree-based models, gradient boosting decision trees (GBDT) and random forest (RF), and 3 other ML models, artificial neural networks (ANN), naive Bayes (NB), and support vector machines (SVM). A 5-fold cross-validation was used in model performance measurement. Results After excluding records with missing data, the final study population comprised 10,588 patients. Feature selection was conducted based on the χ2 test, however, the experiment results showed that the complete dataset provided better prediction of outcomes than the dataset with removal of non-significant features. Among the 8 models, XGBoost had the best performance [area under the receiver operating characteristic (ROC) curve (AUC): 0.852 for XGBoost, 0.849 for CatBoost, 0.850 for LightGBM, 0.846 for GBDT, 0.838 for RF, 0.844 for ANN, 0.833 for NB, and 0.789 for SVM]. The accuracy and logistic loss of XGBoost were 0.875 and 0.301, respectively, which were also the best performances. In the XGBoost model, the SHapley Additive exPlanations (SHAP) value was calculated and the result indicated that the four features: reason no cancer-directed surgery, Surg Prim Site, age, and stage group had the greatest impact on predicting the outcomes. Conclusions The XGBoost model and the complete dataset can be used to construct an accurate prognostic model for patients diagnosed with EC which may be applicable in clinical practice in the future.
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Affiliation(s)
- Xian Gong
- 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
| | - Bin Zheng
- 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
| | - Guobing Xu
- 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
| | - Hao 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
| | - Chun 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
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Yu Y, Wang W, Qin Z, Li H, Liu Q, Ma H, Sun H, Bauer TL, Pimiento JM, Gabriel E, Birdas T, Li Y, Xing W. A clinical nomogram for predicting tumor regression grade in esophageal squamous-cell carcinoma treated with immune neoadjuvant immunotherapy. ANNALS OF TRANSLATIONAL MEDICINE 2022; 10:102. [PMID: 35282099 PMCID: PMC8848421 DOI: 10.21037/atm-22-78] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 01/20/2022] [Indexed: 11/09/2022]
Abstract
Background There are various treatment options for esophageal squamous cell cancer. including surgery, peri-operative chemotherapy, and radiation. More recently, neoadjuvant immunotherapy has also been shown improve outcomes. In this study, we addressed the question, "Can we predict which patients with esophageal squamous cell cancer will benefit from neoadjuvant immunotherapy?". Methods All patients with thoracic esophageal squamous-cell carcinoma (T2N+M0-T3-4N0/+M0) (according to the eighth edition of the National Comprehensive Cancer Network guidelines) who underwent immune neoadjuvant immunochemotherapy with programmed cell death protein 1 (PD-1) combined with paclitaxel plus cisplatin or nedaplatin in the Affiliated Cancer Hospital of Zhengzhou University, China, between November 2019 and August 2021 were included in this study. All patients underwent surgical resection. We developed a response [tumor regression grade (TRG)] prediction model using the least absolute shrinkage and selection operator (LASSO) regression incorporating factors associated with response. The accuracy of the prediction model was then validated. Results We included 79 patients who underwent neoadjuvant immunotherapy combined with chemotherapy, aged 48-78 years (62.05±6.67), including 21 males and 58 females. There were five cases of immune-related pneumonia, of which three cases were diagnosed as immune-related pneumonia during the perioperative period, and one case of immune-related thyroid dysfunction changes. After LASSO regression, the factors that were independently associated with TRG were clinical T stage before neoadjuvant therapy, clinical N stage before neoadjuvant therapy, albumin level difference from before to after neoadjuvant therapy, white blood cell (WBC) count before neoadjuvant therapy, and T stage before surgery. We constructed a prediction model, plotted the nomogram, and verified its accuracy. Its Brier score was 0.13, its calibration slope was 0.98, and its C-index was 0.90 (95% CI: 0.82-0.97). Conclusions Our prediction model can predict the likelihood of TRG in patients with esophageal squamous cell cancer after immunotherapy combined with neoadjuvant chemotherapy. Using this prediction model, we plan to conduct a subsequent neoadjuvant radiotherapy in patients with of TRG 2-3 patients with neoadjuvant radiotherapy.
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Affiliation(s)
- Yongkui Yu
- Department of Thoracic Surgery, The Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
| | - Wei Wang
- Department of Thoracic Surgery, The Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
| | - Zimin Qin
- Department of Thoracic Surgery, The Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
| | - Haomiao Li
- Department of Thoracic Surgery, The Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
| | - Qi Liu
- Department of Thoracic Surgery, The Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
| | - Haibo Ma
- Department of Thoracic Surgery, The Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
| | - Haibo Sun
- Department of Thoracic Surgery, The Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
| | - Thomas L Bauer
- Department of Surgery, Jersey Shore University Medical Center, Department of General Surgery, Hackensack Meridian School of Medicine, Nutley, NJ, USA
| | - Jose M Pimiento
- Department of Gastrointestinal Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | - Thomas Birdas
- Department of Surgery, Thoracic Division, Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Yin Li
- Department of Thoracic Surgery, Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Wenqun Xing
- Department of Thoracic Surgery, The Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
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Ye P, Yang Y, Zhang L, Zheng G. Prognostic Signatures of Alternative Splicing Events in Esophageal Carcinoma Based on TCGA Splice-Seq Data. Front Oncol 2021; 11:658262. [PMID: 34676158 PMCID: PMC8524056 DOI: 10.3389/fonc.2021.658262] [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: 01/27/2021] [Accepted: 09/14/2021] [Indexed: 12/24/2022] Open
Abstract
An alternative splicing (AS) event is a highly complex process that plays an essential role in post-transcriptional gene expression. Several studies have suggested that abnormal AS events were the primary element in the pathological process of cancer. However, few works are dedicated to the study of AS events in esophageal carcinoma (EC). In the present study, clinical information and RNA-seq data of EC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The percent spliced in (PSI) values of AS events were acquired from the TCGA Splice-seq. A total of 183 EC patients were enrolled in this study, and 2,212 AS events were found significantly associated with the overall survival of these patients by univariate Cox regression analysis. The prognostic signatures based on AS events were built by multivariate Cox analysis. Receiver operating characteristic (ROC) curves displayed that the area under the curve (AUC) of the following prognostic signatures, including exon skip (ES), alternate terminator (AT), alternate acceptor site (AA), alternate promoter (AP), alternate donor site (AD), retained intron (RI), and total events, was greater than 0.8, suggesting that these seven signatures had valuable prognosis prediction capacity. Finally, the risk score of prognostic signatures was indicated as an independent risk factor of survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to explore the function of splicing factors (SFs) that were associated with AS events. Also, the interactive network between AS events and SFs identified several hub genes and AS events which need further study. This was a comprehensive study that explored prognosis-related AS events and established valuable prognosis signatures in EC patients. The network of interactions between AS events and SFs might offer novel insights into the fundamental mechanisms of tumorigenesis and progression of EC.
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Affiliation(s)
- Ping Ye
- National Health Commission Key Laboratory of Otorhinolaryngology, Department of Otorhinolaryngology, Qilu Hospital of Shandong University, Jinan, China
| | - Yan Yang
- National Health Commission Key Laboratory of Otorhinolaryngology, Department of Otorhinolaryngology, Qilu Hospital of Shandong University, Jinan, China
| | - Liqiang Zhang
- National Health Commission Key Laboratory of Otorhinolaryngology, Department of Otorhinolaryngology, Qilu Hospital of Shandong University, Jinan, China
| | - Guixi Zheng
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, China
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Predictive Model for Overall Survival and Cancer-Specific Survival in Patients with Esophageal Adenocarcinoma. JOURNAL OF ONCOLOGY 2021; 2021:4138575. [PMID: 34567114 PMCID: PMC8457966 DOI: 10.1155/2021/4138575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 09/01/2021] [Indexed: 12/16/2022]
Abstract
Objective Recent years, there has been a rapid increase in the incidence of esophageal adenocarcinoma (EAC), while the prognosis for patients diagnosed remains poor and has slightly improved. Methods We extracted 6,466 cases with detailed demographical characteristics including age at diagnosis, sex, ethnicity, marital status, and clinical features, involving tumor grade and stage at diagnosis and treatment modalities (radiation therapy, chemotherapy, and surgery) from the Surveillance, Epidemiology, and End Results (SEER) (1975–2017) dataset. They were further randomly divided into the training and validating cohorts. Univariate and multivariate Cox analyses were conducted to determine significant variables for construction of nomogram. The predictive power of the model was then assessed by Harrell concordance index (C-index) and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Results Multivariate analysis revealed that age, marital status, insurance, tumor grade, TNM stage, surgery, and chemotherapy all showed a significant association with overall survival (OS) and cancer-specific survival (CSS). These characteristics were employed to build a nomogram. Particularly, the discrimination of nomogram for OS and CSS prediction in the training set were excellent (C-index = 0.762, 95% CI: 0.754–0.770 and C-index = 0.774, 95% CI: 0.766–0.782). The AUC of the nomogram for predicting 2- and 5-year OS was 0.834 and 0.853 and CSS was 0.844 and 0.866. Similar results were observed in the internal validation set. Conclusion We have successfully established a novel nomogram for predicting OS and CSS in EAC patients with good accuracy, which can help clinicians predict the survival of individual patient survival and provide optimal treatment strategies.
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Yu R, Wang W, Li T, Li J, Zhao K, Wang W, Liang L, Wu H, Ai T, Huang W, Li L, Yu W, Wei C, Wang Y, Shen W, Xiao Z. RATIONALE 311: tislelizumab plus concurrent chemoradiotherapy for localized esophageal squamous cell carcinoma. Future Oncol 2021; 17:4081-4089. [PMID: 34269067 DOI: 10.2217/fon-2021-0632] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Definitive chemoradiotherapy is the standard of care for inoperable locoregionally advanced esophageal squamous cell carcinoma (ESCC). Immune checkpoint inhibitors such as anti-PD-1/PD-L1 antibodies have led to a paradigm shift in advanced, metastatic ESCC treatment; however, the effect of incorporating checkpoint inhibitors in the definitive management of ESCC is unclear. Tislelizumab is an anti-PD-1 antibody specifically engineered to minimize FcɣR binding on macrophages to abrogate antibody-dependent phagocytosis, a mechanism of T-cell clearance and potential resistance to anti-PD-1 therapy. The RATIONALE 311 study described here (BGB-A317-311; NCT03957590) is a registrational multicenter, double-blind, placebo-controlled, randomized, Phase III clinical trial designed to evaluate the efficacy and safety of tislelizumab combined with concurrent chemoradiotherapy in patients with inoperable localized ESCC.
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Affiliation(s)
- Rong Yu
- Department of Radiation Oncology, Peking University Cancer Hospital, Beijing, China
| | - Wenqing Wang
- Cancer Hospital & Institute, Chinese Academy of Medical Sciences, Beijing, China
| | - Tao Li
- Department of Radiation Oncology, Sichuan Cancer Hospital, Chengdu, China
| | - Jiancheng Li
- Department of Radiation Oncology, Fujian Cancer Hospital, Fuzhou, China
| | - Kuaile Zhao
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Weihu Wang
- Department of Radiation Oncology, Peking University Cancer Hospital, Beijing, China
| | - Long Liang
- Department of Radiation Oncology, Sichuan Cancer Hospital, Chengdu, China
| | - Haishan Wu
- Department of Radiation Oncology, Fujian Cancer Hospital, Fuzhou, China
| | - Tashan Ai
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Wei Huang
- BeiGene (Beijing) Co., Ltd., Beijing, China
| | - Liyun Li
- BeiGene (Beijing) Co., Ltd., Beijing, China
| | - Wentao Yu
- BeiGene (Beijing) Co., Ltd., Beijing, China
| | - Chenlu Wei
- BeiGene (Beijing) Co., Ltd., Beijing, China
| | - Yidi Wang
- BeiGene (Beijing) Co., Ltd., Beijing, China
| | - Wei Shen
- BeiGene (Beijing) Co., Ltd., Beijing, China
| | - Zefen Xiao
- Cancer Hospital & Institute, Chinese Academy of Medical Sciences, Beijing, China
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Yin R, Wang G, Yang X, Zhang L, Wang S, Li T, Liu S. Identification of prognostic factors and construction of a nomogram for patients with relapse/refractory adult-onset Still's disease. Clin Rheumatol 2021; 40:3951-3960. [PMID: 34002352 DOI: 10.1007/s10067-021-05722-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 03/18/2021] [Accepted: 03/29/2021] [Indexed: 11/25/2022]
Abstract
OBJECTIVES This study aimed to identify the risk factors for relapse/refractory adult-onset Still's disease (AOSD) and to construct and validate a prognostic nomogram for predicting the individual risk of relapse/refractory disease. METHOD A total of 174 patients were included in our study. Univariate and multivariate logistic regression analyses were used to identify relapse/refractory-associated factors, which were used to construct nomograms. Receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA) were used to assess the predictive ability of the nomograms. RESULTS Univariate and multivariate logistic analyses showed that age, fever, disease duration, platelet count, serum ferritin level, and erythrocyte sedimentation rate were independent unfavourable factors for relapse/refractory AOSD (p < 0.05). We constructed a 6-factor nomogram based on univariate and multivariate logistic analyses. ROC analysis indicated that the area under the curve of the 6-factor nomogram in the training set and test set was 0.765 and 0.714, respectively. In addition, the calibration curves showed excellent prediction accuracy, and DCA showed superior net benefit in the 6-factor nomograms. Moreover, we evaluated the predictive effectiveness of our nomogram in females and young adults. The results showed that our 6-factor nomogram has the same predictive ability in both subgroups. CONCLUSIONS Novel nomograms based on clinical characteristics were developed and may be applied to help predict the individual risk of poor prognosis of patients. Key Points • Logistic regression was used to identify risk factors for relapse/refractory adult-onset Still's disease. • We then constructed a nomogram for predicting disease risk. • ROC analysis, calibration curves, and DCA all showed that the nomogram exerted good prediction ability in both the training set and test set. • The nomogram has the same predictive ability in both female and young adult subgroups.
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Affiliation(s)
- Ruxue Yin
- Department of Rheumatology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, China
| | - Gangjian Wang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, China
| | - Xiaopei Yang
- Department of Rheumatology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, China
| | - Lei Zhang
- Department of Rheumatology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, China
| | - Shuolin Wang
- Department of Rheumatology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, China
| | - Tianfang Li
- Department of Rheumatology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, China
| | - Shengyun Liu
- Department of Rheumatology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, China.
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Abstract
Background: This study aimed to develop nomograms predicting the overall survival (OS) of patients younger than 50 years old with esophageal cancer.Methods: We selected patients included 2004-2015 in the Surveillance, Epidemiology, and End Results (SEER) database. Nomograms were constructed using significant variables from multivariable Cox analyses. The discrimination and calibration power of the models were evaluated using concordance indexes (C-indexes) and calibration curves. Decision curve analysis was used to assess the clinical net benefits of the nomograms.Results: Of 1,997 selected patients, 53.2% had advanced-stage tumor. Race, grade, T stage, N stage, and treatment were independent factors affecting OS in early-stage patients. The C-indexes of the corresponding nomogram were 0.710 (95% CI = 0.684-0.736) and 0.681 (95% CI = 0.640-0.722) in training and validation sets, respectively. Grade, marital status, and treatment were independent factors affecting OS in advanced-stage patients. The C-indexes of the corresponding nomogram were 0.677 (95% CI = 0.653-0.701) and 0.675 (95% CI = 0.638-0.712) in training and validation sets, respectively. Calibration curves demonstrated high consistency between predicted and actual survival.Conclusion: We constructed and verified nomograms that could accurately predict the survival rate of esophageal cancer in patients younger than 50 years old. This may help clinicians better understand prognostic factors.
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Affiliation(s)
- Min Shi
- Department of Gastroenterology, Liyang People's Hospital, Liyang, China
| | - Jian-Wei Tang
- Department of Gastroenterology, Liyang People's Hospital, Liyang, China
| | - Zhi-Rong Cao
- Department of Gastroenterology, Liyang People's Hospital, Liyang, China
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Sex-Associated Gene Expression Alterations Correlate With Esophageal Cancer Survival. Clin Transl Gastroenterol 2020; 12:e00281. [PMID: 33464731 PMCID: PMC7752676 DOI: 10.14309/ctg.0000000000000281] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 11/05/2020] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVES: Esophageal cancer (EC) is a significant cause of cancer death with 5-year survival of 10%–15% and males more frequently affected. Genetic evaluation for loci highlighting risk has been performed, but survival data are limited. The Cancer Genome Atlas (TCGA) data sets allow for potential prognostic marker assessment in large patient cohorts. The study aimed to use the TCGA EC data set to assess whether survival varies by sex and explore genetic alterations that may explain variation observed. METHODS: TCGA clinical/RNA-seq data sets (n = 185, 158 males/27 females) were downloaded from the cancer genome browser. Data analysis/figure preparation was performed in R and GraphPad Prism 7. Survival analysis was performed using the survival package. Text mining of PubMed was performed using the tm, RISmed, and wordcloud packages. Pathway analysis was performed using the Reactome database. RESULTS: In EC, male sex/high tumor grade reduced overall survival (hazard ratio = 2.27 [0.99–5.24] for M vs F and 2.49 [0.89–6.92] for low vs high grade, respectively) and recurrence-free survival (hazard ratio = 4.09 [0.98–17.03] for M vs F and 3.36 [0.81–14.01] for low vs high grade, respectively). To investigate the genetic basis for sex-based survival differences in EC, corresponding gene expression data were analyzed. Sixty-nine genes were dysregulated at the P < 0.01 level by the Wilcox test, 33% were X-chromosome genes, and 7% were Y-chromosome genes. DISCUSSION: Female sex potentially confers an EC survival advantage. Importantly, we demonstrate a genetic/epigenetic basis for these survival differences that are independent of lifestyle-associated risk factors overrepresented in males. Further research may lead to novel concepts in treating/measuring EC aggressiveness by sex.
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Cameniţă D, Demetrian AD, Pleşea RM, Tănasie-Vasile MI, Strâmbu VDE, Grigorean VT, Ioniţă E, Pleşea IE, Marincaş AM. Clinical-morphological profiles of esophageal carcinoma's main types. ROMANIAN JOURNAL OF MORPHOLOGY AND EMBRYOLOGY 2020; 61:407-422. [PMID: 33544792 PMCID: PMC7864308 DOI: 10.47162/rjme.61.2.10] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Aim: The purpose of the study was to define and then to compare particularly the morphological profiles of the main morphological types of esophageal carcinoma (EC). Patients, Materials and Methods: The studied group included 46 operated EC patients. Few parameters were clinical (gender and age). The rest of them described both gross and histological features of the entire group and of the two main histological types of carcinoma (lesion’ site, lateral extension, lesion dimensions, gross aspect, and histological type, and tumor grade, and stage). Stratification scales of cases were defined according to each parameter in order to compare the data and a statistical apparatus [Student’s t-test and χ2 (chi-squared) test] was used. Results: The studied tumors were encountered mostly in mature adult and elderly men, usually in the lower segments of the esophagus. Many of them had between five and ten cm in the long diameter and produced stenosis. Most of them had infiltrating appearance combined often with protruding or/and ulcerated aspects. Usually, the tumors were poorly differentiated and in stage III. The two main histological types of EC showed different morphological profiles. Data from the literature revealed sometimes wide ranges of variation for the studied morphological parameters. Our results were within these ranges of variation. Conclusions: ECs proved to be aggressive and late diagnosed tumors in general, with distinct morphological and behavioral profiles for the two main histological types. Comparisons with literature data confirmed many of our observations regarding the clinical and morphological aspects of both ECs as a whole and its histological types.
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Affiliation(s)
- Dan Cameniţă
- Department II - Morphological Sciences, Carol Davila University of Medicine and Pharmacy, Department of Pathology, Fundeni Clinical Institute, Bucharest, Romania;
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