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Kumar A, Kaw P. Clinicopathological and radiological characteristics and prediction of survival in colon cancer. World J Gastrointest Oncol 2025; 17:101516. [PMID: 39958557 PMCID: PMC11756002 DOI: 10.4251/wjgo.v17.i2.101516] [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: 09/17/2024] [Revised: 10/14/2024] [Accepted: 11/04/2024] [Indexed: 01/18/2025] Open
Abstract
There are various histological characteristics which have been proposed to predict the survival rate in colon cancer. However, there is no definitive model to accurately predict the survival. Therefore, it is important to find out one model for the prediction of survival in colon cancer which may also include the preoperative, and operative factors in addition to histopathology.
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Affiliation(s)
- Ashok Kumar
- Department of Surgical Gastroenterology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow 226014, Uttar Pradesh, India
| | - Payal Kaw
- Department of Surgical Gastroenterology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow 226014, Uttar Pradesh, India
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Hu ZX, Li Y, Yang X, Li YX, He YY, Niu XH, Nie TT, Guo XF, Yuan ZL. Constructing a nomogram to predict overall survival of colon cancer based on computed tomography characteristics and clinicopathological factors. World J Gastrointest Oncol 2024; 16:4104-4114. [DOI: 10.4251/wjgo.v16.i10.4104] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 08/18/2024] [Accepted: 09/06/2024] [Indexed: 09/26/2024] Open
Abstract
BACKGROUND The colon cancer prognosis is influenced by multiple factors, including clinical, pathological, and non-biological factors. However, only a few studies have focused on computed tomography (CT) imaging features. Therefore, this study aims to predict the prognosis of patients with colon cancer by combining CT imaging features with clinical and pathological characteristics, and establishes a nomogram to provide critical guidance for the individualized treatment.
AIM To establish and validate a nomogram to predict the overall survival (OS) of patients with colon cancer.
METHODS A retrospective analysis was conducted on the survival data of 249 patients with colon cancer confirmed by surgical pathology between January 2017 and December 2021. The patients were randomly divided into training and testing groups at a 1:1 ratio. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors associated with OS, and a nomogram model was constructed for the training group. Survival curves were calculated using the Kaplan–Meier method. The concordance index (C-index) and calibration curve were used to evaluate the nomogram model in the training and testing groups.
RESULTS Multivariate logistic regression analysis revealed that lymph node metastasis on CT, perineural invasion, and tumor classification were independent prognostic factors. A nomogram incorporating these variables was constructed, and the C-index of the training and testing groups was 0.804 and 0.692, respectively. The calibration curves demonstrated good consistency between the actual values and predicted probabilities of OS.
CONCLUSION A nomogram combining CT imaging characteristics and clinicopathological factors exhibited good discrimination and reliability. It can aid clinicians in risk stratification and postoperative monitoring and provide important guidance for the individualized treatment of patients with colon cancer.
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Affiliation(s)
- Zhe-Xing Hu
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Yin Li
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Xuan Yang
- Department of Radiology, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, Hubei Province, China
| | - Yu-Xia Li
- College of Informatics, Huazhong Agriculture University, Wuhan 430070, Hubei Province, China
| | - Yao-Yao He
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Xiao-Hui Niu
- College of Informatics, Huazhong Agriculture University, Wuhan 430070, Hubei Province, China
| | - Ting-Ting Nie
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Xiao-Fang Guo
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Zi-Long Yuan
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
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Atienza ÁV, Iriarte OA, Sarrias OR, Lizundia TZ, Beristain OS, Casajús AE, Gigli LÁ, Sastre FR, García IM, Rodríguez JR. Neoadjuvant Statistical Algorithm to Predict Individual Risk of Relapse in Patients with Resected Liver Metastases from Colorectal Cancer. Biomedicines 2024; 12:1859. [PMID: 39200323 PMCID: PMC11351994 DOI: 10.3390/biomedicines12081859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2024] [Revised: 08/10/2024] [Accepted: 08/12/2024] [Indexed: 09/02/2024] Open
Abstract
(1) Background: Liver metastases (LM) are the leading cause of death in colorectal cancer (CRC) patients. Despite advancements, relapse rates remain high and current prognostic nomograms lack accuracy. Our objective is to develop an interpretable neoadjuvant algorithm based on mathematical models to accurately predict individual risk, ensuring mathematical transparency and auditability. (2) Methods: We retrospectively evaluated 86 CRC patients with LM treated with neoadjuvant systemic therapy followed by complete surgical resection. A comprehensive analysis of 155 individual patient variables was performed. Logistic regression (LR) was utilized to develop the predictive model for relapse risk through significance testing and ANOVA analysis. Due to data limitations, gradient boosting machine (GBM) and synthetic data were also used. (3) Results: The model was based on data from 74 patients (12 were excluded). After a median follow-up of 58 months, 5-year relapse-free survival (RFS) rate was 33% and 5-year overall survival (OS) rate was 60.7%. Fifteen key variables were used to train the GBM model, which showed promising accuracy (0.82), sensitivity (0.59), and specificity (0.96) in predicting relapse. Similar results were obtained when external validation was performed as well. (4) Conclusions: This model offers an alternative for predicting individual relapse risk, aiding in personalized adjuvant therapy and follow-up strategies.
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Affiliation(s)
- Ángel Vizcay Atienza
- Department of Medical Oncology, Clínica Universidad de Navarra, 31008 Pamplona, Spain; (Á.V.A.); (T.Z.L.)
| | | | - Oskitz Ruiz Sarrias
- Department of Mathematics and Statistic, NNBi, 31110 Noain, Spain; (O.A.I.); (O.R.S.); (O.S.B.)
| | - Teresa Zumárraga Lizundia
- Department of Medical Oncology, Clínica Universidad de Navarra, 31008 Pamplona, Spain; (Á.V.A.); (T.Z.L.)
| | - Onintza Sayar Beristain
- Department of Mathematics and Statistic, NNBi, 31110 Noain, Spain; (O.A.I.); (O.R.S.); (O.S.B.)
| | - Ana Ezponda Casajús
- Department of Radiology, Clínica Universidad de Navarra, 31008 Pamplona, Spain;
| | - Laura Álvarez Gigli
- Department of Pathology, Clínica Universidad de Navarra, 31008 Pamplona, Spain;
| | | | - Ignacio Matos García
- Department of Medical Oncology, Clínica Universidad de Navarra, 28027 Madrid, Spain;
| | - Javier Rodríguez Rodríguez
- Department of Medical Oncology, Clínica Universidad de Navarra, 31008 Pamplona, Spain; (Á.V.A.); (T.Z.L.)
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Shi Y, Wu X, Qu W, Tian J, Pang X, Fan H, Fei S, Miao B. Construction and validation of a prognostic nomogram for predicting cancer-specific survival in patients with intermediate and advanced colon cancer after receiving surgery and chemotherapy. J Cancer Res Clin Oncol 2023; 149:12821-12834. [PMID: 37458804 PMCID: PMC10587224 DOI: 10.1007/s00432-023-05154-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 07/09/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND Existing predictive models often focus solely on overall survival (OS), neglecting the bias that other causes of death might introduce into survival rate predictions. To date, there is no strict predictive model established for cancer-specific survival (CSS) in patients with intermediate and advanced colon cancer after receiving surgery and chemotherapy. METHODS We extracted the data from the Surveillance, Epidemiology, and End Results (SEER) database on patients with stage-III and -IV colon cancer treated with surgery and chemotherapy between 2010 and 2015. The cancer-specific survival (CSS) was assessed using a competitive risk model, and the associated risk factors were identified via univariate and multivariate analyses. A nomogram predicting 1-, 3-, and 5-year CSS was constructed. The c-index, area under the curve (AUC), and calibration curve were adopted to assess the predictive performance of the model. Additionally, the model was externally validated. RESULTS A total of 18 risk factors were identified by univariate and multivariate analyses for constructing the nomogram. The AUC values of the nomogram for the 1-, 3-, and 5-year CSS prediction were 0.831, 0.842, and 0.848 in the training set; 0.842, 0.853, and 0.849 in the internal validation set; and 0.815, 0.823, and 0.839 in the external validation set. The C-index were 0.826 (se: 0.001), 0.836 (se: 0.002) and 0.763 (se: 0.013), respectively. Moreover, the calibration curve showed great calibration. CONCLUSION The model we have constructed is of great accuracy and reliability, and can help physicians develop treatment and follow-up strategies that are beneficial to the survival of the patients.
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Affiliation(s)
- Yiheng Shi
- First Clinical Medical College, Xuzhou Medical University, Xuzhou, 221002, Jiangsu, China
- Department of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, 99 West Huaihai Road, Xuzhou, 221002, Jiangsu, China
| | - Xiaoting Wu
- Department of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, 99 West Huaihai Road, Xuzhou, 221002, Jiangsu, China
| | - Wanxi Qu
- First Clinical Medical College, Xuzhou Medical University, Xuzhou, 221002, Jiangsu, China
| | - Jiahao Tian
- First Clinical Medical College, Xuzhou Medical University, Xuzhou, 221002, Jiangsu, China
| | - Xunlei Pang
- Department of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, 99 West Huaihai Road, Xuzhou, 221002, Jiangsu, China
| | - Haohan Fan
- First Clinical Medical College, Xuzhou Medical University, Xuzhou, 221002, Jiangsu, China
| | - Sujuan Fei
- Department of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, 99 West Huaihai Road, Xuzhou, 221002, Jiangsu, China.
- Key Laboratory of Gastrointestinal Endoscopy, Xuzhou Medical University, Xuzhou, 221002, Jiangsu, China.
| | - Bei Miao
- Institute of Gastroenterology, Xuzhou Medical University, 84 West Huaihai Road, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Gastrointestinal Endoscopy, Xuzhou Medical University, Xuzhou, 221002, Jiangsu, China.
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Zhang Y, Yang Z, Tang Y, Guo C, Lin D, Cheng L, Hu X, Zhang K, Li G. Hallmark guided identification and characterization of a novel immune-relevant signature for prognostication of recurrence in stage I-III lung adenocarcinoma. Genes Dis 2023; 10:1657-1674. [PMID: 37397559 PMCID: PMC10311029 DOI: 10.1016/j.gendis.2022.07.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 06/07/2022] [Accepted: 07/16/2022] [Indexed: 11/23/2022] Open
Abstract
The high risk of postoperative mortality in lung adenocarcinoma (LUAD) patients is principally driven by cancer recurrence and low response rates to adjuvant treatment. Here, A combined cohort containing 1,026 stage I-III patients was divided into the learning (n = 678) and validation datasets (n = 348). The former was used to establish a 16-mRNA risk signature for recurrence prediction with multiple statistical algorithms, which was verified in the validation set. Univariate and multivariate analyses confirmed it as an independent indicator for both recurrence-free survival (RFS) and overall survival (OS). Distinct molecular characteristics between the two groups including genomic alterations, and hallmark pathways were comprehensively analyzed. Remarkably, the classifier was tightly linked to immune infiltrations, highlighting the critical role of immune surveillance in prolonging survival for LUAD. Moreover, the classifier was a valuable predictor for therapeutic responses in patients, and the low-risk group was more likely to yield clinical benefits from immunotherapy. A transcription factor regulatory protein-protein interaction network (TF-PPI-network) was constructed via weighted gene co-expression network analysis (WGCNA) concerning the hub genes of the signature. The constructed multidimensional nomogram dramatically increased the predictive accuracy. Therefore, our signature provides a forceful basis for individualized LUAD management with promising potential implications.
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Affiliation(s)
- Yongqiang Zhang
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong 510620, China
| | - Zhao Yang
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yuqin Tang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Chengbin Guo
- Center for Biomedicine and Innovations, Faculty of Medicine, Macau University of Science and Technology, Macau 999078, China
| | - Danni Lin
- Center for Biomedicine and Innovations, Faculty of Medicine, Macau University of Science and Technology, Macau 999078, China
| | - Linling Cheng
- Center for Biomedicine and Innovations, Faculty of Medicine, Macau University of Science and Technology, Macau 999078, China
| | - Xun Hu
- Clinical Research Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, China
- Biorepository, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Kang Zhang
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Center for Biomedicine and Innovations, Faculty of Medicine, Macau University of Science and Technology, Macau 999078, China
| | - Gen Li
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong 510620, China
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He JH, Cao C, Ding Y, Yi Y, Lv YQ, Wang C, Chang Y. A nomogram model for predicting distant metastasis of newly diagnosed colorectal cancer based on clinical features. Front Oncol 2023; 13:1186298. [PMID: 37397373 PMCID: PMC10311479 DOI: 10.3389/fonc.2023.1186298] [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: 03/16/2023] [Accepted: 05/18/2023] [Indexed: 07/04/2023] Open
Abstract
Objective Colorectal cancer is one of the most common primary malignancies and the third most common cause of cancer death in both men and women in the United States. Among people diagnosed with initial colorectal cancer, 22% had metastatic colorectal cancer, while the 5-year survival rate was less than 20%. The purpose of this study is to develop a nomogram for predicting distant metastasis in newly diagnosed colorectal cancer patients and to identify high-risk groups. Methods We retrospectively reviewed the data of patients who were diagnosed with colorectal cancer at Zhong nan Hospital of Wuhan University and People's Hospital of Gansu Province between January 2016 and December 2021. Risk predictors for distant metastasis from colorectal patients were determined by the univariate and multivariate logistic regression analyses. Nomograms were developed to predict the probabilities of distant metastatic sites of colorectal cancer patients and evaluated by calibration curves, receiver operating characteristic curves, and decision curve analysis (DCA). Results A total of 327 cases were included in this study: 224 colorectal cancer patients from Zhong nan Hospital of Wuhan University were incorporated into the training set, and 103 colorectal cancer patients from Gansu Provincial People's Hospital were incorporated into the testing set. By univariate logistic regression analysis, platelet (PLT) level (p = 0.009), carcinoembryonic antigen (CEA) level (p = 0.032), histological grade (p < 0.001), colorectal cancer tumor markers (p < 0.001), N stage (p < 0.001), and tumor site (p = 0.005) were associated with distant metastasis in colorectal cancer patients. Multivariate logistic regression analysis showed that N stage (p < 0.001), histological grade (p = 0.026), and colorectal cancer markers (p < 0.001) were independent predictors of distant metastasis in patients initially diagnosed with colorectal cancer. The above six risk factors were used to predict distant metastasis of newly diagnosed colorectal cancer. The C-indexes for the prediction of the nomogram were 0.902 (95% confidence interval (CI), 0.857-0.948). Conclusion The nomogram showed excellent accuracy in predicting distant metastatic sites, and clinical utility may facilitate clinical decision-making.
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Affiliation(s)
- Jiang-Hua He
- Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Cong Cao
- Department of Colorectal Surgery, Gansu Provincial People’s Hospital, Gansu, China
| | - Yang Ding
- Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yun Yi
- Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yu-Qing Lv
- Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Chun Wang
- Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ying Chang
- Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China
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Wang P, Song Q, Lu M, Xia Q, Wang Z, Zhao Q, Ma X. Establishment and validation of a postoperative predictive model for patients with colorectal mucinous adenocarcinoma. World J Surg Oncol 2022; 20:330. [PMID: 36192778 PMCID: PMC9528152 DOI: 10.1186/s12957-022-02791-z] [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: 07/15/2022] [Accepted: 09/18/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The aim of this study was to develop comprehensive and effective nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) rates in patients with colorectal mucinous adenocarcinoma (CRMA). METHODS A total of 4711 CRMA patients who underwent radical surgery between 2010 and 2018 from the Surveillance, Epidemiology, and End Results (SEER) database were collected and randomized into development (n=3299) and validation (n=1412) cohorts at a ratio of 7:3 for model development and validation. OS and CSS nomograms were developed using the prognostic factors from the development cohort after multivariable Cox regression analysis. The performance of the nomograms was evaluated using Harrell's concordance index (C-index), calibration diagrams, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). RESULTS The study included 4711 patients. Multivariate Cox regression analysis demonstrated that age, tumor size, grade, pT stage, pN stage, M stage, carcinoembryonic antigen, perineural invasion, tumor deposits, regional nodes examined, and chemotherapy were correlated with OS and CSS. Marital status was independently related to OS. In the development and validation cohorts, the C-index of OS was 0.766 and 0.744, respectively, and the C-index of CSS was 0.826 and 0.809, respectively. Calibration curves and ROC curves showed predictive accuracy. DCA showed that the nomograms had excellent potency over the 8th edition of the TNM staging system with higher clinical net benefits. Significant differences in OS and CSS were observed among low-, medium-, and high-risk groups. CONCLUSIONS Nomograms were developed for the first time to predict personalized 1-, 3-, and 5-year OS and CSS in CRMA postoperative patients. External and internal validation confirmed the excellent discrimination and calibration ability of the nomograms. The nomograms can help clinicians design personalized treatment strategies and assist with clinical decisions.
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Affiliation(s)
- Pengchao Wang
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, 121 Jiang jia Yuan Road, Nanjing, 210011, Jiangsu, China
| | - Qingyu Song
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, 121 Jiang jia Yuan Road, Nanjing, 210011, Jiangsu, China
| | - Ming Lu
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, 121 Jiang jia Yuan Road, Nanjing, 210011, Jiangsu, China
| | - Qingcheng Xia
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, 121 Jiang jia Yuan Road, Nanjing, 210011, Jiangsu, China
| | - Zijun Wang
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, 121 Jiang jia Yuan Road, Nanjing, 210011, Jiangsu, China
| | - Qinghong Zhao
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, 121 Jiang jia Yuan Road, Nanjing, 210011, Jiangsu, China.
| | - Xiang Ma
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, 121 Jiang jia Yuan Road, Nanjing, 210011, Jiangsu, China.
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A Commentary on “Construction of a nomogram to predict overall survival for patients with M1 stage of colorectal cancer: A retrospective cohort study” (Int J Surg 2019;72:96–101). Int J Surg 2022; 106:106914. [DOI: 10.1016/j.ijsu.2022.106914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 09/09/2022] [Indexed: 11/21/2022]
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Learn to Estimate Genetic Mutation and Microsatellite Instability with Histopathology H&E Slides in Colon Carcinoma. Cancers (Basel) 2022; 14:cancers14174144. [PMID: 36077681 PMCID: PMC9454509 DOI: 10.3390/cancers14174144] [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: 07/30/2022] [Revised: 08/21/2022] [Accepted: 08/22/2022] [Indexed: 11/16/2022] Open
Abstract
Colorectal cancer is one of the most common malignancies and the third leading cause of cancer-related mortality worldwide. Identifying KRAS, NRAS, and BRAF mutations and estimating MSI status is closely related to the individualized therapeutic judgment and oncologic prognosis of CRC patients. In this study, we introduce a cascaded network framework with an average voting ensemble strategy to sequentially identify the tumor regions and predict gene mutations & MSI status from whole-slide H&E images. Experiments on a colorectal cancer dataset indicate that the proposed method can achieve higher fidelity in both gene mutation prediction and MSI status estimation. In the testing set, our method achieves 0.792, 0.886, 0.897, and 0.764 AUCs for KRAS, NRAS, BRAF, and MSI, respectively. The results suggest that the deep convolutional networks have the potential to provide diagnostic insight and clinical guidance directly from pathological H&E slides.
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Wang H, Shan X, Zhang M, Qian K, Shen Z, Zhou W. Homogeneous and heterogeneous risk and prognostic factors for lung metastasis in colorectal cancer patients. BMC Gastroenterol 2022; 22:193. [PMID: 35436849 PMCID: PMC9016976 DOI: 10.1186/s12876-022-02270-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 04/07/2022] [Indexed: 12/24/2022] Open
Abstract
Background The lung is one of the most frequent distant metastasis sites in colorectal cancer (CRC) patients; however, lung metastasis risk and prognostic factors have not been comprehensively elucidated. This study aimed to identify the homogeneous and heterogeneous lung metastasis risk and prognostic factors in CRC patients using the Surveillance, Epidemiology, and End Results (SEER) database. Methods CRC patients registered in the SEER database between 2010 and 2016 were included to analyse risk factors for developing lung metastasis by using univariable and multivariable logistic regression. Patients diagnosed between 2010 and 2015 were selected to investigate prognostic factors for lung metastasis by conducting Cox regression. Kaplan–Meier analysis was used to estimate overall survival outcomes. Results A total of 10,598 (5.2%) patients with synchronous lung metastasis were diagnosed among 203,138 patients with CRC. The median survival time of patients with lung metastasis was 10.0 months (95% CI 9.6–10.5 months). Older age, unmarried status, uninsured status, poor histological differentiation, more lymphatic metastasis, CEA positivity, liver metastasis, bone metastasis and brain metastasis were lung metastasis risk and prognostic factors. Black patients and those with left colon, rectum, and stage T4 disease were more likely to develop lung metastasis, while patients with right colon cancer and no surgical treatment of the primary tumour had poor survival outcomes. Conclusion The incidence of lung metastasis in CRC patients was 5.2%. CRC patients with lung metastasis exhibited homogeneous and heterogeneous risk and prognostic factors. These results are helpful for clinical evaluation and individual treatment decision making. Supplementary Information The online version contains supplementary material available at 10.1186/s12876-022-02270-5.
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Affiliation(s)
- Hongmei Wang
- Department of Pharmacology, College of Pharmacy, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China.,Chongqing Key Laboratory of Drug Metabolism, Chongqing Medical University, Chongqing, 400016, China.,Key Laboratory for Biochemistry and Molecular Pharmacology of Chongqing, Chongqing Medical University, Chongqing, 400016, China.,Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xuefeng Shan
- Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Min Zhang
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, 400016, China
| | - Kun Qian
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Zhengze Shen
- Department of Pharmacy, Yongchuan Hospital of Chongqing Medical University, 439 Xuanhua Road, Yongchuan District, Chongqing, 402160, China.
| | - Weiying Zhou
- Department of Pharmacology, College of Pharmacy, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. .,Chongqing Key Laboratory of Drug Metabolism, Chongqing Medical University, Chongqing, 400016, China. .,Key Laboratory for Biochemistry and Molecular Pharmacology of Chongqing, Chongqing Medical University, Chongqing, 400016, China.
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Mazaki J, Katsumata K, Tago T, Kasahara K, Enomoto M, Ishizaki T, Nagakawa Y, Tsuchida A. Novel and Simple Nomograms Using Inflammation and Nutritional Biomarkers for Stage II–III Colon Cancer, Taking “Time after Curative Surgery” into Consideration. Nutr Cancer 2022; 74:2875-2886. [DOI: 10.1080/01635581.2022.2042570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Junichi Mazaki
- Department of Gastrointestinal and Pediatric Surgery, Tokyo Medical University, Tokyo, Japan
| | - Kenji Katsumata
- Department of Gastrointestinal and Pediatric Surgery, Tokyo Medical University, Tokyo, Japan
| | - Tomoya Tago
- Department of Gastrointestinal and Pediatric Surgery, Tokyo Medical University, Tokyo, Japan
| | - Kenta Kasahara
- Department of Gastrointestinal and Pediatric Surgery, Tokyo Medical University, Tokyo, Japan
| | - Masanobu Enomoto
- Department of Gastrointestinal and Pediatric Surgery, Tokyo Medical University, Tokyo, Japan
| | - Tetsuo Ishizaki
- Department of Gastrointestinal and Pediatric Surgery, Tokyo Medical University, Tokyo, Japan
| | - Yuichi Nagakawa
- Department of Gastrointestinal and Pediatric Surgery, Tokyo Medical University, Tokyo, Japan
| | - Akihiko Tsuchida
- Department of Gastrointestinal and Pediatric Surgery, Tokyo Medical University, Tokyo, Japan
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Shi L, Su Y, Zheng Z, Qi J, Wang W, Wang C. miR-146b-5p promotes colorectal cancer progression by targeting TRAF6. Exp Ther Med 2022; 23:231. [PMID: 35222708 PMCID: PMC8815033 DOI: 10.3892/etm.2022.11155] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 12/06/2021] [Indexed: 12/09/2022] Open
Abstract
Increasing evidence highlights the multiple roles of microRNAs (miRs) in the tumorigenesis of colorectal cancer (CRC); however, the molecular mechanism, particularly the target of miR-146b-5p in CRC has not been fully elucidated. The present study aimed to elucidate the influence of miR-146b-5p via regulating tumor necrosis factor receptor-associated factor 6 (TRAF6) in CRC. The expression levels of miR-146b-5p and TRAF6 in CRC tissue and cells were determined by reverse transcription quantitative PCR and western blotting. Binding between miR-146b-5p and TRAF6 was examined using a dual luciferase reporter gene assay. The impact of miR-146b-5p and TRAF6 on proliferation and migration of CRC cells was determined using Cell Counting Kit-8 and Transwell assays, respectively. An animal model of CRC was established to determine the carcinogenic effect of the miR-146b-5p-TRAF6 axis. The results demonstrated that miR-146b-5p was highly expressed in CRC tissue samples compared with in normal adjacent tissue samples and in CRC cells compared with in the normal NCM460 cell line, whereas TRAF6 was expressed at low levels. Overexpression of miR-146b-5p decreased TRAF6 expression in CRC HT29 and SW620 cells. miR-146b-5p targeted and inhibited TRAF6 expression in CRC cells. Furthermore, transfection with a miR-146b-5p mimic promoted the proliferation, migration and invasion of CRC cells and tumor growth; however, these effects were abolished by TRAF6 overexpression. Transfection with a miR-146b-5p inhibitor suppressed the proliferation of CRC cells. Taken together, the results from the present study demonstrated that miR-146b-5p could enhance the initiation and tumorigenesis of CRC by targeting TRAF6. These results will help elucidate the mechanisms underlying CRC development and will facilitate the development of targeted therapy for CRC.
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Affiliation(s)
- Liangpan Shi
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510630, P.R. China
- Department of Gastrointestinal Surgery, The First Hospital of Quanzhou Affiliated of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China
| | - Yibin Su
- Department of Gastrointestinal Surgery, The First Hospital of Quanzhou Affiliated of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China
| | - Zhihua Zheng
- Department of Gastrointestinal Surgery, The First Hospital of Quanzhou Affiliated of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China
| | - Jinyu Qi
- Department of Gastrointestinal Surgery, The First Hospital of Quanzhou Affiliated of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China
| | - Weidong Wang
- Department of Gastrointestinal Surgery, The First Hospital of Quanzhou Affiliated of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China
| | - Cunchuan Wang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510630, P.R. China
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Zhu X, Jia W, Yan Y, Huang Y, Wang B. NOP14 regulates the growth, migration, and invasion of colorectal cancer cells by modulating the NRIP1/GSK-3β/β-catenin signaling pathway. Eur J Histochem 2021; 65. [PMID: 34218653 PMCID: PMC8273630 DOI: 10.4081/ejh.2021.3246] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/25/2021] [Indexed: 12/24/2022] Open
Abstract
Colorectal cancer (CRC) is the third most common cancer diagnosed worldwide. Recently, nucleolar complex protein 14 (NOP14) has been discovered to play a critical role in cancer development and progression, but the mechanisms of action of NOP14 in colorectal cancer remain to be elucidated. In this study, we used collected colorectal cancer tissues and cultured colorectal cancer cell lines (SW480, HT29, HCT116, DLD1, Lovo), and measured the mRNA and protein expression levels of NOP14 in colorectal cancer cells using qPCR and Western blotting. GFP-NOP14 was constructed and siRNA fragments against NOP14 were synthesized to investigate the importance of NOP14 for the development of colorectal cells. Transwell migration assays were used to measure cell invasion and migration, CCK-8 kits were used to measure cell activity, and flow cytometry was applied to the observation of apoptosis. We found that both the mRNA and protein levels of NOP14 were significantly upregulated in CRC tissues and cell lines. Overexpression of GFP-NOP14 markedly promoted the growth, migration, and invasion of the CRC cells HT19 and SW480, while genetic knockdown of NOP14 inhibited these behaviors. Overexpression of NOP14 promoted the expression of NRIP1 and phosphorylated inactivation of GSK-3β, leading to the upregulation of β-catenin. Genetic knockdown of NOP14 had the opposite effect on NRIP1/GSK-3/β-catenin signals. NOP14 therefore appears to be overexpressed in clinical samples and cell lines of colorectal cancer, and promotes the proliferation, growth, and metastasis of colorectal cancer cells by modulating the NRIP1/GSK-3β/β-catenin signaling pathway.
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Affiliation(s)
- Xuanjin Zhu
- Department of General Surgery, Guangzhou Red Cross Hospital, Medical College of Jinan University, Guangzhou.
| | - Weilu Jia
- School of Clinical Medicine, Guizhou Medical University, Guiyang.
| | - Yong Yan
- Department of General Surgery, Guangzhou Red Cross Hospital, Medical College of Jinan University, Guangzhou .
| | - Yong Huang
- Department of General Surgery, Guangzhou Red Cross Hospital, Medical College of Jinan University, Guangzhou .
| | - Bailin Wang
- Department of General Surgery, Guangzhou Red Cross Hospital, Medical College of Jinan University, Guangzhou .
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Tian S, Li Q, Li R, Chen X, Tao Z, Gong H, Wang X, Hu X. Development and Validation of a Prognostic Nomogram for Hypopharyngeal Carcinoma. Front Oncol 2021; 11:696952. [PMID: 34235086 PMCID: PMC8255987 DOI: 10.3389/fonc.2021.696952] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 06/07/2021] [Indexed: 12/14/2022] Open
Abstract
Hypopharyngeal squamous-cell carcinoma (HSCC) is a relatively rare head and neck cancer, with great variation in patient outcomes. This study aimed to develop a prognostic nomogram for patients with HSCC. From the Surveillance, Epidemiology, and End Results (SEER) database, we retrieved the clinical data of 2198 patients diagnosed with HSCC between 2010 and 2016. The patients were randomly assigned at a 4:1 ratio to the training set or the validation set. An external validation was performed by a set of 233 patients with locally advanced HSCC treated at our center. A Cox proportional hazards regression model was used to assess the relationship between each variable and overall survival (OS). Cox multivariate regression analysis was performed, and the results were used to develop a prognostic nomogram. The calibration curve and concordance index (C-index) were used to evaluate the accuracy of the prognostic nomogram. With a median overall follow-up time of 41 months (interquartile range: 20 to 61), the median OS for the entire cohort of SEER database was 24 months. The 3-year and 5-year OS rates were 41.3% and 32.5%, respectively. The Cox multivariate regression analysis of the training set showed that age, marital status, race, T stage, N stage, M stage, TNM stage, local treatment, and chemotherapy were correlated with OS. The nomogram showed a superior C-index over TNM stage (training set: 0.718 vs 0.627; validation set: 0.708 vs 0.598; external validation set: 0.709 vs 0.597), and the calibration curve showed a high level of concordance between the predicted OS and the actual OS. The nomogram provides a relatively accurate and applicable prediction of the survival outcome of patients with HSCC.
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Affiliation(s)
- Shu Tian
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Radiation Oncology, Eye Ear Nose and Throat Hospital, Fudan University, Shanghai, China
| | - Qin Li
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Fudan University Shanghai Cancer Center, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Ruichen Li
- Department of Radiation Oncology, Eye Ear Nose and Throat Hospital, Fudan University, Shanghai, China
| | - Xinyu Chen
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhonghua Tao
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Hongli Gong
- Shanghai Key Clinical Disciplines of Otorhinolaryngology, Department of Otolaryngology, Eye Ear Nose and Throat Hospital, Fudan University, Shanghai, China
| | - Xiaoshen Wang
- Department of Radiation Oncology, Eye Ear Nose and Throat Hospital, Fudan University, Shanghai, China
| | - Xichun Hu
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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Wang S, Liu Y, Shi Y, Guan J, Liu M, Wang W. Development and external validation of a nomogram predicting overall survival after curative resection of colon cancer. J Int Med Res 2021; 49:3000605211015023. [PMID: 33990147 PMCID: PMC8127758 DOI: 10.1177/03000605211015023] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 04/13/2021] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVE To develop and externally validate a prognostic nomogram to predict overall survival (OS) in patients with resectable colon cancer. METHODS Data for 50,996 patients diagnosed with non-metastatic colon cancer were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were assigned randomly to the training set (n = 34,168) or validation set (n = 16,828). Independent prognostic factors were identified by multivariate Cox proportional hazards regression analysis and used to construct the nomogram. Harrell's C-index and calibration plots were calculated using the SEER validation set. Additional external validation was performed using a Chinese dataset (n = 342). RESULTS Harrell's C-index of the nomogram for OS in the SEER validation set was 0.71, which was superior to that using the 7th edition of the American Joint Committee on Cancer TNM staging (0.59). Calibration plots showed consistency between actual observations and predicted 1-, 3-, and 5-year survival. Harrell's C-index (0.72) and calibration plot showed excellent predictive accuracy in the external validation set. CONCLUSIONS We developed a nomogram to predict OS after curative resection for colon cancer. Validation using the SEER and external datasets revealed good discrimination and calibration. This nomogram may help predict individual survival in patients with colon cancer.
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Affiliation(s)
- Shuanhu Wang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Yakui Liu
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Yi Shi
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Jiajia Guan
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Mulin Liu
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Wenbin Wang
- Department of General Surgery, The Fourth Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
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Kou FR, Zhang YZ, Xu WR. Prognostic nomograms for predicting overall survival and cause-specific survival of signet ring cell carcinoma in colorectal cancer patients. World J Clin Cases 2021; 9:2503-2518. [PMID: 33889615 PMCID: PMC8040180 DOI: 10.12998/wjcc.v9.i11.2503] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 01/28/2021] [Accepted: 02/12/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Signet ring cell carcinoma (SRCC) is an uncommon subtype in colorectal cancer (CRC), with a short survival time. Therefore, it is imperative to establish a useful prognostic model. As a simple visual predictive tool, nomograms combining a quantification of all proven prognostic factors have been widely used for predicting the outcomes of patients with different cancers in recent years. Until now, there has been no nomogram to predict the outcome of CRC patients with SRCC.
AIM To build effective nomograms for predicting overall survival (OS) and cause-specific survival (CSS) of CRC patients with SRCC.
METHODS Data were extracted from the Surveillance, Epidemiology, and End Results database between 2004 and 2015. Multivariate Cox regression analyses were used to identify independent variables for both OS and CSS to construct the nomograms. Performance of the nomograms was assessed by concordance index, calibration curves, and receiver operating characteristic (ROC) curves. ROC curves were also utilized to compare benefits between the nomograms and the tumor-node-metastasis (TNM) staging system. Patients were classified as high-risk, moderate-risk, and low-risk groups using the novel nomograms. Kaplan-Meier curves were plotted to compare survival differences.
RESULTS In total, 1230 patients were included. The concordance index of the nomograms for OS and CSS were 0.737 (95% confidence interval: 0.728-0.747) and 0.758 (95% confidence interval: 0.738-0.778), respectively. The calibration curves and ROC curves demonstrated good predictive accuracy. The 1-, 3-, and 5-year area under the curve values of the nomogram for predicting OS were 0.796, 0.825 and 0.819, in comparison to 0.743, 0.798, and 0.803 for the TNM staging system. In addition, the 1-, 3-, and 5-year area under the curve values of the nomogram for predicting CSS were 0.805, 0.847 and 0.863, in comparison to 0.740, 0.794, and 0.800 for the TNM staging system. Based on the novel nomograms, stratified analysis showed that the 5-year probability of survival in the high-risk, moderate-risk, and low-risk groups was 6.8%, 37.7%, and 67.0% for OS (P < 0.001), as well as 9.6%, 38.5%, and 67.6% for CSS (P < 0.001), respectively.
CONCLUSION Convenient and visual nomograms were built and validated to accurately predict the OS and CSS rates for CRC patients with SRCC, which are superior to the conventional TNM staging system.
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Affiliation(s)
- Fu-Rong Kou
- Department of Day Oncology Unit, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, Beijing 100142, China
| | - Yang-Zi Zhang
- Department of Radiation Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, Beijing 100142, China
| | - Wei-Ran Xu
- Department of Oncology, Peking University International Hospital, Beijing 102206, China
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17
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Lv Z, Liang Y, Liu H, Mo D. Association of chemotherapy with survival in stage II colon cancer patients who received radical surgery: a retrospective cohort study. BMC Cancer 2021; 21:306. [PMID: 33757442 PMCID: PMC7989005 DOI: 10.1186/s12885-021-08057-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 03/17/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND It remains controversial whether patients with Stage II colon cancer would benefit from chemotherapy after radical surgery. This study aims to assess the real effectiveness of chemotherapy in patients with stage II colon cancer undergoing radical surgery and to construct survival prediction models to predict the survival benefits of chemotherapy. METHODS Data for stage II colon cancer patients with radical surgery were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (1:1) was performed according to receive or not receive chemotherapy. Competitive risk regression models were used to assess colon cancer cause-specific death (CSD) and non-colon cancer cause-specific death (NCSD). Survival prediction nomograms were constructed to predict overall survival (OS) and colon cancer cause-specific survival (CSS). The predictive abilities of the constructed models were evaluated by the concordance indexes (C-indexes) and calibration curves. RESULTS A total of 25,110 patients were identified, 21.7% received chemotherapy, and 78.3% were without chemotherapy. A total of 10,916 patients were extracted after propensity score matching. The estimated 3-year overall survival rates of chemotherapy were 0.7% higher than non- chemotherapy. The estimated 5-year and 10-year overall survival rates of non-chemotherapy were 1.3 and 2.1% higher than chemotherapy, respectively. Survival prediction models showed good discrimination (the C-indexes between 0.582 and 0.757) and excellent calibration. CONCLUSIONS Chemotherapy improves the short-term (43 months) survival benefit of stage II colon cancer patients who received radical surgery. Survival prediction models can be used to predict OS and CSS of patients receiving chemotherapy as well as OS and CSS of patients not receiving chemotherapy and to make individualized treatment recommendations for stage II colon cancer patients who received radical surgery.
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Affiliation(s)
- Zhihao Lv
- Proctology Department, Zhongshan Hospital Affiliated to Guangzhou University of Chinese Medicine, No. 3 Kangxin Road, West District, Zhongshan, 528400, Guangdong, People's Republic of China.
| | - Yuqi Liang
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People's Republic of China
| | - Huaxi Liu
- College of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Delong Mo
- Proctology Department, Zhongshan Hospital Affiliated to Guangzhou University of Chinese Medicine, No. 3 Kangxin Road, West District, Zhongshan, 528400, Guangdong, People's Republic of China
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Xu J, Weng J, Yang J, Shi X, Hou R, Zhou X, Zhou Z, Wang Z, Chen C. Development and validation of a nomogram to predict the mortality risk in elderly patients with ARF. PeerJ 2021; 9:e11016. [PMID: 33854838 PMCID: PMC7953875 DOI: 10.7717/peerj.11016] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 02/05/2021] [Indexed: 12/24/2022] Open
Abstract
Background Acute respiratory failure (ARF) is a life-threatening complication in elderly patients. We developed a nomogram model to explore the risk factors of prognosis and the short-term mortality in elderly patients with ARF. Methods A total of 759 patients from MIMIC-III database were categorized into the training set and 673 patients from our hospital were categorized into the validation set. Demographical, laboratory variables, SOFA score and APS-III score were collected within the first 24 h after the ICU admission. A 30-day follow-up was performed for all patients. Results Multivariate logistic regression analysis showed that the heart rate, respiratoryrate, systolic pressure, SPO2, albumin and 24 h urine output were independent prognostic factors for 30-day mortality in ARF patients. A nomogram was established based on above independent prognostic factors. This nomogram had a C-index of 0.741 (95% CI [0.7058-0.7766]), and the C-index was 0.687 (95% CI [0.6458-0.7272]) in the validation set. The calibration curves both in training and validation set were close to the ideal model. The SOFA had a C-index of 0.653 and the APS-III had a C-index of 0.707 in predicting 30-day mortality. Conclusion Our nomogram performed better than APS-III and SOFA scores and should be useful as decision support on the prediction of mortality risk in elderly patients with ARF.
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Affiliation(s)
- Junnan Xu
- Department of Emergency Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China, China
| | - Jie Weng
- Department of General Practice, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China, China
| | - Jingwen Yang
- Department of Geriatric Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China, China
| | - Xuan Shi
- Department of Geriatric Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China, China
| | - Ruonan Hou
- Department of General Practice, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China, China
| | - Xiaoming Zhou
- Department of General Practice, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China, China
| | - Zhiliang Zhou
- Department of Emergency Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China, China
| | - Zhiyi Wang
- Department of General Practice, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China, China.,Center for Health Assessment, Wenzhou Medical University, Wenzhou, China, China
| | - Chan Chen
- Department of Geriatric Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China, China
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Liu Z, Xu Y, Xu G, Baklaushev VP, Chekhonin VP, Peltzer K, Ma W, Wang X, Wang G, Zhang C. Nomogram for predicting overall survival in colorectal cancer with distant metastasis. BMC Gastroenterol 2021; 21:103. [PMID: 33663400 PMCID: PMC7934422 DOI: 10.1186/s12876-021-01692-x] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 02/24/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is a major cancer burden, and prognosis is determined by many demographic and clinicopathologic factors. The present study aimed to construct a prognostic nomogram for colorectal cancer patients with distant metastasis. METHODS Colorectal cancer patients with distant metastasis diagnosed between 2010 and 2016 were selected from the Surveillance, Epidemiology, and End Results database. Cox proportional hazards regression was used to identify independent prognostic factors. A nomogram was constructed to predict survival, and validation was performed. RESULTS A total of 7099 stage IV colorectal cancer patients were enrolled in the construction cohort. The median overall survival was 20.0 (95% CI 19.3-20.7) months. Age at diagnosis, marital status, race, primary tumour site, tumour grade, CEA level, T stage, N stage, presence of bone, brain, liver and lung metastasis, surgery for primary site and performance of chemotherapy were independent prognostic factors. The nomogram was constructed and the calibration curve showed satisfactory agreement. The C-index was 0.742 (95% CI 0.726-0.758). In the validation cohort (7098 patients), the nomogram showed satisfactory discrimination and calibration with a C-index of 0.746 (95% CI 0.730-0.762). CONCLUSION A series of factors associated with the survival of CRC patients with distant metastasis were found. Based on the identified factors, a nomogram was generated to predict the survival of stage IV colorectal cancer patients. The predictive model showed satisfactory discrimination and calibration, which can provide a reference for survival estimation and individualized treatment decisions.
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Affiliation(s)
- Zheng Liu
- Department of Bone and Soft Tissue Tumors, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
- Department of Orthopedics, Heilongjiang Provincial Hospital, Harbin, Heilongjiang Province, China
- Sino-Russian Joint Research Center for Bone Metastasis in Malignant Tumor, Tianjin, China
| | - Yao Xu
- Department of Bone and Soft Tissue Tumors, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
- Sino-Russian Joint Research Center for Bone Metastasis in Malignant Tumor, Tianjin, China
| | - Guijun Xu
- Department of Bone and Soft Tissue Tumors, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
- Department of Orthopaedics, Tianjin Hospital, Tianjin, China
- Sino-Russian Joint Research Center for Bone Metastasis in Malignant Tumor, Tianjin, China
| | - Vladimir P Baklaushev
- Federal Research and Clinical Center of Specialized Medical Care and Medical Technologies, Federal Biomedical Agency of the Russian Federation, Moscow, Russian Federation
- Sino-Russian Joint Research Center for Bone Metastasis in Malignant Tumor, Tianjin, China
| | - Vladimir P Chekhonin
- Department of Basic and Applied Neurobiology, Federal Medical Research Center for Psychiatry and Narcology, Moscow, Russian Federation
- Sino-Russian Joint Research Center for Bone Metastasis in Malignant Tumor, Tianjin, China
| | - Karl Peltzer
- Department of Research and Innovation, University of Limpopo, Turfloop, South Africa
| | - Wenjuan Ma
- Department of Breast Imaging, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
- Sino-Russian Joint Research Center for Bone Metastasis in Malignant Tumor, Tianjin, China
| | - Xin Wang
- Department of Epidemiology and Biostatistics, First Affiliated Hospital, Army Medical University, Chongqing, China
- Sino-Russian Joint Research Center for Bone Metastasis in Malignant Tumor, Tianjin, China
| | - Guowen Wang
- Department of Bone and Soft Tissue Tumors, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
- Sino-Russian Joint Research Center for Bone Metastasis in Malignant Tumor, Tianjin, China.
| | - Chao Zhang
- Department of Bone and Soft Tissue Tumors, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
- Sino-Russian Joint Research Center for Bone Metastasis in Malignant Tumor, Tianjin, China.
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Tang M, Wang H, Cao Y, Zeng Z, Shan X, Wang L. Nomogram for predicting occurrence and prognosis of liver metastasis in colorectal cancer: a population-based study. Int J Colorectal Dis 2021; 36:271-282. [PMID: 32965529 DOI: 10.1007/s00384-020-03722-8] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/21/2020] [Indexed: 02/04/2023]
Abstract
PURPOSE This study aimed to investigate the prevalence, risk, and prognostic factors for synchronous liver metastasis (LM) in colorectal cancer (CRC) and to construct nomogram for predicting occurrence and prognosis of synchronous LM. METHODS A total of 203,998 CRC patients who were registered in the SEER database between 2010 and 2016 were included. Logistic regression was used to analyze risk factors and Kaplan-Meier was used to estimate the overall survival of CRC patients with LM. Potential prognostic factors were identified by multivariable Cox regression. For predicting the risk for development and prognosis in CRC patients with LM, we constructed nomogram and the predictive performance was estimated by the receiver operating characteristics cure, the concordance index, and calibration curve. RESULTS In total, 15.3% of the CRC patients (N = 31,288) had synchronous LM. Male gender, black, uninsured status, left colon, T4/T1, and bone and lung metastases were positively associated with synchronous LM risk. The 1-year, 3-year, and 5-year overall survival rate was 49.1%, 18.4%, and 9.2%, respectively. Older age, male gender, black, uninsured status, poor histological differentiation, lymphatic metastasis, T4/T1, positive carcinoembryonic antigen, and lung, bone, and brain metastases were associated with the overall survival. Nomogram was constructed to predict the development and prognosis of synchronous LM and both of them were proved to have good calibration and discrimination. CONCLUSION LM is highly prevalent in CRC patients. Nomogram basing on the risk and prognostic factors for synchronous LM was proved to have good performance for predicting the probability of LM occurrence and prognosis.
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Affiliation(s)
- Mingshuang Tang
- Emergence Department, The Second Affiliated Hospital of Chongqing Medical University, 76 Linjiang Road, Yuzhong District, Chongqing, 400010, China.,Department of Epidemiology and Biostatistics, First Affiliated Hospital, Army Medical University, Chongqing, China
| | - Hongmei Wang
- Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yitong Cao
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Ziqian Zeng
- Department of Epidemiology and Biostatistics, First Affiliated Hospital, Army Medical University, Chongqing, China
| | - Xuefeng Shan
- Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lihua Wang
- Emergence Department, The Second Affiliated Hospital of Chongqing Medical University, 76 Linjiang Road, Yuzhong District, Chongqing, 400010, China.
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Li Y, Liu W, Zhou Z, Ge H, Zhao L, Liu H, Song X, Wang D, Pei Q, Tan F. Development and validation of prognostic nomograms for early-onset locally advanced colon cancer. Aging (Albany NY) 2020; 13:477-492. [PMID: 33289705 PMCID: PMC7834989 DOI: 10.18632/aging.202157] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 10/20/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND The incidence of colorectal cancer in patients younger than 50 years has been increasing in recent years. OBJECTIVE Develop and validate prognostic nomograms predicting overall survival (OS) and cancer-specific survival (CSS) for early-onset locally advanced colon cancer (EOLACC) based on the Surveillance, Epidemiology, and End Results (SEER) database. RESULTS The entire cohort comprised 13,755 patients with EOLACC. The nomogram predicting OS for EOLACC displayed that T stage contributed the most to prognosis, followed by N stage, regional nodes examined (RNE) and surgery. The nomogram predicting CSS for EOLACC demonstrated similar results. Various methods identified the discriminating superiority of the nomograms. X-tile software was used to classify patients into high-risk, medium-risk, and low-risk according to the risk score of the nomograms. The risk stratification effectively avoided the survival paradox. CONCLUSIONS We established and validated nomograms for predicting OS and CSS based on a national cohort of almost 13,000 EOLACC patients. The nomograms could effectively solve the issue of survival paradox of the AJCC staging system and be an excellent tool to integrate the clinical characteristics to guide the therapeutic choice for EOLACC patients. METHODS Nomograms were constructed based on the SEER database and the Cox regression model.
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Affiliation(s)
- Yuqiang Li
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Wenxue Liu
- Department of Rheumatology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.,Department of Cardiology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhongyi Zhou
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Heming Ge
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Lilan Zhao
- Department of Thoracic surgery, Fujian Provincial Hospital, Fuzhou, China
| | - Heli Liu
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Xiangping Song
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Dan Wang
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Qian Pei
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Fengbo Tan
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
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Chen Q, Wang S, Lang JH. Development and validation of Nomograms for predicting overall survival and Cancer-specific survival in patients with ovarian clear cell carcinoma. J Ovarian Res 2020; 13:123. [PMID: 33069259 PMCID: PMC7568829 DOI: 10.1186/s13048-020-00727-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 10/07/2020] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Ovarian clear cell carcinoma (OCCC) is a rare histologic type of ovarian cancer. There is a lack of an efficient prognostic predictive tool for OCCC in clinical work. This study aimed to construct and validate nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with OCCC. METHODS Data of patients with primary diagnosed OCCC in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016 was extracted. Prognostic factors were evaluated with LASSO Cox regression and multivariate Cox regression analysis, which were applied to construct nomograms. The performance of the nomogram models was assessed by the concordance index (C-index), calibration plots, decision curve analysis (DCA) and risk subgroup classification. The Kaplan-Meier curves were plotted to compare survival outcomes between subgroups. RESULTS A total of 1541 patients from SEER registries were randomly divided into a training cohort (n = 1079) and a validation cohort (n = 462). Age, laterality, stage, lymph node (LN) dissected, organ metastasis and chemotherapy were independently and significantly associated with OS, while laterality, stage, LN dissected, organ metastasis and chemotherapy were independent risk factors for CSS. Nomograms were developed for the prediction of 3- and 5-year OS and CSS. The C-indexes for OS and CSS were 0.802[95% confidence interval (CI) 0.773-0.831] and 0.802 (0.769-0.835), respectively, in the training cohort, while 0.746 (0.691-0.801) and 0.770 (0.721-0.819), respectively, in the validation cohort. Calibration plots illustrated favorable consistency between the nomogram predicted and actual survival. C-index and DCA curves also indicated better performance of nomogram than the AJCC staging system. Significant differences were observed in the survival curves of different risk subgroups. CONCLUSIONS We have constructed predictive nomograms and a risk classification system to evaluate the OS and CSS of OCCC patients. They were validated to be of satisfactory predictive value, and could aid in future clinical practice.
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Affiliation(s)
- Qian Chen
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 ShuaiFuYuan, Wangfujing, DongCheng District, Beijing, 100730 P.R. China
| | - Shu Wang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 ShuaiFuYuan, Wangfujing, DongCheng District, Beijing, 100730 P.R. China
| | - Jing-He Lang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 ShuaiFuYuan, Wangfujing, DongCheng District, Beijing, 100730 P.R. China
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Mo S, Zhou Z, Dai W, Xiang W, Han L, Zhang L, Wang R, Cai S, Li Q, Cai G. Development and external validation of a predictive scoring system associated with metastasis of T1-2 colorectal tumors to lymph nodes. Clin Transl Med 2020; 10:275-287. [PMID: 32508061 PMCID: PMC7240869 DOI: 10.1002/ctm2.30] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 04/08/2020] [Accepted: 04/08/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND It is critical for determining the optimum therapeutic solutions for T1-2 colorectal cancer (CRC) to accurately predict lymph node metastasis (LNM) status. The purpose of the present study is to establish and verify a nomogram to predict LNM status in T1-2 CRCs. METHODS A total of 16 600 T1-2 CRC patients were enrolled and classified into the training, internal validation, and external validation cohorts. The independent predictive parameters were determined by univariate and multivariate analyses to develop a nomogram to predict the probability of LNM status. The calibration curve, the area under the receiver operating characteristic curve (AUROC), and decision curve analysis (DCA) were used to evaluate the performance of the nomogram, and an external verification cohort was to verify the applicability of the nomogram. RESULTS Seven independent predictors of LNM in T1-2 CRC were identified in the multivariable analysis, including age, tumor site, tumor grade, perineural invasion, preoperative carcinoembryonic antigen, clinical assessment of LNM, and T stage. A nomogram incorporating the seven predictors was constructed. The nomogram yielded good discrimination and calibration, with AUROCs of 0.72 (95% confidence interval [CI]: 0.70-0.75), 0.70 (95% CI: 0.67-0.74), and 0.74 (95% CI: 0.71-0.79) in the training, internal validation, and external validation cohorts, respectively. DCA showed that the predictive scoring system had high clinical application value. CONCLUSIONS We proposed a novel predictive model for LNM in T1-2 CRC patients to assist physicians in making treatment decisions. The nomogram is advantageous for tailoring therapy in T1-2 CRC patients.
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Affiliation(s)
- Shaobo Mo
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Zheng Zhou
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Weixing Dai
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Wenqiang Xiang
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Lingyu Han
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Long Zhang
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of Cancer InstituteFudan University Shanghai Cancer CenterFudan UniversityShanghaiChina
| | - Renjie Wang
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Sanjun Cai
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Qingguo Li
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Guoxiang Cai
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
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Mo S, Cai X, Zhou Z, Li Y, Hu X, Ma X, Zhang L, Cai S, Peng J. Nomograms for predicting specific distant metastatic sites and overall survival of colorectal cancer patients: A large population-based real-world study. Clin Transl Med 2020; 10:169-181. [PMID: 32508027 PMCID: PMC7240852 DOI: 10.1002/ctm2.20] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 03/19/2020] [Accepted: 03/20/2020] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND This study aims to develop functional nomograms to predict specific distant metastatic sites and overall survival (OS) of colorectal cancer (CRC) patients. METHODS CRC case data were retrospectively recruited from a large population-based public dataset. Nomograms were developed to predict the probabilities of specific distant metastatic sites and OS of CRC patients. The performance of nomogram was evaluated with the concordance index (C-index), calibration curves, area under the curve (AUC), and decision curve analysis (DCA). RESULTS A total of 142 343 cases were included in the current study. On the basis of univariate and multivariate analyses, clinicopathological features were correlated with specific distant metastatic sites and survival outcomes and were used to establish nomograms. The nomograms showed excellent accuracy in predicting specific distant metastatic sites. The C-indexes for the prediction of liver, lung, bone, and brain metastases were 0.82 (95% confidence interval (CI), 0.81-0.83), 0.80 (95% CI, 0.78-0.81), 0.83 (95% CI, 0.79-0.86), and 0.73 (95% CI, 0.72-0.84), respectively. Then, a prognostic nomogram integrating clinicopathological features and specific distant metastatic sites was established to predict 1-, 3-, and 5-year OS of CRC, with AUCs of 0.764 (95% CI, 0.741-0.783), 0.762 (95% CI, 0.745-0.781), and 0.745 (95% CI, 0.730-0.761), respectively. DCA showed that the prognostic nomogram had a better clinical application value than current TNM staging system. CONCLUSIONS Based on clinicopathological features, original nomograms were constructed for clinicians to predict specific distant metastatic sites and OS of CRC patients. These models could help to support the postoperative personalized assessment.
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Affiliation(s)
- Shaobo Mo
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of Oncology, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Xin Cai
- Department of Radiation OncologyShanghai Proton and Heavy Ion CenterShanghaiChina
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation TherapyShanghaiChina
| | - Zheng Zhou
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of Oncology, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Yaqi Li
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of Oncology, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Xiang Hu
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of Oncology, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Xiaoji Ma
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of Oncology, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Long Zhang
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of Cancer InstituteFudan University Shanghai Cancer CenterFudan UniversityShanghaiChina
| | - Sanjun Cai
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of Oncology, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Junjie Peng
- Department of Colorectal SurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of Oncology, Shanghai Medical CollegeFudan UniversityShanghaiChina
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