Cargando…

ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients

BACKGROUND: Esophageal cancer (EC) is considered as one of the deadliest malignancies with respect to incidence and mortality rate, and numerous risk factors may affect the prognosis of EC patients. For better understanding of the risk factors associated with the onset and prognosis of this malignan...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Jingcheng, Shang, Jun, Song, Qian, Yang, Zuyi, Chen, Jianing, Yu, Ying, Shi, Leming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7552344/
https://www.ncbi.nlm.nih.gov/pubmed/33046018
http://dx.doi.org/10.1186/s12885-020-07479-9
_version_ 1783593382114754560
author Yang, Jingcheng
Shang, Jun
Song, Qian
Yang, Zuyi
Chen, Jianing
Yu, Ying
Shi, Leming
author_facet Yang, Jingcheng
Shang, Jun
Song, Qian
Yang, Zuyi
Chen, Jianing
Yu, Ying
Shi, Leming
author_sort Yang, Jingcheng
collection PubMed
description BACKGROUND: Esophageal cancer (EC) is considered as one of the deadliest malignancies with respect to incidence and mortality rate, and numerous risk factors may affect the prognosis of EC patients. For better understanding of the risk factors associated with the onset and prognosis of this malignancy, we develop an interactive web-based tool for the convenient analysis of clinical and survival characteristics of EC patients. METHODS: The clinical data were obtained from The Surveillance, Epidemiology, and End Results (SEER) database. Seven analysis and visualization modules were built with Shiny. RESULTS: The Esophageal Cancer Clinical Data Interactive Analysis (ECCDIA, http://webapps.3steps.cn/ECCDIA/) was developed to provide basic data analysis, visualization, survival analysis, and nomogram of the overall group and subgroups of 77,273 EC patients recorded in SEER. The basic data analysis modules contained distribution analysis of clinical factor ratios, Sankey plot analysis for relationships between clinical factors, and a map for visualizing the distribution of clinical factors. The survival analysis included Kaplan-Meier (K-M) analysis and Cox analysis for different subgroups of EC patients. The nomogram module enabled clinicians to precisely predict the survival probability of different subgroups of EC patients. CONCLUSION: ECCDIA provides clinicians with an interactive prediction and visualization tool for visualizing invaluable clinical and prognostic information of individual EC patients, further providing useful information for better understanding of esophageal cancer.
format Online
Article
Text
id pubmed-7552344
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-75523442020-10-13 ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients Yang, Jingcheng Shang, Jun Song, Qian Yang, Zuyi Chen, Jianing Yu, Ying Shi, Leming BMC Cancer Technical Advance BACKGROUND: Esophageal cancer (EC) is considered as one of the deadliest malignancies with respect to incidence and mortality rate, and numerous risk factors may affect the prognosis of EC patients. For better understanding of the risk factors associated with the onset and prognosis of this malignancy, we develop an interactive web-based tool for the convenient analysis of clinical and survival characteristics of EC patients. METHODS: The clinical data were obtained from The Surveillance, Epidemiology, and End Results (SEER) database. Seven analysis and visualization modules were built with Shiny. RESULTS: The Esophageal Cancer Clinical Data Interactive Analysis (ECCDIA, http://webapps.3steps.cn/ECCDIA/) was developed to provide basic data analysis, visualization, survival analysis, and nomogram of the overall group and subgroups of 77,273 EC patients recorded in SEER. The basic data analysis modules contained distribution analysis of clinical factor ratios, Sankey plot analysis for relationships between clinical factors, and a map for visualizing the distribution of clinical factors. The survival analysis included Kaplan-Meier (K-M) analysis and Cox analysis for different subgroups of EC patients. The nomogram module enabled clinicians to precisely predict the survival probability of different subgroups of EC patients. CONCLUSION: ECCDIA provides clinicians with an interactive prediction and visualization tool for visualizing invaluable clinical and prognostic information of individual EC patients, further providing useful information for better understanding of esophageal cancer. BioMed Central 2020-10-12 /pmc/articles/PMC7552344/ /pubmed/33046018 http://dx.doi.org/10.1186/s12885-020-07479-9 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Technical Advance
Yang, Jingcheng
Shang, Jun
Song, Qian
Yang, Zuyi
Chen, Jianing
Yu, Ying
Shi, Leming
ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients
title ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients
title_full ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients
title_fullStr ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients
title_full_unstemmed ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients
title_short ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients
title_sort eccdia: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients
topic Technical Advance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7552344/
https://www.ncbi.nlm.nih.gov/pubmed/33046018
http://dx.doi.org/10.1186/s12885-020-07479-9
work_keys_str_mv AT yangjingcheng eccdiaaninteractivewebtoolforthecomprehensiveanalysisofclinicalandsurvivaldataofesophagealcancerpatients
AT shangjun eccdiaaninteractivewebtoolforthecomprehensiveanalysisofclinicalandsurvivaldataofesophagealcancerpatients
AT songqian eccdiaaninteractivewebtoolforthecomprehensiveanalysisofclinicalandsurvivaldataofesophagealcancerpatients
AT yangzuyi eccdiaaninteractivewebtoolforthecomprehensiveanalysisofclinicalandsurvivaldataofesophagealcancerpatients
AT chenjianing eccdiaaninteractivewebtoolforthecomprehensiveanalysisofclinicalandsurvivaldataofesophagealcancerpatients
AT yuying eccdiaaninteractivewebtoolforthecomprehensiveanalysisofclinicalandsurvivaldataofesophagealcancerpatients
AT shileming eccdiaaninteractivewebtoolforthecomprehensiveanalysisofclinicalandsurvivaldataofesophagealcancerpatients