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A Practical Nomogram for Predicting the Prognosis of Elderly Patients with Gastric Adenocarcinoma After Gastrectomy

PURPOSE: To establish a pragmatic prognostic nomogram for predicting the survival of elderly patients undergoing gastrectomy for gastric adenocarcinoma. PATIENTS AND METHODS: Data of elderly patients undergoing gastrectomy for gastric adenocarcinoma between 2004 and 2015 were obtained from the Surve...

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Autores principales: Yang, Heli, Ji, Xin, Jin, Chenggen, Ji, Ke, Jia, Ziyu, Wu, Xiaojiang, Zhang, Ji, Bu, Zhaode
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760985/
https://www.ncbi.nlm.nih.gov/pubmed/35046708
http://dx.doi.org/10.2147/IJGM.S343306
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author Yang, Heli
Ji, Xin
Jin, Chenggen
Ji, Ke
Jia, Ziyu
Wu, Xiaojiang
Zhang, Ji
Bu, Zhaode
author_facet Yang, Heli
Ji, Xin
Jin, Chenggen
Ji, Ke
Jia, Ziyu
Wu, Xiaojiang
Zhang, Ji
Bu, Zhaode
author_sort Yang, Heli
collection PubMed
description PURPOSE: To establish a pragmatic prognostic nomogram for predicting the survival of elderly patients undergoing gastrectomy for gastric adenocarcinoma. PATIENTS AND METHODS: Data of elderly patients undergoing gastrectomy for gastric adenocarcinoma between 2004 and 2015 were obtained from the Surveillance, Epidemiology, and End Results database. Prognostic factors were identified by the Kaplan–Meier method and the Cox proportional hazards model. Based on these factors, we developed a nomogram to predict the overall survival (OS) and gastric cancer-specific survival (GCSS). Concordance index (C-index) and calibration curve are employed to assess the predictive accuracy of the model. Decision curve analysis (DCA) and receiver operating characteristic curve (ROC) analysis are applied to further appraise the clinical utility of the model. RESULTS: A total of 8401 cases were incorporated into this research. After univariate and multivariate analyses, nine prognostic factors of OS were identified, including age (P < 0.001), race (P < 0.001), marital status (P < 0.001), tumor site (P < 0.001), tumor size (P = 0.024), differentiation (P < 0.001), T stage (P < 0.001), N stage (P < 0.001), and M stage (P < 0.001); ten prognostic factors of GCSS were identified, including age (P < 0.001), race (P < 0.001), tumor site (P < 0.001), tumor size (P = 0.002), differentiation (P < 0.001), T stage (P < 0.001), N stage (P < 0.001), M stage (P < 0.001), radiotherapy (P < 0.001) and chemotherapy (P < 0.001). The C-index of the constructed nomogram for OS was 0.708 (95% CI: 0.701–0.715) while for GCSS was 0.745 (95% CI: 0.737–0.753). The calibration curves of the nomogram predictions and actual observations displayed good agreement for the 3- and 5-year OS and GCSS probabilities. The results of DCA and the area under the curve calculated by ROC analysis showed that the developed model was superior than TNM stage. CONCLUSION: The nomogram we established could accurately predict the prognosis of individual elderly patients who underwent gastrectomy for gastric adenocarcinoma.
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spelling pubmed-87609852022-01-18 A Practical Nomogram for Predicting the Prognosis of Elderly Patients with Gastric Adenocarcinoma After Gastrectomy Yang, Heli Ji, Xin Jin, Chenggen Ji, Ke Jia, Ziyu Wu, Xiaojiang Zhang, Ji Bu, Zhaode Int J Gen Med Original Research PURPOSE: To establish a pragmatic prognostic nomogram for predicting the survival of elderly patients undergoing gastrectomy for gastric adenocarcinoma. PATIENTS AND METHODS: Data of elderly patients undergoing gastrectomy for gastric adenocarcinoma between 2004 and 2015 were obtained from the Surveillance, Epidemiology, and End Results database. Prognostic factors were identified by the Kaplan–Meier method and the Cox proportional hazards model. Based on these factors, we developed a nomogram to predict the overall survival (OS) and gastric cancer-specific survival (GCSS). Concordance index (C-index) and calibration curve are employed to assess the predictive accuracy of the model. Decision curve analysis (DCA) and receiver operating characteristic curve (ROC) analysis are applied to further appraise the clinical utility of the model. RESULTS: A total of 8401 cases were incorporated into this research. After univariate and multivariate analyses, nine prognostic factors of OS were identified, including age (P < 0.001), race (P < 0.001), marital status (P < 0.001), tumor site (P < 0.001), tumor size (P = 0.024), differentiation (P < 0.001), T stage (P < 0.001), N stage (P < 0.001), and M stage (P < 0.001); ten prognostic factors of GCSS were identified, including age (P < 0.001), race (P < 0.001), tumor site (P < 0.001), tumor size (P = 0.002), differentiation (P < 0.001), T stage (P < 0.001), N stage (P < 0.001), M stage (P < 0.001), radiotherapy (P < 0.001) and chemotherapy (P < 0.001). The C-index of the constructed nomogram for OS was 0.708 (95% CI: 0.701–0.715) while for GCSS was 0.745 (95% CI: 0.737–0.753). The calibration curves of the nomogram predictions and actual observations displayed good agreement for the 3- and 5-year OS and GCSS probabilities. The results of DCA and the area under the curve calculated by ROC analysis showed that the developed model was superior than TNM stage. CONCLUSION: The nomogram we established could accurately predict the prognosis of individual elderly patients who underwent gastrectomy for gastric adenocarcinoma. Dove 2022-01-11 /pmc/articles/PMC8760985/ /pubmed/35046708 http://dx.doi.org/10.2147/IJGM.S343306 Text en © 2022 Yang et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Yang, Heli
Ji, Xin
Jin, Chenggen
Ji, Ke
Jia, Ziyu
Wu, Xiaojiang
Zhang, Ji
Bu, Zhaode
A Practical Nomogram for Predicting the Prognosis of Elderly Patients with Gastric Adenocarcinoma After Gastrectomy
title A Practical Nomogram for Predicting the Prognosis of Elderly Patients with Gastric Adenocarcinoma After Gastrectomy
title_full A Practical Nomogram for Predicting the Prognosis of Elderly Patients with Gastric Adenocarcinoma After Gastrectomy
title_fullStr A Practical Nomogram for Predicting the Prognosis of Elderly Patients with Gastric Adenocarcinoma After Gastrectomy
title_full_unstemmed A Practical Nomogram for Predicting the Prognosis of Elderly Patients with Gastric Adenocarcinoma After Gastrectomy
title_short A Practical Nomogram for Predicting the Prognosis of Elderly Patients with Gastric Adenocarcinoma After Gastrectomy
title_sort practical nomogram for predicting the prognosis of elderly patients with gastric adenocarcinoma after gastrectomy
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760985/
https://www.ncbi.nlm.nih.gov/pubmed/35046708
http://dx.doi.org/10.2147/IJGM.S343306
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