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A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer

BACKGROUND: Few studies have shown nomograms that may predict disease-specific survival (DSS) probability after curative D2 gastrectomy for advanced gastric cancer (AGC), particularly among Chinese patients. This study sought to develop an elaborative nomogram that predicts long-term DSS for AGC in...

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Autores principales: Wang, Wei, Sun, Zhe, Deng, Jing-Yu, Qi, Xiao-Long, Feng, Xing-Yu, Fang, Cheng, Ma, Xing-Hua, Wang, Zhen-Ning, Liang, Han, Xu, Hui-Mian, Zhou, Zhi-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993138/
https://www.ncbi.nlm.nih.gov/pubmed/29764518
http://dx.doi.org/10.1186/s40880-018-0293-0
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author Wang, Wei
Sun, Zhe
Deng, Jing-Yu
Qi, Xiao-Long
Feng, Xing-Yu
Fang, Cheng
Ma, Xing-Hua
Wang, Zhen-Ning
Liang, Han
Xu, Hui-Mian
Zhou, Zhi-Wei
author_facet Wang, Wei
Sun, Zhe
Deng, Jing-Yu
Qi, Xiao-Long
Feng, Xing-Yu
Fang, Cheng
Ma, Xing-Hua
Wang, Zhen-Ning
Liang, Han
Xu, Hui-Mian
Zhou, Zhi-Wei
author_sort Wang, Wei
collection PubMed
description BACKGROUND: Few studies have shown nomograms that may predict disease-specific survival (DSS) probability after curative D2 gastrectomy for advanced gastric cancer (AGC), particularly among Chinese patients. This study sought to develop an elaborative nomogram that predicts long-term DSS for AGC in Chinese patients. METHODS: A retrospective study was conducted on 6753 AGC patients undergoing D2 gastrectomy between January 1, 2000 and December 31, 2012 from three large medical hospitals in China. We assigned patients from Sun Yat-sen University Cancer Center to the training set, and patients from the First Affiliated Hospital of China Medical University and Tianjin Medical University Cancer Hospital to two separate external validation sets. A multivariate survival analysis was performed using Cox proportional hazards regression model in a training set, and a nomogram was constructed. Harrell’s C-index was used to evaluate discrimination and calibration plots were used to validate similarities between survival probabilities predicted by the nomogram model and actual survival rates in two validation sets. RESULTS: The multivariate Cox regression model identified age, tumor size, location, Lauren classification, lymphatic/venous invasion, depth of invasion, and metastatic lymph node ratio as covariates associated with survival. In the training set, the nomogram exhibited superior discrimination power compared with the 8th American Joint Committee on Cancer TNM classification (Harrell’s C-index, 0.82 vs. 0.74; P < 0.001). In two validation sets, the nomogram’s discrimination power was also excellent relative to TNM classification (C-index, 0.83 vs. 0.75 and 0.81 vs. 0.74, respectively; P < 0.001 for both). After calibration, the nomogram produced survival predictions that corresponded closely with actual survival rate. CONCLUSIONS: The established nomogram was able to predict 3-, 5-, and 10-year DSS probabilities for AGC patients. Validation revealed that this nomogram exhibited excellent discrimination and calibration capacity, suggesting its clinical utility.
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spelling pubmed-59931382018-06-21 A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer Wang, Wei Sun, Zhe Deng, Jing-Yu Qi, Xiao-Long Feng, Xing-Yu Fang, Cheng Ma, Xing-Hua Wang, Zhen-Ning Liang, Han Xu, Hui-Mian Zhou, Zhi-Wei Cancer Commun (Lond) Original Article BACKGROUND: Few studies have shown nomograms that may predict disease-specific survival (DSS) probability after curative D2 gastrectomy for advanced gastric cancer (AGC), particularly among Chinese patients. This study sought to develop an elaborative nomogram that predicts long-term DSS for AGC in Chinese patients. METHODS: A retrospective study was conducted on 6753 AGC patients undergoing D2 gastrectomy between January 1, 2000 and December 31, 2012 from three large medical hospitals in China. We assigned patients from Sun Yat-sen University Cancer Center to the training set, and patients from the First Affiliated Hospital of China Medical University and Tianjin Medical University Cancer Hospital to two separate external validation sets. A multivariate survival analysis was performed using Cox proportional hazards regression model in a training set, and a nomogram was constructed. Harrell’s C-index was used to evaluate discrimination and calibration plots were used to validate similarities between survival probabilities predicted by the nomogram model and actual survival rates in two validation sets. RESULTS: The multivariate Cox regression model identified age, tumor size, location, Lauren classification, lymphatic/venous invasion, depth of invasion, and metastatic lymph node ratio as covariates associated with survival. In the training set, the nomogram exhibited superior discrimination power compared with the 8th American Joint Committee on Cancer TNM classification (Harrell’s C-index, 0.82 vs. 0.74; P < 0.001). In two validation sets, the nomogram’s discrimination power was also excellent relative to TNM classification (C-index, 0.83 vs. 0.75 and 0.81 vs. 0.74, respectively; P < 0.001 for both). After calibration, the nomogram produced survival predictions that corresponded closely with actual survival rate. CONCLUSIONS: The established nomogram was able to predict 3-, 5-, and 10-year DSS probabilities for AGC patients. Validation revealed that this nomogram exhibited excellent discrimination and calibration capacity, suggesting its clinical utility. BioMed Central 2018-05-15 /pmc/articles/PMC5993138/ /pubmed/29764518 http://dx.doi.org/10.1186/s40880-018-0293-0 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.
spellingShingle Original Article
Wang, Wei
Sun, Zhe
Deng, Jing-Yu
Qi, Xiao-Long
Feng, Xing-Yu
Fang, Cheng
Ma, Xing-Hua
Wang, Zhen-Ning
Liang, Han
Xu, Hui-Mian
Zhou, Zhi-Wei
A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer
title A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer
title_full A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer
title_fullStr A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer
title_full_unstemmed A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer
title_short A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer
title_sort novel nomogram individually predicting disease-specific survival after d2 gastrectomy for advanced gastric cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993138/
https://www.ncbi.nlm.nih.gov/pubmed/29764518
http://dx.doi.org/10.1186/s40880-018-0293-0
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