Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional study

Abstract Background Whether the tumor‐node‐metastasis (TNM) staging system is appropriate for patients with node‐negative gastric cancer (GC) is still inconclusive. The modified staging system developed by recursive partitioning analysis (RPA) showed good prognostic performance in a variety of cance...

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Main Authors: Jian‐Xian Lin, Zu‐Kai Wang, Wei Wang, Jian‐Wei Xie, Jia‐Bin Wang, Jun Lu, Qi‐Yue Chen, Long‐Long Cao, Mi Lin, Ru‐Hong Tu, Chao‐Hui Zheng, Ping Li, Zhi‐Wei Zhou, Chang‐Ming Huang
Format: Article
Language:English
Published: Wiley 2019-06-01
Series:Cancer Medicine
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Online Access:https://doi.org/10.1002/cam4.2170
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author Jian‐Xian Lin
Zu‐Kai Wang
Wei Wang
Jian‐Wei Xie
Jia‐Bin Wang
Jun Lu
Qi‐Yue Chen
Long‐Long Cao
Mi Lin
Ru‐Hong Tu
Chao‐Hui Zheng
Ping Li
Zhi‐Wei Zhou
Chang‐Ming Huang
author_facet Jian‐Xian Lin
Zu‐Kai Wang
Wei Wang
Jian‐Wei Xie
Jia‐Bin Wang
Jun Lu
Qi‐Yue Chen
Long‐Long Cao
Mi Lin
Ru‐Hong Tu
Chao‐Hui Zheng
Ping Li
Zhi‐Wei Zhou
Chang‐Ming Huang
author_sort Jian‐Xian Lin
collection DOAJ
description Abstract Background Whether the tumor‐node‐metastasis (TNM) staging system is appropriate for patients with node‐negative gastric cancer (GC) is still inconclusive. The modified staging system developed by recursive partitioning analysis (RPA) showed good prognostic performance in a variety of cancers. The application of RPA has not been reported in the prognostic prediction of GC. Methods Node‐negative GC patients who underwent radical resection at Fujian Medical University Union Hospital (n = 862) and Sun Yat‐sen University Cancer Center (n = 311) with at least 5 years of follow‐up were selected as the training set. RPA was used to develop a modified staging system. Patients from the Surveillance, Epidemiology, and End Results database (n = 1415) were selected as the validation set. Results The 5‐year overall survival (OS) rates of patients with 8th AJCC‐TNM stage IA‐IIIA in the training set were IA 95.2%, IB 87.1%, IIA 78.3%, IIB 75.8%, and IIIA 72.6%. Multivariate analysis (MVA) showed that larger tumor size, elder age, and deeper depth of invasion were independent predictors for OS in patients with node‐negative GC (all P < 0.05). Patients were reclassified into RPA I, RPA II, RPA III, and RPA IV stages based on RPA; the 5‐year OS rates were 96.1%, 87.2%, 81.0%, and 64.3%, respectively, with significant difference (P < 0.05). Two‐step MVA showed that the RPA staging system was an independent predictor of OS (P < 0.05). Compared with the 8th AJCC‐TNM staging system, the RPA staging system had a smaller AIC value (2544.9 vs 2576.2), higher χ2 score (104.2 vs 69.6) and higher Harrell's C‐index (0.697 vs 0.669, P = 0.007). The similar results were found in the validation set. Conclusions A new prognostic predictive system based on RPA was successfully developed and validated, which may be suggested for staging node‐negative GC in future.
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spelling doaj.art-e6f6f0672fc84a1f8483431c1d4413212022-12-22T02:38:04ZengWileyCancer Medicine2045-76342019-06-01862962297010.1002/cam4.2170Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional studyJian‐Xian Lin0Zu‐Kai Wang1Wei Wang2Jian‐Wei Xie3Jia‐Bin Wang4Jun Lu5Qi‐Yue Chen6Long‐Long Cao7Mi Lin8Ru‐Hong Tu9Chao‐Hui Zheng10Ping Li11Zhi‐Wei Zhou12Chang‐Ming Huang13Department of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric and Pancreatic Surgery Sun Yat‐sen University Cancer Center Guangzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaDepartment of Gastric and Pancreatic Surgery Sun Yat‐sen University Cancer Center Guangzhou ChinaDepartment of Gastric Surgery Fujian Medical University Union Hospital Fuzhou ChinaAbstract Background Whether the tumor‐node‐metastasis (TNM) staging system is appropriate for patients with node‐negative gastric cancer (GC) is still inconclusive. The modified staging system developed by recursive partitioning analysis (RPA) showed good prognostic performance in a variety of cancers. The application of RPA has not been reported in the prognostic prediction of GC. Methods Node‐negative GC patients who underwent radical resection at Fujian Medical University Union Hospital (n = 862) and Sun Yat‐sen University Cancer Center (n = 311) with at least 5 years of follow‐up were selected as the training set. RPA was used to develop a modified staging system. Patients from the Surveillance, Epidemiology, and End Results database (n = 1415) were selected as the validation set. Results The 5‐year overall survival (OS) rates of patients with 8th AJCC‐TNM stage IA‐IIIA in the training set were IA 95.2%, IB 87.1%, IIA 78.3%, IIB 75.8%, and IIIA 72.6%. Multivariate analysis (MVA) showed that larger tumor size, elder age, and deeper depth of invasion were independent predictors for OS in patients with node‐negative GC (all P < 0.05). Patients were reclassified into RPA I, RPA II, RPA III, and RPA IV stages based on RPA; the 5‐year OS rates were 96.1%, 87.2%, 81.0%, and 64.3%, respectively, with significant difference (P < 0.05). Two‐step MVA showed that the RPA staging system was an independent predictor of OS (P < 0.05). Compared with the 8th AJCC‐TNM staging system, the RPA staging system had a smaller AIC value (2544.9 vs 2576.2), higher χ2 score (104.2 vs 69.6) and higher Harrell's C‐index (0.697 vs 0.669, P = 0.007). The similar results were found in the validation set. Conclusions A new prognostic predictive system based on RPA was successfully developed and validated, which may be suggested for staging node‐negative GC in future.https://doi.org/10.1002/cam4.2170gastric cancernode‐negativerecursive partitioning analysisTNM staging system
spellingShingle Jian‐Xian Lin
Zu‐Kai Wang
Wei Wang
Jian‐Wei Xie
Jia‐Bin Wang
Jun Lu
Qi‐Yue Chen
Long‐Long Cao
Mi Lin
Ru‐Hong Tu
Chao‐Hui Zheng
Ping Li
Zhi‐Wei Zhou
Chang‐Ming Huang
Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional study
Cancer Medicine
gastric cancer
node‐negative
recursive partitioning analysis
TNM staging system
title Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional study
title_full Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional study
title_fullStr Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional study
title_full_unstemmed Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional study
title_short Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional study
title_sort development and validation of a new staging system for node negative gastric cancer based on recursive partitioning analysis an international multi institutional study
topic gastric cancer
node‐negative
recursive partitioning analysis
TNM staging system
url https://doi.org/10.1002/cam4.2170
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