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Novel staging for gastric neuroendocrine neoplasms by incorporating the WHO grading into the TNM staging system

BACKGROUND: The 8th tumor‐node‐metastasis (TNM) classification of the American Joint Committee on Cancer (AJCC) can be used to estimate the prognosis of gastric neuroendocrine tumor (gNET) and gastric neuroendocrine carcinoma (gNEC) patients but not gastric neuroendocrine neoplasms (gNENs). METHODS:...

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Autores principales: Zhang, Rihong, Guo, Yu, Wang, Youliang, Hu, Li, Fang, Cheng, Yang, Yujie, Yang, Xianqi, Chen, Luohai, Chen, Jie, Wang, Wei, Sun, Xiaowei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067116/
https://www.ncbi.nlm.nih.gov/pubmed/36394081
http://dx.doi.org/10.1002/cam4.5437
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author Zhang, Rihong
Guo, Yu
Wang, Youliang
Hu, Li
Fang, Cheng
Yang, Yujie
Yang, Xianqi
Chen, Luohai
Chen, Jie
Wang, Wei
Sun, Xiaowei
author_facet Zhang, Rihong
Guo, Yu
Wang, Youliang
Hu, Li
Fang, Cheng
Yang, Yujie
Yang, Xianqi
Chen, Luohai
Chen, Jie
Wang, Wei
Sun, Xiaowei
author_sort Zhang, Rihong
collection PubMed
description BACKGROUND: The 8th tumor‐node‐metastasis (TNM) classification of the American Joint Committee on Cancer (AJCC) can be used to estimate the prognosis of gastric neuroendocrine tumor (gNET) and gastric neuroendocrine carcinoma (gNEC) patients but not gastric neuroendocrine neoplasms (gNENs). METHODS: First, in the SEER (training) dataset, a TNMG system was built by combining the WHO G grade (G1‐4; NEC grouped into G4) with the 8th AJCC T (T1‐4), N (N0‐1), and M (M0‐1) stage, which was then validated in a Chinese (validation) cohort. RESULTS: In all, 2245 gNENs cases from the training dataset and 280 cases from the validation dataset were eligible. The T stage, M stage, and G grade were independent prognostic factors for OS in both datasets (all p < 0.05). The TNMG staging system demonstrated better C‐index for predicting OS than the 8th AJCC TNM staging system in both the training (0.87, 95%CI: 0.86–0.88 vs. 0.79, 95%CI: 0.77–0.81) and validation (0.77, 95%CI: 0.73–0.80 vs. 0.75, 95%CI: 0.71–0.79) datasets. The AUC of the 3‐year OS for the TNMG staging system was 0.936 and 0.817 in the SEER and validation dataset, respectively; higher than those of the 8th AJCC system (vs. 0.843 and 0.779, respectively). DCA revealed that compared with the 8th AJCC TNM staging system, the TNMG staging system demonstrated superior net prognostic benefit in both the training and validation datasets. CONCLUSIONS: The proposed TNMG staging system could more accurately predict the 3‐ and 5‐year OS rate of gNENs patients than the 8th AJCC TNM staging system.
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spelling pubmed-100671162023-04-03 Novel staging for gastric neuroendocrine neoplasms by incorporating the WHO grading into the TNM staging system Zhang, Rihong Guo, Yu Wang, Youliang Hu, Li Fang, Cheng Yang, Yujie Yang, Xianqi Chen, Luohai Chen, Jie Wang, Wei Sun, Xiaowei Cancer Med RESEARCH ARTICLES BACKGROUND: The 8th tumor‐node‐metastasis (TNM) classification of the American Joint Committee on Cancer (AJCC) can be used to estimate the prognosis of gastric neuroendocrine tumor (gNET) and gastric neuroendocrine carcinoma (gNEC) patients but not gastric neuroendocrine neoplasms (gNENs). METHODS: First, in the SEER (training) dataset, a TNMG system was built by combining the WHO G grade (G1‐4; NEC grouped into G4) with the 8th AJCC T (T1‐4), N (N0‐1), and M (M0‐1) stage, which was then validated in a Chinese (validation) cohort. RESULTS: In all, 2245 gNENs cases from the training dataset and 280 cases from the validation dataset were eligible. The T stage, M stage, and G grade were independent prognostic factors for OS in both datasets (all p < 0.05). The TNMG staging system demonstrated better C‐index for predicting OS than the 8th AJCC TNM staging system in both the training (0.87, 95%CI: 0.86–0.88 vs. 0.79, 95%CI: 0.77–0.81) and validation (0.77, 95%CI: 0.73–0.80 vs. 0.75, 95%CI: 0.71–0.79) datasets. The AUC of the 3‐year OS for the TNMG staging system was 0.936 and 0.817 in the SEER and validation dataset, respectively; higher than those of the 8th AJCC system (vs. 0.843 and 0.779, respectively). DCA revealed that compared with the 8th AJCC TNM staging system, the TNMG staging system demonstrated superior net prognostic benefit in both the training and validation datasets. CONCLUSIONS: The proposed TNMG staging system could more accurately predict the 3‐ and 5‐year OS rate of gNENs patients than the 8th AJCC TNM staging system. John Wiley and Sons Inc. 2022-11-16 /pmc/articles/PMC10067116/ /pubmed/36394081 http://dx.doi.org/10.1002/cam4.5437 Text en © 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle RESEARCH ARTICLES
Zhang, Rihong
Guo, Yu
Wang, Youliang
Hu, Li
Fang, Cheng
Yang, Yujie
Yang, Xianqi
Chen, Luohai
Chen, Jie
Wang, Wei
Sun, Xiaowei
Novel staging for gastric neuroendocrine neoplasms by incorporating the WHO grading into the TNM staging system
title Novel staging for gastric neuroendocrine neoplasms by incorporating the WHO grading into the TNM staging system
title_full Novel staging for gastric neuroendocrine neoplasms by incorporating the WHO grading into the TNM staging system
title_fullStr Novel staging for gastric neuroendocrine neoplasms by incorporating the WHO grading into the TNM staging system
title_full_unstemmed Novel staging for gastric neuroendocrine neoplasms by incorporating the WHO grading into the TNM staging system
title_short Novel staging for gastric neuroendocrine neoplasms by incorporating the WHO grading into the TNM staging system
title_sort novel staging for gastric neuroendocrine neoplasms by incorporating the who grading into the tnm staging system
topic RESEARCH ARTICLES
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067116/
https://www.ncbi.nlm.nih.gov/pubmed/36394081
http://dx.doi.org/10.1002/cam4.5437
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