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Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study

BACKGROUND: Signet-ring cell carcinoma (SRCC) was previously thought to have a worse prognosis than other differentiated gastric cancer (GC), however, recent studies have shown that the prognosis of SRCC is related to pathological type. We hypothesize that patients with SRCC and with different SRCC...

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Autores principales: Yang, Jia-Jia, Wang, Xiao-Yong, Ma, Rui, Chen, Mei-Hong, Zhang, Guo-Xin, Li, Xuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10324532/
https://www.ncbi.nlm.nih.gov/pubmed/37426318
http://dx.doi.org/10.3748/wjg.v29.i24.3807
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author Yang, Jia-Jia
Wang, Xiao-Yong
Ma, Rui
Chen, Mei-Hong
Zhang, Guo-Xin
Li, Xuan
author_facet Yang, Jia-Jia
Wang, Xiao-Yong
Ma, Rui
Chen, Mei-Hong
Zhang, Guo-Xin
Li, Xuan
author_sort Yang, Jia-Jia
collection PubMed
description BACKGROUND: Signet-ring cell carcinoma (SRCC) was previously thought to have a worse prognosis than other differentiated gastric cancer (GC), however, recent studies have shown that the prognosis of SRCC is related to pathological type. We hypothesize that patients with SRCC and with different SRCC pathological components have different probability of lymph node metastasis (LNM). AIM: To establish models to predict LNM in early GC (EGC), including early gastric SRCC. METHODS: Clinical data from EGC patients who had undergone gastrectomy at the First Affiliated Hospital of Nanjing Medical University from January 2012 to March 2022 were reviewed. The patients were divided into three groups based on type: Pure SRCC, mixed SRCC, and non-signet ring cell carcinoma (NSRC). The risk factors were identified through statistical tests using SPSS 23.0, R, and Em-powerStats software. RESULTS: A total of 1922 subjects with EGC were enrolled in this study, and included 249 SRCC patients and 1673 NSRC patients, while 278 of the patients (14.46%) presented with LNM. Multivariable analysis showed that gender, tumor size, depth of invasion, lymphovascular invasion, ulceration, and histological subtype were independent risk factors for LNM in EGC. Establishment and analysis using prediction models of EGC showed that the artificial neural network model was better than the logistic regression model in terms of sensitivity and accuracy (98.0% vs 58.1%, P = 0.034; 88.4% vs 86.8%, P < 0.001, respectively). Among the 249 SRCC patients, LNM was more common in mixed (35.06%) rather than in pure SRCC (8.42%, P < 0.001). The area under the ROC curve of the logistic regression model for LNM in SRCC was 0.760 (95%CI: 0.682-0.843), while the area under the operating characteristic curve of the internal validation set was 0.734 (95%CI: 0.643-0.826). The subgroups analysis of pure types showed that LNM was more common in patients with a tumor size > 2 cm (OR = 5.422, P = 0.038). CONCLUSION: A validated prediction model was developed to recognize the risk of LNM in EGC and early gastric SRCC, which can aid in pre-surgical decision making of the best method of treatment for patients.
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spelling pubmed-103245322023-07-07 Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study Yang, Jia-Jia Wang, Xiao-Yong Ma, Rui Chen, Mei-Hong Zhang, Guo-Xin Li, Xuan World J Gastroenterol Retrospective Cohort Study BACKGROUND: Signet-ring cell carcinoma (SRCC) was previously thought to have a worse prognosis than other differentiated gastric cancer (GC), however, recent studies have shown that the prognosis of SRCC is related to pathological type. We hypothesize that patients with SRCC and with different SRCC pathological components have different probability of lymph node metastasis (LNM). AIM: To establish models to predict LNM in early GC (EGC), including early gastric SRCC. METHODS: Clinical data from EGC patients who had undergone gastrectomy at the First Affiliated Hospital of Nanjing Medical University from January 2012 to March 2022 were reviewed. The patients were divided into three groups based on type: Pure SRCC, mixed SRCC, and non-signet ring cell carcinoma (NSRC). The risk factors were identified through statistical tests using SPSS 23.0, R, and Em-powerStats software. RESULTS: A total of 1922 subjects with EGC were enrolled in this study, and included 249 SRCC patients and 1673 NSRC patients, while 278 of the patients (14.46%) presented with LNM. Multivariable analysis showed that gender, tumor size, depth of invasion, lymphovascular invasion, ulceration, and histological subtype were independent risk factors for LNM in EGC. Establishment and analysis using prediction models of EGC showed that the artificial neural network model was better than the logistic regression model in terms of sensitivity and accuracy (98.0% vs 58.1%, P = 0.034; 88.4% vs 86.8%, P < 0.001, respectively). Among the 249 SRCC patients, LNM was more common in mixed (35.06%) rather than in pure SRCC (8.42%, P < 0.001). The area under the ROC curve of the logistic regression model for LNM in SRCC was 0.760 (95%CI: 0.682-0.843), while the area under the operating characteristic curve of the internal validation set was 0.734 (95%CI: 0.643-0.826). The subgroups analysis of pure types showed that LNM was more common in patients with a tumor size > 2 cm (OR = 5.422, P = 0.038). CONCLUSION: A validated prediction model was developed to recognize the risk of LNM in EGC and early gastric SRCC, which can aid in pre-surgical decision making of the best method of treatment for patients. Baishideng Publishing Group Inc 2023-06-28 2023-06-28 /pmc/articles/PMC10324532/ /pubmed/37426318 http://dx.doi.org/10.3748/wjg.v29.i24.3807 Text en ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.
spellingShingle Retrospective Cohort Study
Yang, Jia-Jia
Wang, Xiao-Yong
Ma, Rui
Chen, Mei-Hong
Zhang, Guo-Xin
Li, Xuan
Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study
title Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study
title_full Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study
title_fullStr Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study
title_full_unstemmed Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study
title_short Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study
title_sort prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: a real-world retrospective cohort study
topic Retrospective Cohort Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10324532/
https://www.ncbi.nlm.nih.gov/pubmed/37426318
http://dx.doi.org/10.3748/wjg.v29.i24.3807
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