Cargando…

A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection

BACKGROUND: Though the survival benefit of primary tumor operation for patients with signet ring cell carcinoma of the stomach is known, the specific characteristics of those patients who would profit from the operation are yet to be determined. To this end, a predictive model was developed to ident...

Descripción completa

Detalles Bibliográficos
Autores principales: Hu, Biao, Zou, Run-Pu, Gan, Yin-Wen, Zhu, Yi-Hao, Ren, Si-Min, Hou, Wei-Zhong, Xie, Zhi-Xin, Wang, Ru, Yang, Wen-Ting, Lin, Peng-Ji, Feng, Jun-Tao, Gao, Zi-Min, Guo, Xu-Guang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8925095/
https://www.ncbi.nlm.nih.gov/pubmed/35296343
http://dx.doi.org/10.1186/s12957-022-02544-y
_version_ 1784669995670700032
author Hu, Biao
Zou, Run-Pu
Gan, Yin-Wen
Zhu, Yi-Hao
Ren, Si-Min
Hou, Wei-Zhong
Xie, Zhi-Xin
Wang, Ru
Yang, Wen-Ting
Lin, Peng-Ji
Feng, Jun-Tao
Gao, Zi-Min
Guo, Xu-Guang
author_facet Hu, Biao
Zou, Run-Pu
Gan, Yin-Wen
Zhu, Yi-Hao
Ren, Si-Min
Hou, Wei-Zhong
Xie, Zhi-Xin
Wang, Ru
Yang, Wen-Ting
Lin, Peng-Ji
Feng, Jun-Tao
Gao, Zi-Min
Guo, Xu-Guang
author_sort Hu, Biao
collection PubMed
description BACKGROUND: Though the survival benefit of primary tumor operation for patients with signet ring cell carcinoma of the stomach is known, the specific characteristics of those patients who would profit from the operation are yet to be determined. To this end, a predictive model was developed to identify the conjecture that the survival profit from primary tumor operation would only be obtained by patients. METHOD: The clinical data of the patients with signet ring cell carcinoma of the stomach were obtained from the Surveillance, Epidemiology, and End Results database, and then divided into operation and no-operation groups based on whether the patients underwent the primary tumor operation. To remove the confounding factors, propensity score matching was employed, and it was hypothesized that the patients who had been operated on and lived a longer life than the median cancer-specific survival time of those who hadn’t must have profited from the surgery. To discuss the independent factors of cancer-specific survival time in the beneficial group and the non-beneficial group, the Cox model was used, and based on the various vital predictive factors, a nomogram was drawn using logistic regression. RESULT: The number of eligible patients was 12,484, with 43.9% (5483) of them having received surgery. After employing propensity score matching, the cancer-specific survival time of the operation group was found to be apparently longer (median: 21 vs. 5 months; p < 0.001) than the no-operation group. In the operation group, 4757 (86.7%) of the patients lived longer than five months (beneficial group). The six indexes (beneficial and non-beneficial group) included gender, age, Tumor Node Metastasis stage, histologic type, differentiation grade, and tumor position, and were used as predictors to draw the nomogram. The nomogram was used to divide the patients who had taken operations into two groups: the beneficial operation group and the non-beneficial operation group. The beneficial operation group, it was found, survived longer than the non-beneficial operation group (median cancer-specific survival time: 28 vs. 3 months, p < 0.001). Moreover, there was we could tell little difference in survival between the two groups (median cancer-specific survival time: 3 vs. 5 months). CONCLUSIONS: The predictive model created to select suitable candidates for surgical treatment from patients with signet ring carcinoma of the stomach could be adopted to identify certain patients benefiting from the primary tumor operation.
format Online
Article
Text
id pubmed-8925095
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-89250952022-03-23 A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection Hu, Biao Zou, Run-Pu Gan, Yin-Wen Zhu, Yi-Hao Ren, Si-Min Hou, Wei-Zhong Xie, Zhi-Xin Wang, Ru Yang, Wen-Ting Lin, Peng-Ji Feng, Jun-Tao Gao, Zi-Min Guo, Xu-Guang World J Surg Oncol Research BACKGROUND: Though the survival benefit of primary tumor operation for patients with signet ring cell carcinoma of the stomach is known, the specific characteristics of those patients who would profit from the operation are yet to be determined. To this end, a predictive model was developed to identify the conjecture that the survival profit from primary tumor operation would only be obtained by patients. METHOD: The clinical data of the patients with signet ring cell carcinoma of the stomach were obtained from the Surveillance, Epidemiology, and End Results database, and then divided into operation and no-operation groups based on whether the patients underwent the primary tumor operation. To remove the confounding factors, propensity score matching was employed, and it was hypothesized that the patients who had been operated on and lived a longer life than the median cancer-specific survival time of those who hadn’t must have profited from the surgery. To discuss the independent factors of cancer-specific survival time in the beneficial group and the non-beneficial group, the Cox model was used, and based on the various vital predictive factors, a nomogram was drawn using logistic regression. RESULT: The number of eligible patients was 12,484, with 43.9% (5483) of them having received surgery. After employing propensity score matching, the cancer-specific survival time of the operation group was found to be apparently longer (median: 21 vs. 5 months; p < 0.001) than the no-operation group. In the operation group, 4757 (86.7%) of the patients lived longer than five months (beneficial group). The six indexes (beneficial and non-beneficial group) included gender, age, Tumor Node Metastasis stage, histologic type, differentiation grade, and tumor position, and were used as predictors to draw the nomogram. The nomogram was used to divide the patients who had taken operations into two groups: the beneficial operation group and the non-beneficial operation group. The beneficial operation group, it was found, survived longer than the non-beneficial operation group (median cancer-specific survival time: 28 vs. 3 months, p < 0.001). Moreover, there was we could tell little difference in survival between the two groups (median cancer-specific survival time: 3 vs. 5 months). CONCLUSIONS: The predictive model created to select suitable candidates for surgical treatment from patients with signet ring carcinoma of the stomach could be adopted to identify certain patients benefiting from the primary tumor operation. BioMed Central 2022-03-16 /pmc/articles/PMC8925095/ /pubmed/35296343 http://dx.doi.org/10.1186/s12957-022-02544-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Hu, Biao
Zou, Run-Pu
Gan, Yin-Wen
Zhu, Yi-Hao
Ren, Si-Min
Hou, Wei-Zhong
Xie, Zhi-Xin
Wang, Ru
Yang, Wen-Ting
Lin, Peng-Ji
Feng, Jun-Tao
Gao, Zi-Min
Guo, Xu-Guang
A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection
title A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection
title_full A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection
title_fullStr A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection
title_full_unstemmed A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection
title_short A population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection
title_sort population-based predictive model to identify patients with signet ring cell carcinoma of the stomach who are most suitable for primary tumor resection
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8925095/
https://www.ncbi.nlm.nih.gov/pubmed/35296343
http://dx.doi.org/10.1186/s12957-022-02544-y
work_keys_str_mv AT hubiao apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT zourunpu apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT ganyinwen apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT zhuyihao apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT rensimin apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT houweizhong apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT xiezhixin apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT wangru apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT yangwenting apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT linpengji apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT fengjuntao apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT gaozimin apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT guoxuguang apopulationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT hubiao populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT zourunpu populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT ganyinwen populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT zhuyihao populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT rensimin populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT houweizhong populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT xiezhixin populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT wangru populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT yangwenting populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT linpengji populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT fengjuntao populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT gaozimin populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection
AT guoxuguang populationbasedpredictivemodeltoidentifypatientswithsignetringcellcarcinomaofthestomachwhoaremostsuitableforprimarytumorresection