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A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer
BACKGROUND: The study was intended to establish predictive nomogram models for predicting total early mortality (the probability of surviving less than or equal to 3 months) and cancer-specific early mortality in patients with stage IV gastric cancer. This was the first study to establish prognostic...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Scientific Literature, Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453749/ https://www.ncbi.nlm.nih.gov/pubmed/32813682 http://dx.doi.org/10.12659/MSM.923931 |
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author | Feng, Yuqian Guo, Kaibo Jin, Huimin Xiang, Yuying Zhang, Yiting Ruan, Shanming |
author_facet | Feng, Yuqian Guo, Kaibo Jin, Huimin Xiang, Yuying Zhang, Yiting Ruan, Shanming |
author_sort | Feng, Yuqian |
collection | PubMed |
description | BACKGROUND: The study was intended to establish predictive nomogram models for predicting total early mortality (the probability of surviving less than or equal to 3 months) and cancer-specific early mortality in patients with stage IV gastric cancer. This was the first study to establish prognostic survival in patients with stage IV gastric cancer. MATERIAL/METHODS: Patients from the SEER database were identified using inclusion and exclusion criteria. Their clinical characteristics were statistically analyzed. The Kaplan-Meier method and the log-rank test were used to compare the influences of different factors on survival time. Logistic regression models were conducted to explore the correlative factors of early mortality. A nomogram was established based on factors significant in the logistic regression model and an internal validation was performed. RESULTS: Of the 11,036 eligible patients included in the study, 4932 (44.7%) patients resulted in total early death (42.6% died of the cancer and 2.1% died of other reasons). Larger tumor size, poor differentiation, and liver metastasis were positively related to cancer-specific early mortality. Surgery was negatively related to total early mortality and cancer-specific early mortality, while cardia was only negatively associated with total early death. Predictive nomogram models for total early mortality and cancer-specific early mortality have been validated internally. The areas under the receiver operating characteristics curve were 73.5%, and 68.0%, respectively, and the decision curve analysis also proved the value of the models. CONCLUSIONS: The nomogram models proved to be a suitable tool for predicting the early mortality in stage IV gastric cancer. |
format | Online Article Text |
id | pubmed-7453749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | International Scientific Literature, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74537492020-09-03 A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer Feng, Yuqian Guo, Kaibo Jin, Huimin Xiang, Yuying Zhang, Yiting Ruan, Shanming Med Sci Monit Database Analysis BACKGROUND: The study was intended to establish predictive nomogram models for predicting total early mortality (the probability of surviving less than or equal to 3 months) and cancer-specific early mortality in patients with stage IV gastric cancer. This was the first study to establish prognostic survival in patients with stage IV gastric cancer. MATERIAL/METHODS: Patients from the SEER database were identified using inclusion and exclusion criteria. Their clinical characteristics were statistically analyzed. The Kaplan-Meier method and the log-rank test were used to compare the influences of different factors on survival time. Logistic regression models were conducted to explore the correlative factors of early mortality. A nomogram was established based on factors significant in the logistic regression model and an internal validation was performed. RESULTS: Of the 11,036 eligible patients included in the study, 4932 (44.7%) patients resulted in total early death (42.6% died of the cancer and 2.1% died of other reasons). Larger tumor size, poor differentiation, and liver metastasis were positively related to cancer-specific early mortality. Surgery was negatively related to total early mortality and cancer-specific early mortality, while cardia was only negatively associated with total early death. Predictive nomogram models for total early mortality and cancer-specific early mortality have been validated internally. The areas under the receiver operating characteristics curve were 73.5%, and 68.0%, respectively, and the decision curve analysis also proved the value of the models. CONCLUSIONS: The nomogram models proved to be a suitable tool for predicting the early mortality in stage IV gastric cancer. International Scientific Literature, Inc. 2020-08-19 /pmc/articles/PMC7453749/ /pubmed/32813682 http://dx.doi.org/10.12659/MSM.923931 Text en © Med Sci Monit, 2020 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) ) |
spellingShingle | Database Analysis Feng, Yuqian Guo, Kaibo Jin, Huimin Xiang, Yuying Zhang, Yiting Ruan, Shanming A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer |
title | A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer |
title_full | A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer |
title_fullStr | A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer |
title_full_unstemmed | A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer |
title_short | A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer |
title_sort | predictive nomogram for early mortality in stage iv gastric cancer |
topic | Database Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453749/ https://www.ncbi.nlm.nih.gov/pubmed/32813682 http://dx.doi.org/10.12659/MSM.923931 |
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