A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma
Background: The aim of our study was to develop a nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRC). Methods: GSRC patients from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Result...
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Online Access: | https://doi.org/10.1177/15330338211027912 |
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doaj-309e183eeb0d482eb323898976e6f6892021-06-30T22:34:59ZengSAGE PublishingTechnology in Cancer Research & Treatment1533-03382021-06-012010.1177/15330338211027912A Prognostic Model for Patients With Gastric Signet Ring Cell CarcinomaQinping Guo MD0Yinquan Wang MD1Jie An MD2Siben Wang MD3Xiushan Dong MD4Haoliang Zhao PhD5 Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, China Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, China Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, China Department of Thoracic Surgery, Huainan First People’s Hospital, Huainan, Anhui Province, China Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, China Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, ChinaBackground: The aim of our study was to develop a nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRC). Methods: GSRC patients from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and randomly assigned to the training and validation sets. Multivariate Cox regression analyses screened for OS and CSS independent risk factors and nomograms were constructed. Results: A total of 7,149 eligible GSRC patients were identified, including 4,766 in the training set and 2,383 in the validation set. Multivariate Cox regression analysis showed that gender, marital status, race, AJCC stage, TNM stage, surgery and chemotherapy were independent risk factors for both OS and CSS. Based on the results of the multivariate Cox regression analysis, prognostic nomograms were constructed for OS and CSS. In the training set, the C-index was 0.754 (95% CI = 0.746-0.762) for the OS nomogram and 0.762 (95% CI: 0.753-0.771) for the CSS nomogram. In the internal validation, the C-index for the OS nomogram was 0.758 (95% CI: 0.746-0.770), while the C-index for the CSS nomogram was 0.762 (95% CI: 0.749-0.775). Compared with TNM stage and SEER stage, the nomogram had better predictive ability. In addition, the calibration curves also showed good consistency between the predicted and actual 3-year and 5-year OS and CSS. Conclusion: The nomogram can effectively predict OS and CSS in patients with GSRC, which may help clinicians to personalize prognostic assessments and clinical decisions.https://doi.org/10.1177/15330338211027912 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qinping Guo MD Yinquan Wang MD Jie An MD Siben Wang MD Xiushan Dong MD Haoliang Zhao PhD |
spellingShingle |
Qinping Guo MD Yinquan Wang MD Jie An MD Siben Wang MD Xiushan Dong MD Haoliang Zhao PhD A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma Technology in Cancer Research & Treatment |
author_facet |
Qinping Guo MD Yinquan Wang MD Jie An MD Siben Wang MD Xiushan Dong MD Haoliang Zhao PhD |
author_sort |
Qinping Guo MD |
title |
A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma |
title_short |
A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma |
title_full |
A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma |
title_fullStr |
A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma |
title_full_unstemmed |
A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma |
title_sort |
prognostic model for patients with gastric signet ring cell carcinoma |
publisher |
SAGE Publishing |
series |
Technology in Cancer Research & Treatment |
issn |
1533-0338 |
publishDate |
2021-06-01 |
description |
Background: The aim of our study was to develop a nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRC). Methods: GSRC patients from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and randomly assigned to the training and validation sets. Multivariate Cox regression analyses screened for OS and CSS independent risk factors and nomograms were constructed. Results: A total of 7,149 eligible GSRC patients were identified, including 4,766 in the training set and 2,383 in the validation set. Multivariate Cox regression analysis showed that gender, marital status, race, AJCC stage, TNM stage, surgery and chemotherapy were independent risk factors for both OS and CSS. Based on the results of the multivariate Cox regression analysis, prognostic nomograms were constructed for OS and CSS. In the training set, the C-index was 0.754 (95% CI = 0.746-0.762) for the OS nomogram and 0.762 (95% CI: 0.753-0.771) for the CSS nomogram. In the internal validation, the C-index for the OS nomogram was 0.758 (95% CI: 0.746-0.770), while the C-index for the CSS nomogram was 0.762 (95% CI: 0.749-0.775). Compared with TNM stage and SEER stage, the nomogram had better predictive ability. In addition, the calibration curves also showed good consistency between the predicted and actual 3-year and 5-year OS and CSS. Conclusion: The nomogram can effectively predict OS and CSS in patients with GSRC, which may help clinicians to personalize prognostic assessments and clinical decisions. |
url |
https://doi.org/10.1177/15330338211027912 |
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