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Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study
BACKGROUND: Gastric signet ring cell carcinoma (GSRCC) is a rare disease associated with poor prognosis. A prognostic nomogram was developed and validated in this study to assess GSRCC patients’ overall survival (OS). METHODS: Patients diagnosed with GSRCC from the Surveillance, Epidemiology, and En...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7982806/ https://www.ncbi.nlm.nih.gov/pubmed/33763350 http://dx.doi.org/10.3389/fonc.2021.603031 |
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author | Zhang, Shuairan Liu, Yang Jiao, Zihan Li, Zenan Wang, Jin Li, Ce Qu, Xiujuan Xu, Ling |
author_facet | Zhang, Shuairan Liu, Yang Jiao, Zihan Li, Zenan Wang, Jin Li, Ce Qu, Xiujuan Xu, Ling |
author_sort | Zhang, Shuairan |
collection | PubMed |
description | BACKGROUND: Gastric signet ring cell carcinoma (GSRCC) is a rare disease associated with poor prognosis. A prognostic nomogram was developed and validated in this study to assess GSRCC patients’ overall survival (OS). METHODS: Patients diagnosed with GSRCC from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2016) and the First Hospital of China Medical University (CMU1h) were enrolled in this retrospective cohort study. Univariate and multivariate COX analysis was used to determine independent prognostic factors to construct the prognostic nomogram. Predictions were evaluated by the C-index and calibration curve. In addition, the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and Kaplan-Meier analysis were employed to assess the clinical utility of the survival prediction model. RESULTS: Patients were classified into two cohorts. We randomly divided patients in the SEER database and CMU1h cohort into a training group (n=3068, 80%) and a validation group (n=764, 20%). Age, race, T stage, N stage, M stage, therapy, and tumor size were significantly associated with the prognosis of GSRCC patients. On this basis, a nomogram was constructed, with a C-index in the training and the validation cohorts at 0.772 (95% CI: 0.762–0.782) and 0.774 (95% CI: 0.752–0.796), respectively. The accuracy of the generated nomogram was verified through calibration plots. Similarly, compared with the traditional AJCC staging system, the results of the area under curve (AUC) calculated by ROC, DCA, and Kaplan-Meier curves, demonstrated a good predictive value of the constructed nomogram, compared to the traditional AJCC staging system. CONCLUSION: In the present study, seven independent prognostic factors of GSRCC were screened out. The established nomogram models based on seven variables provided a visualization of each prognostic factor’s risk and assisted clinicians in predicting the 1-, 3-, and 5-year OS of GSRCC. |
format | Online Article Text |
id | pubmed-7982806 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79828062021-03-23 Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study Zhang, Shuairan Liu, Yang Jiao, Zihan Li, Zenan Wang, Jin Li, Ce Qu, Xiujuan Xu, Ling Front Oncol Oncology BACKGROUND: Gastric signet ring cell carcinoma (GSRCC) is a rare disease associated with poor prognosis. A prognostic nomogram was developed and validated in this study to assess GSRCC patients’ overall survival (OS). METHODS: Patients diagnosed with GSRCC from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2016) and the First Hospital of China Medical University (CMU1h) were enrolled in this retrospective cohort study. Univariate and multivariate COX analysis was used to determine independent prognostic factors to construct the prognostic nomogram. Predictions were evaluated by the C-index and calibration curve. In addition, the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and Kaplan-Meier analysis were employed to assess the clinical utility of the survival prediction model. RESULTS: Patients were classified into two cohorts. We randomly divided patients in the SEER database and CMU1h cohort into a training group (n=3068, 80%) and a validation group (n=764, 20%). Age, race, T stage, N stage, M stage, therapy, and tumor size were significantly associated with the prognosis of GSRCC patients. On this basis, a nomogram was constructed, with a C-index in the training and the validation cohorts at 0.772 (95% CI: 0.762–0.782) and 0.774 (95% CI: 0.752–0.796), respectively. The accuracy of the generated nomogram was verified through calibration plots. Similarly, compared with the traditional AJCC staging system, the results of the area under curve (AUC) calculated by ROC, DCA, and Kaplan-Meier curves, demonstrated a good predictive value of the constructed nomogram, compared to the traditional AJCC staging system. CONCLUSION: In the present study, seven independent prognostic factors of GSRCC were screened out. The established nomogram models based on seven variables provided a visualization of each prognostic factor’s risk and assisted clinicians in predicting the 1-, 3-, and 5-year OS of GSRCC. Frontiers Media S.A. 2021-03-05 /pmc/articles/PMC7982806/ /pubmed/33763350 http://dx.doi.org/10.3389/fonc.2021.603031 Text en Copyright © 2021 Zhang, Liu, Jiao, Li, Wang, Li, Qu and Xu http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Zhang, Shuairan Liu, Yang Jiao, Zihan Li, Zenan Wang, Jin Li, Ce Qu, Xiujuan Xu, Ling Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study |
title | Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study |
title_full | Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study |
title_fullStr | Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study |
title_full_unstemmed | Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study |
title_short | Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study |
title_sort | development and validation of a prognostic nomogram for gastric signet ring cell carcinoma: a multicenter population-based study |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7982806/ https://www.ncbi.nlm.nih.gov/pubmed/33763350 http://dx.doi.org/10.3389/fonc.2021.603031 |
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