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Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases

BACKGROUND: Nomogram can be used to accurately predict the prognosis of patients and guide treatment according to the individual situation of patients. This study is to investigate the independent prognostic factors for multi-organ metastases in gastric cancer (GC) patients, and construct and valida...

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Autores principales: Wang, Ting, Liu, Chuan, Wang, Wancong, Huang, Binglu, Yu, Rong, Huang, Mengting, Dong, Weiguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273680/
https://www.ncbi.nlm.nih.gov/pubmed/35836507
http://dx.doi.org/10.21037/tcr-21-2569
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author Wang, Ting
Liu, Chuan
Wang, Wancong
Huang, Binglu
Yu, Rong
Huang, Mengting
Dong, Weiguo
author_facet Wang, Ting
Liu, Chuan
Wang, Wancong
Huang, Binglu
Yu, Rong
Huang, Mengting
Dong, Weiguo
author_sort Wang, Ting
collection PubMed
description BACKGROUND: Nomogram can be used to accurately predict the prognosis of patients and guide treatment according to the individual situation of patients. This study is to investigate the independent prognostic factors for multi-organ metastases in gastric cancer (GC) patients, and construct and validate prognostic nomograms for overall survival (OS) and cancer-specific survival (CSS). METHODS: The clinical data of GC patients with multi-organ metastases from 2010 to 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The independent prognostic factors affecting the OS and CSS of the patients were screened using univariate and multivariate Cox’s proportional hazards model and the Fine-Gray competing risk model. Corresponding nomogram models were constructed to predict the OS and CSS of the patients. The reliability and accuracy of the prediction model were evaluated by consistency index (C-index), area under receiver operating characteristic (ROC) curve (AUC) and calibration curve. RESULTS: A total of 1,386 patients were included and randomly divided into a training group (972 cases) and a validation group (414 cases) in a 7:3 ratio. Cox proportional hazards analysis showed that age [P<0.001, hazard ratio (HR) =1.29 (1.11–1.49)], race (P=0.018, HR =0.79 (0.65–0.96)], metastases [P=0.036, HR =1.96 (1.05–3.67)], tumor size [P=0.045, HR =1.35 (1.01–1.82)], degree of differentiation [P=0.002, HR =1.99 (1.30–3.06)] and metastasis surgery (P=0.005, HR =0.52 (0.33–0.82)] were independent prognostic factors for OS in GC patients with multi-organ metastases. The Fine-Gray competing risk analysis showed that age [P=0.006, HR =1.23 (1.06–1.42)], histological type [P=0.037, HR =1.53 (1.03–2.27)], metastases [P=0.009, HR =2.02 (1.19–3.41)], tumor size [P=0.028, HR =1.33 (1.03–1.70)], degree of differentiation [P=0.009, HR =1.65 (1.13–2.40)] and metastasis surgery [P=0.001, HR =0.50 (0.32–0.76)] were independent prognostic factors for CSS in GC patients with multi-organ metastases. The above factors were used to construct nomogram models for predicting OS and CSS. Both C-index and AUC of the training group and the validation group showed that the models had an acceptable predictive performance. The calibration curve showed that the predicted and ideal curves fit well, indicating that the constructed models were well-calibrated. CONCLUSIONS: Using data from the SEER database, this study established and validated nomogram models for OS and CSS in GC patients with multi-organ metastases, to help clinicians formulate accurate and individualized treatment plans.
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spelling pubmed-92736802022-07-13 Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases Wang, Ting Liu, Chuan Wang, Wancong Huang, Binglu Yu, Rong Huang, Mengting Dong, Weiguo Transl Cancer Res Original Article BACKGROUND: Nomogram can be used to accurately predict the prognosis of patients and guide treatment according to the individual situation of patients. This study is to investigate the independent prognostic factors for multi-organ metastases in gastric cancer (GC) patients, and construct and validate prognostic nomograms for overall survival (OS) and cancer-specific survival (CSS). METHODS: The clinical data of GC patients with multi-organ metastases from 2010 to 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The independent prognostic factors affecting the OS and CSS of the patients were screened using univariate and multivariate Cox’s proportional hazards model and the Fine-Gray competing risk model. Corresponding nomogram models were constructed to predict the OS and CSS of the patients. The reliability and accuracy of the prediction model were evaluated by consistency index (C-index), area under receiver operating characteristic (ROC) curve (AUC) and calibration curve. RESULTS: A total of 1,386 patients were included and randomly divided into a training group (972 cases) and a validation group (414 cases) in a 7:3 ratio. Cox proportional hazards analysis showed that age [P<0.001, hazard ratio (HR) =1.29 (1.11–1.49)], race (P=0.018, HR =0.79 (0.65–0.96)], metastases [P=0.036, HR =1.96 (1.05–3.67)], tumor size [P=0.045, HR =1.35 (1.01–1.82)], degree of differentiation [P=0.002, HR =1.99 (1.30–3.06)] and metastasis surgery (P=0.005, HR =0.52 (0.33–0.82)] were independent prognostic factors for OS in GC patients with multi-organ metastases. The Fine-Gray competing risk analysis showed that age [P=0.006, HR =1.23 (1.06–1.42)], histological type [P=0.037, HR =1.53 (1.03–2.27)], metastases [P=0.009, HR =2.02 (1.19–3.41)], tumor size [P=0.028, HR =1.33 (1.03–1.70)], degree of differentiation [P=0.009, HR =1.65 (1.13–2.40)] and metastasis surgery [P=0.001, HR =0.50 (0.32–0.76)] were independent prognostic factors for CSS in GC patients with multi-organ metastases. The above factors were used to construct nomogram models for predicting OS and CSS. Both C-index and AUC of the training group and the validation group showed that the models had an acceptable predictive performance. The calibration curve showed that the predicted and ideal curves fit well, indicating that the constructed models were well-calibrated. CONCLUSIONS: Using data from the SEER database, this study established and validated nomogram models for OS and CSS in GC patients with multi-organ metastases, to help clinicians formulate accurate and individualized treatment plans. AME Publishing Company 2022-06 /pmc/articles/PMC9273680/ /pubmed/35836507 http://dx.doi.org/10.21037/tcr-21-2569 Text en 2022 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Wang, Ting
Liu, Chuan
Wang, Wancong
Huang, Binglu
Yu, Rong
Huang, Mengting
Dong, Weiguo
Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases
title Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases
title_full Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases
title_fullStr Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases
title_full_unstemmed Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases
title_short Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases
title_sort development and validation of a surveillance, epidemiology, and end results (seer)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273680/
https://www.ncbi.nlm.nih.gov/pubmed/35836507
http://dx.doi.org/10.21037/tcr-21-2569
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