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Prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on SEER database
OBJECTIVE: To evaluate the risk factors and construct a nomogram model for the prognosis of primary liver cancer in the elderly based on the data from the US SEER database. METHODS: The latest data of patients with primary liver cancer were extracted from the SEER database using SEER*STAT software,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9615972/ https://www.ncbi.nlm.nih.gov/pubmed/36288830 http://dx.doi.org/10.1136/bmjopen-2021-051946 |
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author | Li, Fangyuan Zheng, Ting Gu, Xuewei |
author_facet | Li, Fangyuan Zheng, Ting Gu, Xuewei |
author_sort | Li, Fangyuan |
collection | PubMed |
description | OBJECTIVE: To evaluate the risk factors and construct a nomogram model for the prognosis of primary liver cancer in the elderly based on the data from the US SEER database. METHODS: The latest data of patients with primary liver cancer were extracted from the SEER database using SEER*STAT software, and the required variables were included. The data were screened and then divided into a training cohort and a validation cohort. A nomogram model was constructed by screening the variables through univariate and multivariate Cox analysis. The C-Index, ROC and calibration curves were used for model evaluation. RESULTS: A total of 10 824 eligible cases from 2004 to 2017 were extracted, among which, 7757 cases were included in the training cohort and 3247 in the validation cohort. The C-Index of the model was 0.747 (in the training cohort) and 0.773 (in the validation cohort). The 3-year area under the curve (AUCs) of the training and the validation cohorts were 0.760 and 0.750, and the 5-year AUCs of the two cohorts were 0.761 and 0.748. The calibration curves showed an ideal calibration of the constructed model. CONCLUSIONS: The nomogram model constructed followed by Cox regression analysis showed moderate calibration and discrimination property, and can provide reference to a certain extent for furture clinical application of primary liver cancer in the elderly. |
format | Online Article Text |
id | pubmed-9615972 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-96159722022-10-29 Prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on SEER database Li, Fangyuan Zheng, Ting Gu, Xuewei BMJ Open Oncology OBJECTIVE: To evaluate the risk factors and construct a nomogram model for the prognosis of primary liver cancer in the elderly based on the data from the US SEER database. METHODS: The latest data of patients with primary liver cancer were extracted from the SEER database using SEER*STAT software, and the required variables were included. The data were screened and then divided into a training cohort and a validation cohort. A nomogram model was constructed by screening the variables through univariate and multivariate Cox analysis. The C-Index, ROC and calibration curves were used for model evaluation. RESULTS: A total of 10 824 eligible cases from 2004 to 2017 were extracted, among which, 7757 cases were included in the training cohort and 3247 in the validation cohort. The C-Index of the model was 0.747 (in the training cohort) and 0.773 (in the validation cohort). The 3-year area under the curve (AUCs) of the training and the validation cohorts were 0.760 and 0.750, and the 5-year AUCs of the two cohorts were 0.761 and 0.748. The calibration curves showed an ideal calibration of the constructed model. CONCLUSIONS: The nomogram model constructed followed by Cox regression analysis showed moderate calibration and discrimination property, and can provide reference to a certain extent for furture clinical application of primary liver cancer in the elderly. BMJ Publishing Group 2022-10-26 /pmc/articles/PMC9615972/ /pubmed/36288830 http://dx.doi.org/10.1136/bmjopen-2021-051946 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Oncology Li, Fangyuan Zheng, Ting Gu, Xuewei Prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on SEER database |
title | Prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on SEER database |
title_full | Prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on SEER database |
title_fullStr | Prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on SEER database |
title_full_unstemmed | Prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on SEER database |
title_short | Prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on SEER database |
title_sort | prognostic risk factor analysis and nomogram construction for primary liver cancer in elderly patients based on seer database |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9615972/ https://www.ncbi.nlm.nih.gov/pubmed/36288830 http://dx.doi.org/10.1136/bmjopen-2021-051946 |
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