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Establishment and validation of systematic prognostic nomograms in patients over 60 years of age with osteosarcoma: A multicenter external verification study

BACKGROUND: The aim of this study was to develop and validate systematic nomograms to predict cancer specific survival (CSS) and overall survival (OS) in osteosarcoma patients aged over 60 years. METHODS: We used data from the Surveillance, Epidemiology, and End Results (SEER) database and identifie...

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Autores principales: Shao, Zhuce, Li, JiaChen, Liu, Ze, Bi, Shuxiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10166929/
https://www.ncbi.nlm.nih.gov/pubmed/36992547
http://dx.doi.org/10.1002/cam4.5736
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author Shao, Zhuce
Li, JiaChen
Liu, Ze
Bi, Shuxiong
author_facet Shao, Zhuce
Li, JiaChen
Liu, Ze
Bi, Shuxiong
author_sort Shao, Zhuce
collection PubMed
description BACKGROUND: The aim of this study was to develop and validate systematic nomograms to predict cancer specific survival (CSS) and overall survival (OS) in osteosarcoma patients aged over 60 years. METHODS: We used data from the Surveillance, Epidemiology, and End Results (SEER) database and identified 982 patients with osteosarcoma over 60 years of age diagnosed between 2004 and 2015. Overall, 306 patients met the requirements for the training group. Next, we enrolled 56 patients who met the study requirements from multiple medical centers as the external validation group to validate and analyze our model. We collected all available variables and finally selected eight that were statistically associated with CSS and OS through Cox regression analysis. Integrating the identified variables, we constructed 3‐ and 5‐year OS and CSS nomograms, respectively, which were further evaluated by calculating the C‐index. A calibration curve was used to evaluate the accuracy of the model. Receiver operating characteristic (ROC) curves measured the predictive capacity of the nomograms. The Kaplan–Meier analysis was used for all patient‐based variables to explore the influence of various factors on patient survival. Finally, a decision curve analysis (DCA) curve was used to analyze whether our model would be suitable for application in clinical practice. RESULTS: Cox regression analysis of clinical variables identified age, sex, marital status, tumor grade, tumor laterality, tumor size, M‐stage, and surgical treatment as prognostic factors. Nomograms showed good predictive capacity for OS and CSS. We calculated that the C‐index of the OS nomogram of the training population was 0.827 (95% CI 0.778–0.876), while that of the CSS nomogram was 0.722 (95% CI 0.665–0.779). The C‐index of the OS nomogram evaluated on the external validation population was 0.716 (95% CI 0.575–0.857), while that of the CSS nomogram was 0.642 (95% CI 0.50–0.788). Furthermore, the calibration curve of our prediction models indicated the nomograms could accurately predict patient outcome. CONCLUSIONS: The constructed nomogram is a useful tool for accurately predicting OS and CSS at 3 and 5 years for patients over 60 years of age with osteosarcoma and can assist clinicians in making appropriate decisions in practice.
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spelling pubmed-101669292023-05-10 Establishment and validation of systematic prognostic nomograms in patients over 60 years of age with osteosarcoma: A multicenter external verification study Shao, Zhuce Li, JiaChen Liu, Ze Bi, Shuxiong Cancer Med RESEARCH ARTICLES BACKGROUND: The aim of this study was to develop and validate systematic nomograms to predict cancer specific survival (CSS) and overall survival (OS) in osteosarcoma patients aged over 60 years. METHODS: We used data from the Surveillance, Epidemiology, and End Results (SEER) database and identified 982 patients with osteosarcoma over 60 years of age diagnosed between 2004 and 2015. Overall, 306 patients met the requirements for the training group. Next, we enrolled 56 patients who met the study requirements from multiple medical centers as the external validation group to validate and analyze our model. We collected all available variables and finally selected eight that were statistically associated with CSS and OS through Cox regression analysis. Integrating the identified variables, we constructed 3‐ and 5‐year OS and CSS nomograms, respectively, which were further evaluated by calculating the C‐index. A calibration curve was used to evaluate the accuracy of the model. Receiver operating characteristic (ROC) curves measured the predictive capacity of the nomograms. The Kaplan–Meier analysis was used for all patient‐based variables to explore the influence of various factors on patient survival. Finally, a decision curve analysis (DCA) curve was used to analyze whether our model would be suitable for application in clinical practice. RESULTS: Cox regression analysis of clinical variables identified age, sex, marital status, tumor grade, tumor laterality, tumor size, M‐stage, and surgical treatment as prognostic factors. Nomograms showed good predictive capacity for OS and CSS. We calculated that the C‐index of the OS nomogram of the training population was 0.827 (95% CI 0.778–0.876), while that of the CSS nomogram was 0.722 (95% CI 0.665–0.779). The C‐index of the OS nomogram evaluated on the external validation population was 0.716 (95% CI 0.575–0.857), while that of the CSS nomogram was 0.642 (95% CI 0.50–0.788). Furthermore, the calibration curve of our prediction models indicated the nomograms could accurately predict patient outcome. CONCLUSIONS: The constructed nomogram is a useful tool for accurately predicting OS and CSS at 3 and 5 years for patients over 60 years of age with osteosarcoma and can assist clinicians in making appropriate decisions in practice. John Wiley and Sons Inc. 2023-03-29 /pmc/articles/PMC10166929/ /pubmed/36992547 http://dx.doi.org/10.1002/cam4.5736 Text en © 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle RESEARCH ARTICLES
Shao, Zhuce
Li, JiaChen
Liu, Ze
Bi, Shuxiong
Establishment and validation of systematic prognostic nomograms in patients over 60 years of age with osteosarcoma: A multicenter external verification study
title Establishment and validation of systematic prognostic nomograms in patients over 60 years of age with osteosarcoma: A multicenter external verification study
title_full Establishment and validation of systematic prognostic nomograms in patients over 60 years of age with osteosarcoma: A multicenter external verification study
title_fullStr Establishment and validation of systematic prognostic nomograms in patients over 60 years of age with osteosarcoma: A multicenter external verification study
title_full_unstemmed Establishment and validation of systematic prognostic nomograms in patients over 60 years of age with osteosarcoma: A multicenter external verification study
title_short Establishment and validation of systematic prognostic nomograms in patients over 60 years of age with osteosarcoma: A multicenter external verification study
title_sort establishment and validation of systematic prognostic nomograms in patients over 60 years of age with osteosarcoma: a multicenter external verification study
topic RESEARCH ARTICLES
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10166929/
https://www.ncbi.nlm.nih.gov/pubmed/36992547
http://dx.doi.org/10.1002/cam4.5736
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