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A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study
BACKGROUND: The purpose of this study was to investigate the significance of preoperative C-reactive protein-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in predicting overall survival (OS) of osteosarcoma, to establish a nomogram of an individu...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805258/ https://www.ncbi.nlm.nih.gov/pubmed/36585638 http://dx.doi.org/10.1186/s12885-022-10477-8 |
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author | Huang, Xianying Liu, Yongjin Liang, Weifeng Luo, Kai Qin, Yiwu Li, Feicui Xie, Tianyu Qin, Haibiao He, Juliang Wei, Qingjun |
author_facet | Huang, Xianying Liu, Yongjin Liang, Weifeng Luo, Kai Qin, Yiwu Li, Feicui Xie, Tianyu Qin, Haibiao He, Juliang Wei, Qingjun |
author_sort | Huang, Xianying |
collection | PubMed |
description | BACKGROUND: The purpose of this study was to investigate the significance of preoperative C-reactive protein-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in predicting overall survival (OS) of osteosarcoma, to establish a nomogram of an individualized prognostic prediction model for osteosarcoma. METHODS: Two hundred thirty-five patients with osteosarcoma from multiple centers were included in this study. Receiver operating characteristic (ROC) and Youden index were used to determine the optimal cutoff values for CAR, NLR, and PLR. Univariate analysis using COX proportional hazards model to identify factors associated with OS in osteosarcoma, and multivariate analysis of these factors to identify independent prognostic factors. R software (4.1.3-win) rms package was used to build a nomogram, and the concordance index (C-index) and calibration curve were used to assess model accuracy and discriminability. RESULTS: Univariate analysis revealed that the OS of osteosarcoma is significantly correlated (P < 0.05) with CAR, NLR, PLR, Enneking stage, tumor size, age, neoadjuvant chemotherapy (NACT), and high alkaline phosphatase. Multivariate analysis confirmed that CAR, NLR, Enneking stage, NACT and tumor size are independent prognostic factors for OS of osteosarcoma. The calibration curve shows that the nomogram constructed from these factors has acceptable consistency and calibration capability. CONCLUSION: Preoperative CAR and NLR were independent predictors of osteosarcoma prognosis, and the combination of nomogram model can realize individualized prognosis prediction and guide medical practice. |
format | Online Article Text |
id | pubmed-9805258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98052582023-01-01 A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study Huang, Xianying Liu, Yongjin Liang, Weifeng Luo, Kai Qin, Yiwu Li, Feicui Xie, Tianyu Qin, Haibiao He, Juliang Wei, Qingjun BMC Cancer Research BACKGROUND: The purpose of this study was to investigate the significance of preoperative C-reactive protein-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in predicting overall survival (OS) of osteosarcoma, to establish a nomogram of an individualized prognostic prediction model for osteosarcoma. METHODS: Two hundred thirty-five patients with osteosarcoma from multiple centers were included in this study. Receiver operating characteristic (ROC) and Youden index were used to determine the optimal cutoff values for CAR, NLR, and PLR. Univariate analysis using COX proportional hazards model to identify factors associated with OS in osteosarcoma, and multivariate analysis of these factors to identify independent prognostic factors. R software (4.1.3-win) rms package was used to build a nomogram, and the concordance index (C-index) and calibration curve were used to assess model accuracy and discriminability. RESULTS: Univariate analysis revealed that the OS of osteosarcoma is significantly correlated (P < 0.05) with CAR, NLR, PLR, Enneking stage, tumor size, age, neoadjuvant chemotherapy (NACT), and high alkaline phosphatase. Multivariate analysis confirmed that CAR, NLR, Enneking stage, NACT and tumor size are independent prognostic factors for OS of osteosarcoma. The calibration curve shows that the nomogram constructed from these factors has acceptable consistency and calibration capability. CONCLUSION: Preoperative CAR and NLR were independent predictors of osteosarcoma prognosis, and the combination of nomogram model can realize individualized prognosis prediction and guide medical practice. BioMed Central 2022-12-30 /pmc/articles/PMC9805258/ /pubmed/36585638 http://dx.doi.org/10.1186/s12885-022-10477-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Huang, Xianying Liu, Yongjin Liang, Weifeng Luo, Kai Qin, Yiwu Li, Feicui Xie, Tianyu Qin, Haibiao He, Juliang Wei, Qingjun A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study |
title | A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study |
title_full | A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study |
title_fullStr | A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study |
title_full_unstemmed | A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study |
title_short | A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study |
title_sort | new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805258/ https://www.ncbi.nlm.nih.gov/pubmed/36585638 http://dx.doi.org/10.1186/s12885-022-10477-8 |
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