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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.
Afiliação
  • Huang X; Department of Trauma Orthopedic and Hand Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Liu Y; Department of Spinal Surgery, the First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning, China.
  • Liang W; Clinical Laboratory of Guilin Hospital of Traditional Chinese Medicine, Guilin, China.
  • Luo K; Department of Spinal Bone Disease, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Qin Y; Department of Spinal Bone Disease, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Li F; Department of Trauma Orthopedic and Hand Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Xie T; Department of Spinal Bone Disease, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Qin H; Department of Spinal Bone Disease, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • He J; Department of Spinal Surgery, the First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning, China.
  • Wei Q; Department of Bone and Soft Tissue Surgery, Guangxi Medical University Cancer Hospital, Nanning, China. hejuliang@gxmu.edu.cn.
BMC Cancer ; 22(1): 1370, 2022 Dec 30.
Article em En | MEDLINE | ID: mdl-36585638
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Ósseas / Osteossarcoma Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Ósseas / Osteossarcoma Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article