Prognostic value of inflammation-based scores in patients with osteosarcoma.
Prognostic value of inflammation-based scores in patients with osteosarcoma.
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DOI：
10.1038/srep39862
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发表时间：
2016-12-23
影响因子：
4.6
通讯作者：
He A
中科院分区：
文献类型：
--
作者：
Liu B;Huang Y;Sun Y;Zhang J;Yao Y;Shen Z;Xiang D;He A
全身炎症反应与癌症的发生和进展有关。C-反应蛋白（CRP）、格拉斯哥预后评分（GPS）、嗜中性粒细胞-淋巴细胞比率（NLR）、血小板-淋巴细胞比率（PLR）、淋巴细胞-单核细胞比率（LMR）和嗜中性粒细胞-血小板评分（PLT）已被证明是各种类型恶性肿瘤的独立危险因素。本文回顾性分析了162例骨肉瘤病例，以评估其对骨肉瘤生存的预测价值。采用SPSS统计软件进行统计学分析。生成受试者工作特征（ROC）分析以设置最佳阈值;曲线下面积（AUC）用于显示基于炎症的评分的区分能力;进行Kaplan-Meier分析以绘制生存曲线;采用考克斯回归模型来确定独立的预后因素。NLR、PLR和LMR的最佳截断点分别为2.57、123.5和4.73。GPS和NLR的AUC明显大于CRP、PLR和LMR。CRP、GPS、NLR、PLR水平升高及LMR水平降低与预后不良相关（P < 0.05）。多因素考克斯回归分析显示，GPS、NLR和发生转移是骨肉瘤患者死亡的首要危险因素。
Systemic inflammation responses have been associated with cancer development and progression. C-reactive protein (CRP), Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and neutrophil-platelet score (NPS) have been shown to be independent risk factors in various types of malignant tumors. This retrospective analysis of 162 osteosarcoma cases was performed to estimate their predictive value of survival in osteosarcoma. All statistical analyses were performed by SPSS statistical software. Receiver operating characteristic (ROC) analysis was generated to set optimal thresholds; area under the curve (AUC) was used to show the discriminatory abilities of inflammation-based scores; Kaplan-Meier analysis was performed to plot the survival curve; cox regression models were employed to determine the independent prognostic factors. The optimal cut-off points of NLR, PLR, and LMR were 2.57, 123.5 and 4.73, respectively. GPS and NLR had a markedly larger AUC than CRP, PLR and LMR. High levels of CRP, GPS, NLR, PLR, and low level of LMR were significantly associated with adverse prognosis (P < 0.05). Multivariate Cox regression analyses revealed that GPS, NLR, and occurrence of metastasis were top risk factors associated with death of osteosarcoma patients.
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影响因子：
3.5
作者：
Jeong, Jae-Heon;Lim, Sun Min;Kim, Yu Ri
通讯作者：
Kim, Yu Ri
DOI：
10.12659/msm.894448
发表时间：
2015-09-25
期刊：
Medical science monitor : international medical journal of experimental and clinical research
影响因子：
--
作者：
Liu Y;Teng Z;Wang Y;Gao P;Chen J
通讯作者：
Chen J
影响因子：
8
作者：
Ji, H;Houghton, AM;Wong, KK
通讯作者：
Wong, KK
影响因子：
50.5
作者：
Joseph, N.;Dovedi, S. J.;Choudhury, A.
通讯作者：
Choudhury, A.
影响因子：
8.8
作者：
Lamb, G. W. A.;Aitchison, M.;Ramsey, S.;Housley, S. L.;McMillan, D. C.
通讯作者：
McMillan, D. C.