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Establishment of a nomogram with EMP3 for predicting clinical outcomes in patients with glioma: A bi-center study

机译:与EMP3的建立题库以预测胶质瘤患者的临床结果:双中心研究

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Aim To demonstrate the clinical value of epithelial membrane protein 3 (EMP3) with bioinformatic analysis and clinical data, and then to establish a practical nomogram predictive model with bicenter validation. Methods The data from CGGA and TCGA database were used to analyze the expression of EMP3 and its correlation with clinical prognosis. Then, we analyzed EMP3 expression in samples from 179 glioma patients from 2013 to 2017. Univariate and multivariate cox regression were used to predict the prognosis with multiple factors. Finally, a nomogram to predict poor outcomes was formulated. The accuracy and discrimination of nomograms were determined with ROC curve and calibration curve in training and validation cohorts. Results EMP3 was significantly higher in higher-grade glioma and predicted poor prognosis. In multivariate analysis, high expression of EMP3 (HR?=?2.842, 95% CI 1.984–4.071), WHO grade (HR?=?1.991, 95% CI 1.235–3.212), and IDH1 mutant (HR?=?0.503, 95% CI 0.344–0.737) were included. The nomogram was constructed based on the above features, which represented great predictive value in clinical outcomes. Conclusion This study demonstrated EMP3 as a novel predictor for clinical progression and clinical outcomes in glioma. Moreover, the nomogram with EMP3 expression represented a practical approach to provide individualized risk assessment for glioma patients.
机译:目的旨在证明具有生物信息分析和临床数据的上皮膜蛋白3(EMP3)的临床价值,然后建立具有Bicenter验证的实用墨迹预测模型。方法采用CGGA和TCGA数据库的数据分析EMP3表达及其与临床预后的相关性。然后,我们分析了来自2013年至2013年的179名胶质瘤患者的样品中的EMP3表达。单变量和多元COX回归用于预测多种因素的预后。最后,制定了预测结果不良结果的载体图。 ROM图的准确性和歧视与ROC曲线和校准曲线确定训练和验证队列。结果较高级胶质瘤的EMP3显着较高,预测预后差。在多变量分析中,EMP3的高表达(HR?=?2.842,95%CI 1.984-4.071)级别(HR?=?1.991,95%CI 1.235-3.212)和IDH1突变体(HR?= 0.503,包括95%CI 0.344-0.737)。基于上述特征构建了NOM图,该特征在临床结果中表示巨大的预测值。结论本研究证明了EMP3作为胶质瘤临床进展和临床结果的新型预测因子。此外,具有EMP3表达的NOM图表表示为胶质瘤患者提供个性化风险评估的实用方法。

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