Establishment of a Nomogram with EMP3 for Predicting Clinical Outcomes in Patients with Glioma: A Bi-center Study

Overview

Journal CNS Neurosci Ther

Specialties Neurology
Pharmacology

Date 2021 Jul 16

PMID 34268874

Citations 6

Authors

Anke Zhang

Houshi Xu

Zeyu Zhang

Yibo Liu

Xiaying Han

Ling Yuan

Yunjia Ni

Shiqi Gao

Yuanzhi Xu

Sheng Chen

Junkun Jiang

Yike Chen

Xiaotao Zhang

Meiqing Lou

Jianmin Zhang

Affiliations

Soon will be listed here.

Abstract

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.

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