Identification of a Nomogram with an Autophagy-Related Risk Signature for Survival Prediction in Patients with Glioma

被引:3
|
作者
Fu, Xiaofeng [1 ]
Hong, Luwei [2 ]
Gong, Haiying [3 ]
Kan, Guangjuan [4 ]
Zhang, Pengfei [1 ]
Cui, Ting-Ting [5 ]
Fan, Gonglin [6 ]
Si, Xing [7 ]
Zhu, Jiang [1 ]
机构
[1] Zhejiang Univ, Sch Med, Womens Hosp, Dept Ultrasound, Hangzhou 310000, Zhejiang, Peoples R China
[2] Zhejiang Univ, Sch Med, Affiliated Hosp 2, Dept Radiol, Hangzhou 310000, Zhejiang, Peoples R China
[3] Yiwu Tradit Chinese Med Hosp, Dept Ultrasound, Jinhua 321000, Zhejiang, Peoples R China
[4] Zhejiang Univ, Sch Med, Affiliated Hangzhou Peoples Hosp 1, Dept Ultrasound, Hangzhou 310000, Zhejiang, Peoples R China
[5] Taizhou Tradit Chinese Med Hosp, Dept Ultrasound, Taizhou 318000, Zhejiang, Peoples R China
[6] Zhejiang Univ, Sch Med, Sir Run Run Shaw Hosp, Dept Ultrasound, Hangzhou 310000, Zhejiang, Peoples R China
[7] Hangzhou Normal Univ, Hangzhou 310000, Zhejiang, Peoples R China
关键词
glioma; autophagy; risk signature; prognosis; nomogram; PROPORTIONAL HAZARDS MODEL; RADIORESISTANCE; INHIBITION; APOPTOSIS;
D O I
10.2147/IJGM.S335571
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Glioma is a common type of tumor in the central nervous system characterized by high morbidity and mortality. Autophagy plays vital roles in the development and progression of glioma, and is involved in both normal physiological and various Patients and Methods: A total of 531 autophagy-related genes (ARGs) were obtained and 1738 glioma patients were collected from three public databases. We performed least absolute shrinkage and selection operator regression to identify the optimal prognosisrelated genes and constructed an autophagy-related risk signature. The performance of the signature was validated by receiver operating characteristic analysis, survival analysis, clinic correlation analysis, and Cox regression. A nomogram model was established by using multivariate Cox regression analysis. Schoenfeld's global and individual test were used to estimate time-varying covariance for the assumption of the Cox proportional hazard regression analysis. The R programming language was used as the main data analysis and visualizing tool. Results: An overall survival-related risk signature consisting of 15 ARGs was constructed and significantly stratified glioma patients into high- and low-risk groups (P < 0.0001). The area under the ROC curve of 1-, 3-, 5-year survival was 0.890, 0.923, and 0.889, respectively. Univariate and multivariate Cox analyses indicated that the risk signature was a satisfactory independent prognostic factor. Moreover, a nomogram model integrating risk signature with clinical information for predicting survival rates of patients with glioma was constructed (C-index=0.861 +/- 0.024). Conclusion: This study constructed a novel and reliable ARG-related risk signature, which was verified as a satisfactory prognostic marker. The nomogram model could provide a reference for individually predicting the prognosis for each patient with glioma and promoting the selection of optimal treatment.
引用
收藏
页码:1517 / 1535
页数:19
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