Construction and validation of a robust prognostic model based on immune features in sepsis - Zheng, Yongxin; Liu, Baiyun; Deng, Xiumei; Chen, Yubiao; Huang, Yongbo; Zhang, Yu; Xu, Yonghao; Sang, Ling; Liu, Xiaoqing; Li, Yimin (Frontiers in Immunology, 2022)
Sepsis is uncontrolled host response to infection. Immune-related genes (IRGs) have been used to construct the diagnostic and prognostic model. However, a IRGs prognostic model used to predict the 28-day mortality in sepsis was still limited. Therefore, the study aimed to develop a prognostic model based on IRGs to identify patients with high risk and predict the 28-day mortality in sepsis. A total of 7 datasets were included in our study. Among them, GSE65682 was identified as discovery cohort. According to multivariate Cox regression analysis, 22 DEIRGs were further identified to construct the prognostic model and identify patients with high risk. The Kaplan–Meier survival analysis showed that high risk groups have higher 28-day mortality than low risk groups (P=1.105e-13). External datasets also proven that the prognostic model had an excellent prediction value. Besides, sepsis patients in high risk groups might exist the immunosuppression and immune cells infiltration types were significantly differently. Our study provides a robust prognostic model based on 22 DEIRGs which can predict 28-day mortality and immunosuppression status in sepsis. The higher riskscore was positively associated with 28-day mortality and the development of immunosuppression. IRGs are the promising biomarker which might facilitate the personalized treatments in sepsis.