Bioinformatic analysis constructs an optimal prognostic index for survival-related variables (OPISV) based on whole-genome expression data in Glioblastoma.

Purpose: Using clinical information and transcriptomic sequencing data from glioblastoma (GBM) patients in the TCGA database to perform gene-by-gene analysis that is aligned with individual patient characteristics and develop an optimal prognostic index of survival-related variables (OPISV) through iterative machine learning techniques to predict the prognosis of GBM patients.

Study Design: The TCGA dataset was utilized as the training dataset, while two GEO datasets served as independent validation cohorts. Initially, survival analysis (p < 0.