Lower-grade gliomas (LGGs) encompass a diverse group of primary brain tumors and are associated with poor survival outcomes, particularly among young adults. This study aimed to develop a novel approach for accurately predicting prognosis in LGG patients. Methods: Using gene expression and clinical data from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas, we identified and validated genes with prognostic significance. We then constructed a 71-gene prognostic score and developed a corresponding nomogram. These tools were evaluated for their association with overall survival (OS) and relapse-free survival (RFS) in LGG patients. Additionally, hierarchical clustering of the 71 genes was performed to identify distinct patient subgroups with unique clinical characteristics. Results: The 71-gene score was found to be a significant and independent predictor of poor OS and RFS in LGG patients, regardless of clinicopathological features. Hierarchical clustering revealed 3 distinct patient subgroups. Notably, tumors in Cluster 2 were characterized by higher tumor grade, more frequent radiation therapy, and worse OS and RFS compared to those in Clusters 1 and 3. Furthermore, the 71-gene nomogram, which incorporates survival-related clinical variables, showed high predictive accuracy for OS and for 3- and 5-year survival rates, with area under the curve values of 0.83, 0.88, and 0.86, respectively. Conclusions: The 71-gene nomogram shows significant potential to enhance prognostic prediction in LGG, offering a valuable and reliable tool for clinicians and researchers.
Zhou et al. (Fri,) studied this question.