AB059. Molecular signatures for survival prediction in glioma: a prospective, real-world data analysis.

Background: Glioma characterization and follow-up are underreported from low-and-middle-income country centers within the literature. With the recent emphasis on molecular markers for survival prediction, there is a need for robust data exploring molecular epidemiology in these countries. In Pakistan particularly, there is a significant gap in glioma outcomes reporting and survival analysis.

Methods: One hundred and sixty-five consecutive glioma patients were enrolled from 2019 onwards; histopathological and molecular analysis was performed on archived formalin-fixed paraffin-embedded (FFPE) blocks for isocitrate dehydrogenase (IDH), P53, α-thalassemia retardation X-linked (ATRX) and Ki-67 immunohistochemical (IHC) markers. Survival analysis was calculated using the Kaplan-Meier method; hazard ratios are reported through a multivariate Cox regression model.

Results: Fifty-seven (35%) histopathological diagnoses were revised according to the updated criteria; 30% (n=16) glioblastoma were converted to a new category on re-analysis. IDH wild type (IDH-WT) gliomas had a significantly worse overall survival (log-rank =0.002), with a 2-year survival rate of 60% for IDH-mutant (IDH-M) and 38% for IDH-WT. Significant survival differences were seen for the Ki-67 index (log-rank =0.001) and methylguanine methyltransferase (MGMT) promotor methylation [log-rank =0.027, 2-year survival rate: 100% (methylation detected), 33% (methylation not detected)]. On Cox proportional hazards regression, gross total resection (P<0.001), IDH mutation (P<0.001), and updated histopathological diagnosis (P<0.001) were significant predictors of survival, with good sensitivity and specificity as seen on receiver operating characteristic (ROC) analysis [area under the curve (AUC) =0.86].

Conclusions: In our cohort, the revised World Health Organization (WHO) classification shows significant implications on prognosis and implications for treatment. Although these markers are not commonly used in low-and-middle-income country centers, our results strongly support their greater implementation for improved prognostication and reclassification.