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

Mohammad Hamza Bajwa, Altaf Ali Laghari, Sufiyan Sufiyan, Wajiha Amin, Arsalan Ahmed, Syed Hani Abidi, Ahmed Gilani, Nouman Mughal, Syed Ather Enam

Chinese Clinical Oncology, 2024

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.21037/cco-24-ab059
Data confidence 70 medium
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Abstract

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.