MOLECULAR CLASSIFICATION VERSUS TRADITIONAL HISTOPATHOLOGICAL CLASSIFICATION IN GLIOMAS: A SYSTEMATIC REVIEW

Abstract

Background: Glioma classification has evolved from morphology-based grading toward integrated diagnosis using histopathology, immunohistochemistry, molecular genetics, genomic profiling and selected imaging biomarkers. The supplied evidence matrix summarizes 22 studies addressing this transition. Objective: To synthesize evidence comparing traditional histopathological classification with molecular classification for glioma diagnosis, biological subclassification, prognostic stratification and clinical application. Methods: The 22 studies identified in the supplied results matrix were synthesized narratively in accordance with PRISMA 2020 principles. Study design, classification approach, molecular markers, imaging contribution, principal outcomes and clinical implications were extracted. Quantitative pooling was not undertaken because of substantial heterogeneity in study design, populations, platforms and reported outcomes. Results: The evidence consistently indicated that molecular information adds diagnostic and prognostic resolution beyond morphology alone. IDH alterations, 1p/19q codeletion, MGMT promoter methylation, TP53, EGFR, PDGFRA, ATRX, TERT promoter alterations and broader expression/genomic signatures were reported as clinically informative. Gene-expression profiling showed stronger survival correlation than histological classification in the Nutt study. Simplified molecular/immunohistochemical approaches also demonstrated clinical utility. Imaging contributed complementary information but did not replace tissue-based diagnosis. Histopathology remained essential for morphological assessment but was limited by sampling, subjective interpretation and interobserver variability. Conclusion: The evidence supports integrated histopathological and molecular classification rather than replacement of one modality by the other. Contemporary WHO CNS classification reflects this molecularly informed paradigm. Future priorities include standardized testing, access to affordable molecular assays, quality assurance and prospective evaluation of the effect of integrated classification on treatment selection and patient outcomes.