P27.14.B OPTIMIZING GLIOBLASTOMA TRIAL DESIGN: A PROGNOSTIC MODEL HARNESSING REAL-WORLD DATA AND GENOMIC ALTERATIONS
Authors: T Christiansen, V Fougner, S B Chiranth, R H Dahlrot, J K Petersen, I J Christensen, D S Nørøxe, B Hasselbalch, U Lassen, H S Poulsen, T Urup
Journal: Neuro-Oncology (2024)

Abstract INTRODUCTION Patients with glioblastoma, the most aggressive primary brain tumor, lack effective treatment despite advancements in molecular understanding. This study aims to develop and validate a prognostic model integrating genomic alterations and clinical factors in newly diagnosed glioblastoma patients undergoing standard radiation therapy with concomitant and adjuvant temozolomide. MATERIALS AND METHODS From our prospective clinical database, all consecutive IDH-wildtype glioblastoma patients who received standard therapy at Rigshospitalet (Denmark) from January 2016 to December 2023 were included. The cohort was divided into training (2016-21) and validation (2021-23) datasets. Tumor tissue underwent genomic profiling (whole-exome, whole-genome, or targeted panel sequencing). Candidate genomic factors comprised pathogenic and likely-pathogenic genetic variants present in &amp;gt; 5% of cases. Uni- and multivariate Cox regression analysis was performed to model overall survival (OS) and progression-free survival (PFS). The final multivariate model will be applied to the validation set. RESULTS A total of 515 were included in training (n=361) and validation (n=154). Genomic profiling was conducted in 214 patients (59%) of the training set and 122 patients (79%) of the validation set. A clinical prognostic model was developed by multivariate analysis of OS (training set): ECOG-performance status 1 vs. 0 (HR = 1.12, 95% CI: 0.88-1.43; p=0.36) and 2 vs. 0 (HR = 1.78, 95% CI: 1.04-3.06; p=0.04), ten year age increase (HR 1.08, 95% CI: 0.97-1.21; p=1.17), corticosteroid use (HR = 1.39, 95% CI: 1.10-1.75; p&amp;lt;0.01), multifocal disease (HR = 1.91, 95% CI: 1.40-2.61; p&amp;lt;0.01), surgical resection vs. biopsy (HR = 0.89, 95% CI: 0.66-1.21; p=0.47), and unmethylated O6-methylguanine-DNA methyltransferase (MGMT) promotor region (HR = 2.16, 95% CI: 1.69-2.75; p&amp;lt;0.01). Using this model, a clinical prognostic index for OS was established with a concordance index of 0.65. Application of the prognostic index to the validation set showed a significant association (p&amp;lt;0.01). In the training set, five out of 13 candidate genomic alterations were associated (p &amp;lt; 0.10) with OS by univariate analysis. By adding these to the prognostic index, two genomic alterations were independently associated with OS: Neurofibromin 1 (NF1) (HR 1.72, 95% CI: 1.08-2.74; p=0.02) and Retinoblastoma transcriptional corepressor 1 (RB1) (HR 0.54, 95% CI: 0.34-0.84; p&amp;lt;0.01). Validation analysis of these predictors will be performed using the internal validation dataset and has been planned in an external cohort. CONCLUSION A clinical prognostic index was established and validated. NF1 and RB1 alterations were independent predictors of OS. The results will be presented. This study advances prognostic stratification and enables matching-adjusted single-arm trials for testing of targeted therapies.