Ein integrativer Risikoscore für das post-operative Überleben von neudiagnostizierten Glioblastomen: interaktive Effekte zwischen der chirurgischen Resektion mit klinischen und molekularen Prognosefaktoren

Following resection or biopsy, individuals with newly diagnosed glioblastoma frequently enter clinical trials. Nuanced risk assessment is warranted to reduce imbalances between study arms. Here, we aim (I) to analyze the interactive effects of residual tumor with clinical and molecular factors on outcome and (II) to define a prognostic postoperative risk score.

We retrospectively compiled an international, seven-center training cohort of newly diagnosed glioblastoma. The combined associations of residual tumor with molecular or clinical factors and survival were analyzed, and recursive partitioning analysis was performed for risk modeling. Terminal regression tree nodes were combined into risk classes and a numerical score. The resulting model was prognostically verified in a separate external validation cohort.

Our training cohort compromised 1003 patients with newly diagnosed IDH-wildtype glioblastoma, including 744 patients who underwent adjuvant radiochemotherapy per EORTC-NCIC (TMZ/RT→TMZ). Residual tumor per RANO classification, MGMT promotor methylation status, age (as continuous variable; optimal cutoff: ≤65 years), and KPS (as continuous variable; optimal cutoff: ≥80) were prognostic of overall survival and forwarded into regression tree analysis. By integrating eleven terminal nodes and individually weighting the prognostic factors, an additive scale (range, 0-9 points) integrating these four variables distinguished patients with low (0-2 points), intermediate (3-5 points), and high risk (6-9 points) for poor postoperative outcome (median overall survival: 24 vs. 16 vs. 6 months; p < 0.01). Adjustment of the regression tree for adjuvant therapy was applied, and the presence of the three risk groups was confirmed in the patient subgroups treated with or without RT/TMZ→TMZ. The prognostic value of the risk score was verified in a external single-center validation cohort (n = 231, p < 0.01). Compared to previously postulated risk models, our score was superior in concordance between predicted with observed survival (c-index; development cohort: 0.7, validation cohorts: 0.6).

The risk score integrates molecular and clinical factors to serve as an easy-to-use, yet highly prognostic tool to stratify patients after resection or biopsy of newly diagnosed glioblastoma. The score may serve to inform patient management and minimize imbalances between study arms in prospective interventional trials.