Prognostic revalidation of RANO categories for extent of resection in glioblastoma: a reconstruction of individual patient data.

Abstract

Background: The RANO classification for glioblastoma defines resection categories based on volumetric tumor assessments, aiming to standardize outcomes related to extent of resection (EOR). This study revalidates the prognostic impact of RANO classes by reconstructing individual patient data (IPD).

Methods: A systematic review and meta-analysis were performed, including three studies comprising 580 glioblastoma patients. Included studies reported or allowed conversion to RANO classes for glioblastoma resection extent, with detailed OS data and numbers at risk. Overall survival (OS) data were extracted from Kaplan-Meier survival curves, and IPD were reconstructed using Digitizelt and the R package IPDfromKM. Survival analyses were conducted using Kaplan-Meier estimates and Cox regression models.

Results: Median follow-up was 15.6 months (IQR: 10.1-28.8). Patients undergoing supramaximal resection (RANO class 1, n = 163) had the highest median OS (35.6 months; 95% CI: 30.9-40.4), significantly outperforming non-class 1 resections (median OS: 13.9 months; 95% CI: 13.0-14.7; p < 0.001). Subgroup analysis revealed superior OS for class 2a (19.0 months) over class 2b (14.1 months; p < 0.001), while class 3 and 4 resections demonstrated progressively poorer outcomes. Hazard ratios consistently favored class 1 versus all other classes (HR: 0.28; 95% CI: 0.23-0.37).

Conclusions: Supramaximal (class 1) resection provides a significant survival benefit in glioblastoma, underscoring its critical role in surgical management. The RANO classification stratifies resection outcomes effectively, supporting its use as a prognostic tool. These findings advocate for resection strategies targeting maximal tumor removal.