Reconciling Extent of Resection and Residual Tumor Volume in Glioblastoma: Sources of Discordance and a Proposed Reporting Framework

Extent of resection (EOR) and residual tumor volume (RV) are among the few modifiable prognostic factors in glioblastoma (GBM), yet their interpretation remains complicated by substantial methodological heterogeneity.This narrative review synthesizes contemporary literature on EOR and RV as prognostic metrics in adult IDH-wild-type GBM, drawing on a structured search of PubMed/MEDLINE, Embase, Scopus, and Web of Science (January 2000-March 2026), and proposes a standardized reporting framework to improve cross-study comparability.Although both metrics are consistently associated with survival, apparent disagreement between EOR-and RV-based studies largely reflects methodological rather than genuine biological discordance.Key sources of heterogeneity include inconsistent terminology (18 distinct terms identified across six decades of literature, only about half with explicit thresholds), variable postoperative MRI timing, differing segmentation methods, inconsistent definitions of contrast-enhancing versus non-enhancing tumor compartments, evolving WHO molecular classification, and inadequate adjustment for confounding by indication, tumor location, and treatment factors.The Response Assessment in Neuro-Oncology (RANO)-resect classification represents an important advance toward standardization and has undergone independent revalidation, but definitional inconsistency persists more broadly.Building on these findings, this review proposes an author-derived, ten-domain reporting framework spanning study population, patient and tumor characteristics, surgical approach, imaging acquisition, segmentation methodology, EOR/RV calculation, molecular classification, confounder adjustment, statistical methods, and outcome reporting, intended to complement rather than replace existing standards such as Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD).This framework has not undergone formal Delphi consensus or prospective validation and should be regarded as a preliminary proposal.Standardized, transparent reporting, potentially supported by emerging AI-based segmentation and reporting tools, may help reconcile apparently conflicting findings and strengthen future evidence synthesis regarding surgical cytoreduction in GBM.