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

IF 3.2 2区医学 Q2 CLINICAL NEUROLOGY

Journal of Neuro-Oncology Pub Date : 2025-02-24 DOI:10.1007/s11060-025-04950-0

Johannes Wach, Martin Vychopen, Erdem Güresir

{"title":"Prognostic revalidation of RANO categories for extent of resection in glioblastoma: a reconstruction of individual patient data.","authors":"Johannes Wach, Martin Vychopen, Erdem Güresir","doi":"10.1007/s11060-025-04950-0","DOIUrl":null,"url":null,"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.","PeriodicalId":16425,"journal":{"name":"Journal of Neuro-Oncology","volume":" ","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neuro-Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11060-025-04950-0","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}

引用次数: 0

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.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Journal of Neuro-Oncology 医学-临床神经学

CiteScore

6.60

自引率

7.70%

发文量

277

审稿时长

3.3 months

期刊介绍： The Journal of Neuro-Oncology is a multi-disciplinary journal encompassing basic, applied, and clinical investigations in all research areas as they relate to cancer and the central nervous system. It provides a single forum for communication among neurologists, neurosurgeons, radiotherapists, medical oncologists, neuropathologists, neurodiagnosticians, and laboratory-based oncologists conducting relevant research. The Journal of Neuro-Oncology does not seek to isolate the field, but rather to focus the efforts of many disciplines in one publication through a format which pulls together these diverse interests. More than any other field of oncology, cancer of the central nervous system requires multi-disciplinary approaches. To alleviate having to scan dozens of journals of cell biology, pathology, laboratory and clinical endeavours, JNO is a periodical in which current, high-quality, relevant research in all aspects of neuro-oncology may be found.