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Incorporating supramaximal resection into survival stratification of IDH-wildtype glioblastoma: a refined multi-institutional recursive partitioning analysis

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dc.contributor.author김세훈-
dc.contributor.author박예원-
dc.contributor.author안성수-
dc.contributor.author이승구-
dc.contributor.author장종희-
dc.contributor.author한경화-
dc.date.accessioned2025-02-03T08:10:27Z-
dc.date.available2025-02-03T08:10:27Z-
dc.date.issued2024-11-
dc.identifier.issn1078-0432-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/201580-
dc.description.abstractPurpose: To propose a novel recursive partitioning analysis (RPA) classification model in patients with IDH-wildtype glioblastomas that incorporates the recently expanded conception of the extent of resection (EOR) in terms of both supramaximal and total resections. Experimental design: This multicenter cohort study included a developmental cohort of 622 patients with IDH-wildtype glioblastomas from a single institution (Severance Hospital) and validation cohorts of 536 patients from three institutions (Seoul National University Hospital, Asan Medical Center, and Heidelberg University Hospital). All patients completed standard treatment including concurrent chemoradiotherapy and underwent testing to determine their IDH mutation and MGMTp methylation status. EORs were categorized into either supramaximal, total, or non-total resections. A novel RPA model was then developed and compared with a previous Radiation Therapy Oncology Group (RTOG) RPA model. Results: In the developmental cohort, the RPA model included age, MGMTp methylation status, Karnofsky performance status, and EOR. Younger patients with MGMTp methylation and supramaximal resections showed a more favorable prognosis [class I: median overall survival (OS) 57.3 months], whereas low-performing patients with non-total resections and without MGMTp methylation showed the worst prognosis (class IV: median OS 14.3 months). The prognostic significance of the RPA was subsequently confirmed in the validation cohorts, which revealed a greater separation between prognostic classes for all cohorts compared with the previous RTOG RPA model. Conclusions: The proposed RPA model highlights the impact of supramaximal versus total resections and incorporates clinical and molecular factors into survival stratification. The RPA model may improve the accuracy of assessing prognostic groups. See related commentary by Karschnia et al., p. 4811.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherAmerican Association for Cancer Research-
dc.relation.isPartOfCLINICAL CANCER RESEARCH-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAdult-
dc.subject.MESHAged-
dc.subject.MESHBrain Neoplasms* / genetics-
dc.subject.MESHBrain Neoplasms* / mortality-
dc.subject.MESHBrain Neoplasms* / pathology-
dc.subject.MESHBrain Neoplasms* / surgery-
dc.subject.MESHChemoradiotherapy / methods-
dc.subject.MESHDNA Methylation-
dc.subject.MESHDNA Modification Methylases / genetics-
dc.subject.MESHDNA Repair Enzymes / genetics-
dc.subject.MESHFemale-
dc.subject.MESHGlioblastoma* / genetics-
dc.subject.MESHGlioblastoma* / mortality-
dc.subject.MESHGlioblastoma* / pathology-
dc.subject.MESHGlioblastoma* / surgery-
dc.subject.MESHHumans-
dc.subject.MESHIsocitrate Dehydrogenase* / genetics-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHMutation-
dc.subject.MESHPrognosis-
dc.titleIncorporating supramaximal resection into survival stratification of IDH-wildtype glioblastoma: a refined multi-institutional recursive partitioning analysis-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Pathology (병리학교실)-
dc.contributor.googleauthorYae Won Park-
dc.contributor.googleauthorKyu Sung Choi-
dc.contributor.googleauthorMartha Foltyn-Dumitru-
dc.contributor.googleauthorGianluca Brugnara-
dc.contributor.googleauthorRouzbeh Banan-
dc.contributor.googleauthorSooyon Kim-
dc.contributor.googleauthorKyunghwa Han-
dc.contributor.googleauthorJi Eun Park-
dc.contributor.googleauthorTobias Kessler-
dc.contributor.googleauthorMartin Bendszus-
dc.contributor.googleauthorSandro Krieg-
dc.contributor.googleauthorWolfgang Wick-
dc.contributor.googleauthorFelix Sahm-
dc.contributor.googleauthorSeung Hong Choi-
dc.contributor.googleauthorHo Sung Kim-
dc.contributor.googleauthorJong Hee Chang-
dc.contributor.googleauthorSe Hoon Kim-
dc.contributor.googleauthorDoonyaporn Wongsawaeng-
dc.contributor.googleauthorJeffrey Michael Pollock-
dc.contributor.googleauthorSeung-Koo Lee-
dc.contributor.googleauthorRamon Francisco Barajas Jr-
dc.contributor.googleauthorPhilipp Vollmuth-
dc.contributor.googleauthorSung Soo Ahn-
dc.identifier.doi10.1158/1078-0432.CCR-23-3845-
dc.contributor.localIdA00610-
dc.contributor.localIdA05330-
dc.contributor.localIdA02234-
dc.contributor.localIdA02912-
dc.contributor.localIdA03470-
dc.contributor.localIdA04267-
dc.relation.journalcodeJ00564-
dc.identifier.pmid38829906-
dc.identifier.urlhttps://aacrjournals.org/clincancerres/article/30/21/4866/749134/Incorporating-Supramaximal-Resection-into-Survival-
dc.contributor.alternativeNameKim, Se Hoon-
dc.contributor.affiliatedAuthor김세훈-
dc.contributor.affiliatedAuthor박예원-
dc.contributor.affiliatedAuthor안성수-
dc.contributor.affiliatedAuthor이승구-
dc.contributor.affiliatedAuthor장종희-
dc.contributor.affiliatedAuthor한경화-
dc.citation.volume30-
dc.citation.number21-
dc.citation.startPageepub-
dc.citation.endPage4875-
dc.identifier.bibliographicCitationCLINICAL CANCER RESEARCH, Vol.30(21) : epub-4875, 2024-11-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurosurgery (신경외과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Pathology (병리학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers

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