Evidence map›Paper›PMID 40628985›Full record

ArticleEuropean radiology2026

Revisiting prognosis of oligodendroglioma patients in the 2021 WHO classification: incremental value of imaging features.

Seo Hee Choi, Narae Lee, Kaeum Choi, Kyunghwa Han, Na-Young Shin, Sung Soo Ahn, Hong In Yoon, Jong Hee Chang, Se Hoon Kim, Seung-Koo Lee and 1 more

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Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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11 authors.

Seo Hee ChoiDepartment of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea.
Narae LeeDivision of Nuclear Medicine, Department of Radiology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Kaeum ChoiDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, USA.
Kyunghwa HanDepartment of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea.
Na-Young ShinDepartment of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea.
Sung Soo AhnDepartment of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea.
Hong In YoonDepartment of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea.
Jong Hee ChangDepartment of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea.
Se Hoon KimDepartment of Pathology, Yonsei University College of Medicine, Seoul, Korea.
Seung-Koo LeeDepartment of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea.
Yae Won ParkDepartment of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea. yaewonpark@yuhs.ac.ORCID http://orcid.org/0000-0001-8907-5401

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate whether imaging factors can improve the prediction of progression-free survival (PFS) in patients with oligodendroglioma over clinicopathological features. MATERIALS AND

methodsA total of 180 patients diagnosed and treated for oligodendroglioma (IDH-mutant and 1p/19q codeleted) between 2005 and 2021 were included. Clinical data and preoperative MRI images were analyzed for qualitative and quantitative characteristics. Qualitative features included tumor location, calcification, gliomatosis cerebri pattern, cystic change, necrosis, and infiltrative pattern, while quantitative features included total, contrast-enhancing (CE), non-enhancing, and necrotic tumor volumes via automatic segmentation. Significant predictors of PFS were identified using univariable and multivariable Cox analyses. Two prognostic models were developed: model 1 (clinicopathological features) and model 2 (addition of imaging features). The prognostic value of the two models was compared.

resultsOn univariable analysis, male sex, gliomatosis cerebri pattern, larger total tumor, CE tumor, and non-enhancing tumor volumes, and partial resection or biopsy were unfavorable predictors of PFS. On multivariable analysis, male sex (hazard ratio (HR) = 3.76, p = 0.012), larger CE tumor volume (HR = 1.06, p = 0.003) and partial resection or biopsy (HR = 6.83, p = 0.001) remained as unfavorable predictors for PFS. Compared with the clinicopathological model, the model adding imaging feature demonstrated a higher C-index (0.784 vs. 0.776) and iAUC (0.745 vs. 0.725), with a significantly high time-dependent AUC for PFS at 1 year (0.989 vs. 0.943, p = 0.001).

conclusionThe CE tumor volume on preoperative MRI is an independent prognostic factor in oligodendroglioma patients, potentially guiding follow-up and adjuvant treatment decisions. KEY POINTS: Question This study examines whether imaging factors can improve the prediction of progression-free survival (PFS) in patients with oligodendroglioma over clinicopathological features. Findings Larger contrast-enhancing (CE) tumor volume, male sex, and lesser resection independently predicted shorter PFS. Incorporating CE tumor volume improved model performance over clinicopathological features alone. Clinical relevance The clinicopathological and imaging features were comprehensively investigated in patients with oligodendroglioma to predict PFS. Incorporating CE tumor volume improved the model's predictive performance, providing valuable information for clinical decision-making in identifying high-risk patients.

Indexed as

Brain NeoplasmsMagnetic Resonance ImagingOligodendrogliomaAdultAgedFemaleHumansMaleMiddle AgedPrognosisProgression-Free SurvivalRetrospective StudiesTumor BurdenWorld Health OrganizationMagnetic resonance imagingOligodendrogliomaPredictive modelProgression-free survival

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PMID40628985

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.