Real‐World Validation of the Clinical Distinctiveness of IDH‐Mutant Glioblastoma in the SEER Transition Era: A Population‐Based Study Integrating Machine Learning
Aug 2026· Brain and Behavior· Vol 16· 0 citations· 27 references
Medicine
TL;DR
This study aims to provide real‐world validation of this reclassification using the specific ICD‐O‐3 code (9445/3) from the Surveillance, Epidemiology, and End Results (SEER) “Transition Era” (2018–2022) and develop a machine learning (ML)‐based prognostic model.
Abstract
The 2021 WHO classification reclassified “IDH‐mutant glioblastoma (GBM)” as “Astrocytoma, IDH‐mutant, grade 4.” This study aims to provide real‐world validation of this reclassification using the specific ICD‐O‐3 code (9445/3) from the Surveillance, Epidemiology, and End Results (SEER) “Transition Era” (2018–2022) and develop a machine learning (ML)‐based prognostic model.
TFE3‐rearranged renal cell carcinoma (TFE3‐rRCC) is a rare, aggressive subtype that predominantly affects adolescents and young adults. Its marked morphologic heterogeneity can delay recognition and downstream confirmatory testing.
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In the absence of a standardized, OC‐specific assessment methodology, the Combined Positive Score (CPS) with cutoffs of ≥ 1 and ≥ 10, applied in other tumor types, represents a pragmatic approach.
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The use of multiple stage classification systems—UICC/AJCC‐TNM‐system, SEER‐Summary‐Stage, Essential‐TNM (ETNM), and Condensed‐TNM (CTNM) complicates their utility and interoperability, and the lack of a unified framework for translating between their categories limits data harmonization for global epidemiological anal...
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It is evaluated whether RNA sequencing molecular risk classification improved outcome prediction under Chinese Children's Cancer Group (CCCG)‐acute lymphoblastic leukemia (ALL)‐2020.
This retrospective observational study characterizes R‐GemOx treatment patterns and outcomes among patients with R/R LBCL from the nationwide, longitudinal Flatiron Health electronic health record‐derived database comprising patient‐level data primarily from US community oncology practices.
L. Budde, A. Olszewski, Bei Hu et al.· eJHaem· 0 citations
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