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.
Yu-Hang Chen, Quanhui Xu, Haohua Yao et al.· Cancer Medicine· 0 citations
Programmed death‐ligand 1 (PD‐L1) has emerged as a potential biomarker for prognosis and treatment response in various solid tumors. However, its clinical relevance in ovarian carcinoma (OC) remains unclear, with published studies reporting inconsistent associations with platinum sensitivity and survival. These discrepancies are likely related to the biological heterogeneity of OC and methodological variability in PD‐L1 evaluation. 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.
J. Hausnerová, Petra Ovesná, L. Ehrlichová et al.· Cancer Medicine· 0 citations
Although accurate information on cancer stage at diagnosis is critical for surveillance, cancer registries in low‐ and middle‐income countries (LMICs) report incomplete stage data. The use of multiple stage classification systems—UICC/AJCC‐TNM‐system, SEER‐Summary‐Stage (SSS), Essential‐TNM (ETNM), and Condensed‐TNM (CTNM) complicates their utility and interoperability. The lack of a unified framework for translating between their categories limits data harmonization for global epidemiological analyses.
Gokul Sarveswaran, A. Ramraj, J. Sankarapillai et al.· Cancer Medicine· 0 citations
Clinical risk group and early minimal residual disease (MRD) guide therapy for childhood B‐cell acute lymphoblastic leukemia (B‐ALL) but may not capture all molecular heterogeneity. We evaluated whether RNA sequencing (RNA‐seq) molecular risk classification improved outcome prediction under Chinese Children's Cancer Group (CCCG)‐acute lymphoblastic leukemia (ALL)‐2020.
Highlights • Integrated ML framework fuses clinical features and DL-sign for ccRCC RFS prediction.• 3D-ViT outperforms ResNet variants, delivering high external test AUC of 0.846 for DL signature.• Combined nomogram achieves excellent external C-index of 0.910 with robust multi-year RFS prediction.• Model outperforms UISS/SSIGN, enabling precise ccRCC risk stratification and clinical decision support.
Data for the use of rituximab, gemcitabine, and oxaliplatin (R‐GemOx) for relapsed/refractory (R/R) large B‐cell lymphoma (LBCL) in the United States are limited. 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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