A comparative analysis of IDH-mutant glioma in pediatric, young adult, and older adult patients
Bibliographic record
Abstract
BACKGROUND: The frequency and significance of IDH mutations in glioma across age groups are incompletely understood. We performed a multi-center retrospective age-stratified comparison of patients with IDH-mutant gliomas to identify age-specific differences in clinico-genomic features, treatments, and outcomes. METHODS: Clinical, histologic, and sequencing data from patients with IDH-mutant, grades 2-4 gliomas, were collected from collaborating institutions between 2013 and 2019. Patients were categorized as pediatric (<19 years), young adult (YA; 19-39 years), or older adult (≥40 years). Clinical presentation, treatment, histologic, and molecular features were compared across age categories using Fisher's exact test or analysis-of-variance. Cox proportional-hazards regression was used to determine the association of age and other covariates with overall (OS) and progression-free survival (PFS). RESULTS: We identified a cohort of 379 patients (204 YA) with IDH-mutant glioma with clinical data. There were 155 (41%) oligodendrogliomas and 224 (59%) astrocytomas. YA showed significantly shorter PFS and shorter median time-to-malignant transformation (MT) compared to pediatric and adult groups, but no significant OS difference. Adjusting for pathology type, extent of resection, and upfront therapy in multivariable analysis, the YA group was independently prognostic of shorter PFS than pediatric and adult groups. Among astrocytomas, CDK4/6 copy number amplifications were associated with both shorter PFS and shorter OS. Among oligodendrogliomas, PIK3CA and CDKN2A/2B alterations were associated with shorter OS. CONCLUSIONS: IDH-mutant glioma YA patients had significantly shorter PFS and time to MT but did not differ in OS compared to pediatric and adult groups. Treatment approaches varied significantly by patient age and warrant further study as addressable age-associated outcome drivers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".