P.159 Association Between Extent of Resection and Survival in Pediatric Patients with High-Grade Glioma: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: While pediatric high-grade glioma (HGG) has a poor prognosis, the relationship between extent of resection (EOR), tumor location, and survival remains unclear. Our aim is to determine whether gross-total resection (GTR) is associated with prolonged survival relative to subtotal resection (STR) and biopsy. Methods: PubMed, Ovid EBM Reviews, Embase, and MEDLINE were systematically reviewed. Eligible articles were included for study-level and individual-patient data (IPD) meta-analysis. Difference by study-level and IPD characteristics were estimated using subgroup meta-analysis and meta-regression. PRISMA guidelines were followed. Results: In total, 33 studies were included. Study-level meta-analysis found GTR conferred decreased mortality relative to STR at 1 year (RR=0.73, 95%CI=0.59-0.89) and 2 years (RR=0.74, 95%CI=0.64-0.84). STR did not demonstrate survival advantages compared to biopsy at 1 year (RR=0.81, 95%CI=0.64-1.03), but showed decreased mortality at 2 years (RR=0.90, 95%CI=0.82-0.99). IPD meta-analysis comprised 186 patients, and indicated that STR (HR=2.61, 95%CI=1.56-4.38) and biopsy (HR=2.83, 95%CI=1.54-5.19) had shortened survival relative to GTR, with no differences between STR and biopsy (HR=0.93, 95%CI=0.55-1.56). In subgroup analysis, GTR was associated with prolonged survival for hemispheric tumors (HR=0.16, 95%CI=0.07-0.36) Conclusions: Among pediatric patients with HGGs, GTR was independently associated with better overall survival compared to STR and biopsy, especially in patients with hemispheric tumors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.029 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".