NIMG-53. POST-SURGICAL, RESIDUAL ENHANCING TUMOR VOLUME IS PROGNOSTIC FOR OVERALL SURVIVAL IN NEWLY DIAGNOSED GLIOBLASTOMA: EVIDENCE FROM 1,458 PATIENTS POOLED FROM INTERNATIONAL TRIALS, SINGLE INSTITUTION DATABASES, AND MULTICENTER CONSORTIUMS
Bibliographic record
Abstract
The prognostic significance of residual contrast enhancing tumor volume after initial surgery to predict OS in newly diagnosed GBM remains poorly understood and not controlled for in prospective clinical trials. In the current study we pooled imaging data in >1,400 newly diagnosed GBM patients from international multicenter clinical trials, single institution databases, and multicenter clinical trial consortiums identify relationships between clinical parameters, MGMT methylation status, treatment, and residual enhancing tumor volume on OS. Data from 1,458 newly diagnosed GBM patients from 3 sources (2 for training and 1 for validation) were included in our imaging database: 1) a single institution database from UCLA (N=398; Training Set 1); 2) patients treated within the Ben and Cathy Ivy Foundation for Early Phase Clinical Trials Consortium (N=262 from 8 centers; Training Set 2); and 3) AVAglio – an international phase III trial comparing chemoradiation plus bevacizumab (N=404) vs. placebo (N=394) used as a validation set. Post-surgical, residual enhancing disease was isolated from blood products and quantified using T1 subtraction maps. Multivariate Cox regression models were used to determine influence of clinical variables, MGMT status, and residual tumor volume on OS. Results confirmed that post-surgical, residual enhancing tumor volume is a strong prognostic factor for OS (P<0.0001), regardless of therapy, age, and MGMT status. Pre-surgical tumor volume and extent of resection as continuous variables were not significant prognostic factors, but patients with an extent of resection greater than 98% had a significant survival advantage (P<0.01). Influence of residual non-enhancing disease and other imaging factors will also be discussed. Results support the hypotheses that post-surgical, residual contrast-enhancing disease significantly influences survival in patients with newly diagnosed glioblastoma, regardless of treatment.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".