The influence of central review on outcome in malignant gliomas of the spinal cord: the CCG-945 experience
Bibliographic record
Abstract
OBJECT The impact of central pathology review on outcome has been described in pediatric patients with high-grade glioma (HGG). The objective of this report was to analyze the impact of the central pathology review on outcome in the subgroup of patients with institutional diagnosis of HGG of the spinal cord enrolled in the Children's Cancer Group 945 cooperative study. METHODS Five neuropathologists centrally reviewed the pathology of the 18 patients with HGG of the spinal cord who were enrolled in the study. These reviews were independent, and reviewers were blinded to clinical history and outcomes. A consensus diagnosis was established for each patient, based on the outcome of the review. RESULTS Of 18 patients, only 10 were confirmed to have HGG on central review. At a median follow-up of 12 years, event-free and overall survival for all 18 patients was 43.2% ± 13.3% and 50% ± 13.4%, respectively. After central review, 10-year event-free and overall survival for confirmed HGGs and discordant diagnoses was 30% ± 12.5% versus 58.3% ± 18.8% (p = 0.108) and 30% ± 12.5% versus 75% ± 14.2% (p = 0.0757), respectively. CONCLUSIONS The level of discordant diagnoses in children and adolescents with institutional diagnosis of HGG of the spinal cord was 44% in this experience. However, there was no significant difference in outcome between patients with confirmed and discordant diagnosis. This group of tumor deserves a specific attention in future trials.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".