GCT-23. MULTI-INSTITUTIONAL ANALYSIS OF TREATMENT MODALITIES IN BASAL GANGLIA AND THALAMIC GERMINOMA
Bibliographic record
Abstract
Abstract BACKGROUND Central nervous system (CNS) germinomas are radiotherapy (RT)-sensitive tumors with excellent survival. Current treatment strategies combine chemotherapy with RT to reduce the field and dose of RT. There is no standard treatment for germinomas originating in the basal ganglia/thalami (BGTG) given their rarity and poorly-defined imaging characteristics. Craniospinal (CSI), whole brain (WBI), whole ventricle (WVI), and focal RT have been previously utilized; however, the optimal strategy remains unclear. METHODS Retrospective multi-institutional analysis was conducted across 18 institutions in four countries. RESULTS For 46 cases with non-metastatic BGTG, the event-free survival (EFS) was 86.9% at both 5 and 10 years, while overall survival (OS) was 100%, and 95.7% respectively at 5 and 10 years. Median RT dose and range for the various treatment volumes were as follows: CSI (n=10): 2340 cGy (1980–3060 cGy), WBI (n=8): 2340 (1800–3000 cGy), WVI (n=14): 2340 cGy (1800–2550 cGy), focal (n=9): 3600 cGy (3060–5400 cGy). There was no statistically significant difference in the EFS based on RT modality (p=0.57), but EFS for subjects with CSI and WBI were both 100%. The three subjects who received chemotherapy alone had significantly lower EFS than those who received chemotherapy and RT (p=0.001), but were salvageable with RT. CONCLUSION In the largest study to date for BGTG, there were no significant differences in outcomes between patients who received CSI, WBI, WVI or focal RT. This group of patients should be included in future prospective clinical trials, and a more limited RT field may be considered.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".