Multi‐institutional analysis of treatment modalities in basal ganglia and thalamic germinoma
Bibliographic record
Abstract
BACKGROUND: Central nervous system (CNS) germinomas are treatment-sensitive tumors with excellent survival outcomes. Current treatment strategies combine chemotherapy with radiotherapy (RT) in order to reduce the field and dose of RT. Germinomas originating in the basal ganglia/thalamus (BGTGs) have proven challenging to treat given their rarity and poorly defined imaging characteristics. Craniospinal (CSI), whole brain (WBI), whole ventricle (WVI), and focal RT have all been utilized; however, the best treatment strategy remains unclear. METHODS: Retrospective multi-institutional analysis has been conducted across 18 institutions in four countries. RESULTS: For 43 cases of nonmetastatic BGTGs, the 5- and 10-year event-free survivals (EFS) were 85.8% and 81.0%, respectively, while the 5- and 10-year overall survivals (OS) were 100% and 95.5%, respectively (one patient fatality from unrelated cause). Median RT doses were as follows: CSI: 2250 cGy/cGy(RBE) (1980-2400); WBI: 2340 cGy/cGy(RBE) (1800-3000); WVI: 2340 cGy/cGy(RBE) (1800-2550); focal: 3600 cGy (3060-5400). Thirty-eight patients (90.5%) received chemotherapy. There was no statistically significant difference in the EFS based on initial field extent (p = .84). Nevertheless, no relapses were reported in patients who received CSI or WBI. Chemotherapy alone had significantly inferior EFS compared to combined therapy (p = .0092), but patients were salvageable with RT. CONCLUSION: Patients with BGTGs have excellent outcomes and RT proved to be an integral component of the treatment plan. This group of patients should be included in future prospective clinical trials and the best RT field should be investigated further.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".