MDB-09. WNT AND GROUP 4 MEDULLOBLASTOMAS OF EARLY CHILDHOOD TREATED WITH HIGH DOSE CHEMOTHERAPY AND CRANIOSPINAL IRRADIATION SPARING APPROACH
Bibliographic record
Abstract
Abstract BACKGROUND WNT and group 4 medulloblastoma (MB) are rare in young children and their outcome when treated with radiation avoidance infant strategies is unknown. METHOD This retrospective international cohort included children less than 7 years of age, with molecularly characterized group 4 or WNT MB, treated with high-dose chemotherapy(HDC) and CSI sparing approach. RESULTS The current cohort includes 29 patients (19M/10F). For the 26 patients with group 4 MB (median age at diagnosis 45.9 months), 16 (61.5%) were M0 and 17 (65.3%) underwent initial gross total resection (GTR). The most common consolidation regimen used was three cycles of high dose carboplatin and thiotepa (65.5%) or a single cycle of high dose of carboplatin, etoposide and thiotepa (31%).Two received adjuvant focal radiotherapy. Sixteen patients (61.5%) relapsed at a median time of 21.4 months from diagnosis (median age of 5.2 years). Relapse was local for 50% of the patients. One patient underwent palliative management and 15 received radiation-based salvage therapy (2 focal, 13 CSI+/- boost).The median dose of CSI was 36Gy (18-36). Five of the 15 died of disease. Overall, at a median follow-up of 37.9 months from diagnosis, 17/26 (65.3%) patients were alive, six had died of disease and two of toxicity. All 3 WNT patients (median age at diagnosis 57.8 months) underwent GTR and two were M0. Two received sequential high dose carboplatin and thiotepa. One patient with initial partial response, progressed 2 months after treatment completion and received salvaged CSI (18Gy). All of them were alive at a median follow up of 88 months from diagnosis. CONCLUSIONS HDC and CSI sparing approaches led to a high rate of relapse for young patient with group 4 (61.5%). However, 2/3 were salvaged with radiation-based therapy given at a median age 5.2 yrs. Additional WNT patients are needed to better describe their management.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".