MEDU-41. MANAGEMENT OF MEDULLOBLASTOMA PATIENTS IN PRAGUE PEDIATRIC HEMATOLOGY AND ONCOLOGY CENTER
Bibliographic record
Abstract
BACKGROUND: The purpose of the study was to evaluate outcome and pattern of failure in patients with newly diagnosed medulloblastoma treated at the Department of Pediatric Hematology and Oncology in Prague, Czech Republic between 2000–2015. METHODS: Demographics, treatment and survival data were collected in 94 consecutive patients (34 F, 60 M) with histologicaly proven medulloblastoma. Median patient age at the time of diagnosis was 8.43 (0.29 - 17.6) years. Two patients were lost to follow up. Altogether 92 patients were evaluable, Kaplan-Meier analysis was performed to determine survival. Two out of 16 infants (5 metastatic) deceased before the start of any treatment, 14 were treated with chemotherapy only. Older patients (n=75) were treated with radiotherapy and chemotherapy, 44 as a standard risk (SR) and 31 as high risk (HR) group (14 metastatic). One patient with biallelic BRCA2/FANCD1 mutation underwent individualized treatment. RESULTS: The 5-year PFS and OS of all 92 analyzed patients were 66.8% and 72.3%. Survival was higher in older children treated with radiotherapy with 5-year PFS and OS 75.9% and 76.9% respectively. 5-year OS in SR treatment group was 83.0%, in HR group 67.9%. Overall 23 patients have died from all causes. Strikingly, the incidence of secondary malignancies reached 9% (n=9 in 8 patients) and were responsible for 4 deaths. CONCLUSION: The prognosis of medulloblastoma patients is good with over 70% surviving 5 years from the diagnosis with current therapies. Worrisome is a number of SMN. “Supported by the “Project for Conceptual Development of Research Organization 00064203”
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".