MDB-15. CLINICAL CHARACTERISTICS AND OUTCOME OF CHILDHOOD LI-FRAUMENI SYNDROME MEDULLOBLASTOMA PATIENTS
Bibliographic record
Abstract
Abstract Patients with Li-Fraumeni syndrome (LFS) who develop medulloblastoma (MB) have a very poor prognosis. The development of novel therapeutic strategies is challenged by the lack of clinical data for this patient group. We here present clinical and molecular data on a retrospective cohort of pediatric patients with LFS-associated MB. This is an international, retrospective, multicenter cohort study. Patients with LFS-associated MB under 21 years and class 5 (pathogenic) or class 4 (likely pathogenic) constitutional TP53 variants were included. We evaluated TP53 mutation status (constitutional and somatic), DNA methylation subgroup, treatment modalities, event-free (EFS) and overall survival (OS), patterns of recurrence, as well as occurrence of secondary neoplasms. Forty-seven individuals with LFS-associated MB were included. MBs were classified mainly as Sonic Hedgehog (SHH) group (87%). TP53 variants were classified as class 5 (70%) and class 4 (30%). The majority (74%) of TP53 variants represented missense variants. The 2-year (y-) EFS and -OS were 33% and 53%, respectively. A significantly better outcome was seen in patients who received post-operative radiotherapy (RT) (2y-EFS: 44%, 2y-OS: 60%) or chemotherapy before RT (2y-EFS: 24%, 2y-OS: 48%) compared with patients who received no RT (2y-EFS: n.a., 2y-OS: 25%). No significantly different outcomes were seen between patients treated either according to protocols including high-intensity chemotherapy or receiving only maintenance-type chemotherapy (2y-EFS: 42% and 31%, 2y-OS: 68% and 53%, respectively). Patients with LFS-associated MB have a dismal prognosis. Use of RT in LFS-associated MB significantly increased survival rates in the presented cohort, but choice of chemotherapy regimen did not influence their clinical outcome. To improve the outcome of patients with LFS-associated MB, prospective collection of clinical data and development of novel treatments are required.
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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 | 0.001 |
| 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) | 0.002 | 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".