MB-23RECURRENT SHH/TP53 MUTANT MEDULLOBLASTOMA TREATED WITH A COMBINATION OF LITHIUM AND RADIATION THERAPY
Bibliographic record
Abstract
INTRODUCTION: TP53 mutations remain a poor prognotic factor and account for a high proportion of the treatment failure in SHH subgroup medulloblatoma. Poor survival of patients with P53 mutant medulloblastoma may be related to radiation/chemotherapy resistance. Lithium, an activator of the WNT pathway, sensitizes TP53 mutant medulloblastoma to radiation. CASE REPORT: a 12-yo boy presented with left localized hemispheric medulloblastoma. After a complete excision of the tumour he was randomized and treated according to COG ACNS0331 and received a standard-dose craniospinal radiation with a boost to the entire posterior fossa, followed by maintenance chemotherapy. Patient was considered in complete remission. 15 months post-end of treatment, MRI showed a local recurrence. After 2 cycles of temozolomide, irinotecan and bevacizumab chemotherapy, patient had tumor progression. He then underwent a complete resection of the tumour. Pathology showed anaplastic type, SHH/TP53 mutant medulloblastoma. Due to the expected poor survival and the lack of known and consensual curative treatment, the patient was treated with a combination of therapeutic dose of lithium and focal radiation therapy to a dose of 54 Gy. One year later, the patient remains asymptomatic and, in complete remission. CONCLUSION: Lithium combined to radiation therapy may represent an interesting therapeutic avenue for higher risk groups of medulloblastoma in a context of a pilot study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".