LGG-23. EXCELLENT CLINICAL / RADIOLOGICAL RESPONSE TO BRAF INHIBITION IN A YOUNG CHILD WITH IN-OPERABLE SUPRA-SELLAR PILOCYTIC ASTROCYTOMA
Bibliographic record
Abstract
Abstract In-operable low grade gliomas (LGG) in the pediatric population continue to present a treatment dilemma. Due to the low-grade nature of these tumors, and variable response to chemotherapy / radiation, the choice of adjuvant treatment is difficult. Overall survival is directly related to the degree of surgical resection, adding complexity to these inoperable tumors. Current chemotherapeutic regimen for these inoperable tumors includes vincristine (VCR) and carboplatin (Carbo). With advancements in the molecular characterization of gliomas, the role of targeted therapy has come into question. We present a 2-year-old female with biopsy proven Pilocytic Astrocytoma (positive BRAF-V600E mutation) involving the hypothalamic/optic chiasm region. She presented with ataxic gait, bi-temporal hemianopia, obstructive hydrocephalus and central hypothyroidism, which progressed to altered consciousness, and right hemiparesis due to location/mass effect of the tumor. She was initially treated with chemotherapy (VCR/Carbo) but her tumor progressed at 6 weeks of treatment. As her tumor was positive for BRAF-V600E mutation, she was started on Dabrafenib monotherapy, resulting in dramatic improvement in her clinical symptoms (able to stand, improved vision), and a 60% reduction in tumor size at 3-months. At 6-months, follow up MRI showed slight increase in the solid portion of the tumor, with no clinical symptoms. We plan to add MEK inhibitor (Trametinib) and continue with Dabrafenib. Our experience and literature review suggests that LGG with BRAF-V600E mutations may benefit from upfront targeted therapy. Prospective clinical trials comparing the efficacy of BRAF inhibitors versus standard chemotherapy in LGG with BRAF mutations are urgently needed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".