Guillain-Barre Syndrome after Treatment with Dabrafenib for Metastatic Recurrent Melaloma. (P4.232)
Bibliographic record
Abstract
Case report presentation: A 78 year-old lady was diagnosed with a conjonctival melanoma in 2010. She was treated with surgical resection, subsequent palliative radiotherapy and a second surgery at recurrence in December 2012. After trials on Lambrozilumab and Vemurafenib which caused deleterious side effects, she was treated with Dabrafenib, a BRAF inhibitor that revolutionned the treatment of melanoma in the last few years. During the treatment, she developped an acute motor weakness without bulbar or autonomic findings. The complete work-up including a lumbar puncture, brain and spine MRI and EMG testing were consistent with a primary demyelinating diffuse polyneuropathy. She improved after IVIG infusions, but relapsed after re-exposure to Dabrafenib. The complexity of this case relates to the fact that our patient was exposed to 3 different immunotherapies in a 6 months interval. The novelty of those drugs makes this case very challenging. It is the first case to our knowlegde of GBS triggered by Dabrafenib. The extensive work-up, the process leading to this diagnosis and the response to treatment will be detailed on the poster.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".