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Record W4391211391 · doi:10.3390/curroncol31010041

Primary Diffuse Leptomeningeal Melanomatosis in a Child with Extracranial Metastasis: Case Report

2024· article· en· W4391211391 on OpenAlexvenueno aff
Shubin Shahab, Prabhumallikarjun Patil, Jason Fangusaro, Brooke Patteson, Adam Goldman-Yassen, Bree R. Eaton, William Boydston, Matthew Schniederjan, Dolly Aguilera

Bibliographic record

VenueCurrent Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNivolumabIpilimumabMetastasisImmunotherapyPrimary tumorSurgeryInternal medicineCancer

Abstract

fetched live from OpenAlex

Primary meningeal melanomatosis is an extremely rare tumor with very few documented responses to treatment. A 3-year-old male with a complex past medical history, including prematurity and shunted hydrocephalus, was diagnosed with primary meningeal melanomatosis with peritoneal implants. Molecular testing revealed an NRAS Q61R mutation. The patient received proton craniospinal radiation followed by immunotherapy with nivolumab (1 mg/kg) and ipilimumab (3 mg/kg) IV every 3 weeks and, upon progression, he was switched to a higher dose of nivolumab (3 mg/kg IV every 2 weeks) and binimetinib (24 mg/m2/dose, twice a day). The patient had significant improvement of CNS disease with radiation therapy and initial immunotherapy but progression of extracranial metastatic peritoneal and abdominal disease. Radiation was not administered to the whole abdomen. After two cycles of nivolumab and treatment with the MEK inhibitor binimetinib, he had radiographic and clinical improvement in abdominal metastasis and ascitis. He ultimately died from RSV infection, Klebsiella sepsis, and subdural hemorrhage without evidence of tumor progression. This is the first report of a child with primary meningeal melanomatosis with extracranial metastatic disease with response to a combination of radiation, immunotherapy and MEK inhibitor therapy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.379
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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