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Record W4402610887 · doi:10.1210/jcemcr/luae165

A Potential Role for Nivolumab in the Treatment of Fibrous Dysplasia-Related Pain

2024· article· en· W4402610887 on OpenAlexaff
Mohammad Jay, Cassandra Hawco, Stan Van Uum

Bibliographic record

VenueJCEM Case Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsNivolumabFibrous dysplasiaMedicineSurgeryInternal medicineImmunotherapyCancer

Abstract

fetched live from OpenAlex

Fibrous dysplasia (FD) is a chronic and progressive disorder of bone growth because of decreased osteoblast formation and osteoclast overactivity. Its main symptoms include pain, fracture, and irregular bone growth. Bisphosphonates are the mainstay of therapy for FD with a primary goal of pain relief. A 50-year-old woman presented to ophthalmology in March 2011 with intermittent proptosis, vertical diplopia, and orbital pain. A computed tomography scan of the head revealed a skull base lesion, which was confirmed to be fibrous dysplasia on bone biopsy. Because of significant headache, she was treated with IV pamidronate monthly starting November 2011, which led to pain reduction. Repeated attempts to decrease the frequency of pamidronate were unsuccessful because of breakthrough pain. Oral alendronate and risedronate did not control her symptoms. She remained on risedronate however because of its convenience. In August 2021, she was diagnosed with metastatic melanoma and started nivolumab. Her headache completely resolved for the first time in 10 years. Although nivolumab, a programmed death-1 blocker, has been used in the treatment of bone malignancy, it has not been previously studied in FD. By suppressing RANK ligand-related osteoclastogenesis, nivolumab decreases cancer-associated bone pain. Our case suggests a potential role for nivolumab in treating FD-associated pain.

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 score0.088
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.010
GPT teacher head0.271
Teacher spread0.261 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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