MétaCan
Menu
Back to cohort
Record W3153591551 · doi:10.5693/djo.02.2020.06.001

Rapid growth of primary uveal melanoma following intravitreal bevacizumab injection: a case report and review of the literature

2020· review· en· W3153591551 on OpenAlexaff
BMSc Jingyi, Kelsey A. Roelofs, Laurie Russell, Ezekiel Weis, MDCM Sylvia H. Chen

Bibliographic record

VenueDigital Journal of Ophthalmology · 2020
Typereview
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineBevacizumabOphthalmologyHyphemaCiliary bodyMelanomaIntraocular pressureMetastasisNeovascularizationSurgeryCancerInternal medicineChemotherapyAngiogenesis

Abstract

fetched live from OpenAlex

Uveal melanoma size is a significant predictor of tumor metastasis. Although the relationship between antivascular endothelial growth factors (VEGF) and uveal melanoma growth has been studied, results are paradoxical, and the relationship remains controversial. We report the case of a 65-year-old man who presented with elevated intraocular pressure in his right eye, neovascularization of his iris, and significant corneal edema, which obscured the view of the angle. Given his history of proliferative diabetic retinopathy, he was diagnosed with neovascular glaucoma and subsequently received an intravitreal injection of bevacizumab and underwent Ahmed valve insertion. This was complicated by postoperative hyphema. Two and a half months postoperatively, a mass involving the inferior iris and ciliary body became visible, and fine-needle aspiration biopsy confirmed uveal melanoma. Seven weeks after diagnosis, the tumor's largest basal diameter had increased from 2.51 mm to 18.0 mm, and apical height increased from 6.23 mm to 11.0 mm. His right eye was enucleated. Histopathological analysis showed discontinuous invasion next to the Ahmed valve. Tumor progression after injection raises the possibility that in some untreated uveal melanomas, accelerated growth may occur following exposure to anti-VEGF agents.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.232
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.323
Teacher spread0.296 · 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
GenreReview

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

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueDigital Journal of OphthalmologySame topicOcular Oncology and TreatmentsFrench-language works237,207