Current and emerging treatment options for uveal melanoma
Bibliographic record
Abstract
Patricia Rusa Pereira,1 Alexandre Nakao Odashiro,2 Li-Anne Lim,1 Cristina Miyamoto,1 Paula L Blanco,4 Macanori Odashiro,3 Shawn Maloney,1 Dominique F De Souza,1 Miguel N Burnier Jr1 1The Henry C Witelson Ocular Pathology Laboratory, McGill University, Montreal, QC, Canada; 2Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada; 3Federal University of Mato Grosso do Sul, Campo Grande, MS, Brazil; 4Department of Pathology and Laboratory Medicine, University of Ottawa, ON, Canada Abstract: Uveal melanoma (UM) is the most common primary malignant intraocular tumor in adults, with a 10-year cumulative metastatic rate of 34%. The most common site of metastasis is the liver (95%). Unfortunately, the current treatment of metastatic UM is limited by the lack of effective systemic therapy. Options for the management of the primary intraocular tumor include radical surgery as well as conservative treatments in order to preserve visual acuity. For metastatic disease, several approaches have been described with no standard method. Nevertheless, median survival after liver metastasis is poor, being around 4–6 months, with a 1-year survival of 10%–15%. In this review, the authors summarize current and promising new treatments for UM. Keywords: uveal melanoma, choroidal melanoma, eye, metastasis, treatment, therapy
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".