Management of Uveal Melanoma: A Consensus-Based Provincial Clinical Practice Guideline
Bibliographic record
Abstract
INTRODUCTION: Survival in uveal melanoma has remained unchanged since the early 1970s. Because outcomes are highly related to the size of the tumour, timely and accurate diagnosis can increase the chance for cure. METHODS: A consensus-based guideline was developed to inform practitioners. PubMed was searched for publications related to this topic. Reference lists of key publications were hand-searched. The National Guidelines Clearinghouse and individual guideline organizations were searched for relevant guidelines. Consensus discussions by a group of content experts from medical, radiation, and surgical oncology were used to formulate the recommendations. RESULTS: Eighty-four publications, including five existing guidelines, formed the evidence base. SUMMARY: Key recommendations highlight that, for uveal melanoma and its indeterminate melanocytic lesions in the uveal tract, management is complex and requires experienced specialists with training in ophthalmologic oncology. Staging examinations include serum and radiologic investigations. Large lesions are still most often treated with enucleation, and yet radiotherapy is the most common treatment for tumours that qualify. Adjuvant therapy has yet to demonstrate efficacy in reducing the risk of metastasis, and no systemic therapy clearly improves outcomes in metastatic disease. Where available, enrolment in clinical trials is encouraged for patients with metastatic disease. Highly selected patients might benefit from surgical resection of liver metastases.
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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 | 0.017 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".