Melanoma-Associated Retinopathy Treated with Ipilimumab Therapy
Bibliographic record
Abstract
Melanoma-associated retinopathy (MAR) is a rare autoimmune syndrome in patients with melanoma characterized by visual disorders. MAR is induced by the degeneration of bipolar cells of the retina and the presence of serum autoantibodies against retina proteins. Ipilimumab, an anti-cytotoxic T lymphocyte-associated antigen 4 antibody, improves survival in previously treated patients with metastatic melanoma, but is responsible for a spectrum of immune-related adverse events. Administration of ipilimumab to patients with autoimmune diseases (such as MAR or vitiligo) is actually not recommended. We report a patient presenting with MAR occurring during a melanoma relapse. Surgery and chemotherapy had no effect on visual acuity and melanoma increased. In the absence of alternative antitumoral treatment, we focused on the vital prognosis and treated the patient with ipilimumab. Two years after the treatment the patient is free from new metastasis but has presented with exacerbation of vitiligo and MAR. In the very rare case of melanoma with autoimmune disease without a therapy option, ipilimumab could be discussed, taking into account the fact that it can be effective on tumor burden but can also increase autoimmunity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".