PIMASERTIB AND SEROUS RETINAL DETACHMENTS
Bibliographic record
Abstract
In Brief Purpose: To report a case of multifocal serous retinal detachments associated with pimasertib. Methods: The authors report a 26-year-old patient who developed bilateral multifocal serous retinal detachments appearing 2 days after starting pimasertib (as part of a clinical trial investigating its use in low-grade metastatic ovarian cancer) and rapidly resolving 3 days after stopping it. Conclusion: The mechanism of MEK inhibitor induced visual toxicity remains unclear. The pathophysiology of multifocal serous retinal detachments as a complication of pimasertib is still poorly understood. This is the first case that describes bilateral, multifocal central serous retinopathy appearing 2 days after starting pimasertib for ovarian cancer and rapidly resolving 3 days after stopping pimasertib. Pimasertib is an orally bioavailable MEK 1 and 2 inhibitor with potential antineoplastic activity, that is, currently used in clinical trials for ovarian cancer. Multifocal serous retinal detachments have been reported with the use of MEK 1 and 2 inhibitors. The authors report the development of multifocal serous retinal detachments with the use of pimasertib in a 26-year-old woman with metastatic low-grade serous ovarian cancer that was initially treated in 2010, with laparoscopic right oophorectomy. The tumor showed evidence of progression in 2011 for which a hysterectomy, left salpingo-oophorectomy, omentectomy, and removal of the metastatic disease from the diaphragm was performed. This was followed by six cycles of carboplatin and taxol, along with one cycle of maintenance bevacizumab. There was no other medical history. The pathophysiology of this complication is still poorly understood.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".