Ocular adverse events following <scp>CAR‐T</scp> cell therapy: A pharmacovigilance study and systematic review
Bibliographic record
Abstract
The rise of immuno-oncology, including the use of chimeric antigen receptor T-cell (CAR-T) therapy is bringing in a new wave of cancer treatments, particularly in hematologic malignancies. However, data on their adverse events, particularly of the eye, is under-reported. To assess the ocular adverse events associated with the six FDA-approved CAR-T cell therapies, a disproportionality analysis utilizing the FAERS database was conducted from the first quarter of 2017 to the third quarter of 2023, as well as a systematic review of case reports of ocular events following CAR-T cell therapy up to December 20, 2023. A total of 53 ocular adverse events were identified from the FDAs FAERS database. The adverse events most frequently observed were mydriasis and xerophthalmia with tisagenlecleucel (Kymriah). The systematic review resulted in 8 case reports encompassing 19 patients which included a total of 27 events. This study demonstrates the importance of anticipation of potential ocular adverse events by ophthalmologists and oncologists as they can greatly contribute to morbidity in patients with cancer.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".