Photosensitivity From Avapritinib: Pharamacovigilance Analysis
Bibliographic record
Abstract
Certain protein kinase inhibitors have been reported to cause photosensitivity. Avapritinib is a tyrosine kinase inhibitor that was approved in January 2020. The aim of this analysis was to determine if a statistically significant signal exists between Avapritinib and photosensitivity in the real-world population. A disproportionality analysis was conducted using the Food and Drug Administration Adverse Event Reporting System (FAERS) from January 1, 2020, to December 31, 2021. A literature review was also performed to identify case reports of Avapritinib-induced photosensitivity. A total of 13 adverse event reports with Avapritinib as the drug and photosensitivity as the reaction were identified in FAERS. Avapritinib was the suspect drug in all 13 reports, and in 12 of the 13 reports, Avapritinib was the only drug listed. Disproportionality analysis found a proportional reporting ratio of 11.0, χ21=107, reporting odds ratio of 11.0, and a lower limit of the 95% CI of the information component of 2.1. The literature review found 1 case report of Avapritinib-induced photosensitivity in a patient who had been taking Avapritinib 300 mg daily for 5 months. A statistically significant signal was found between Avapritinib use and photosensitivity. Clinicians should continue to balance the benefits and risks when prescribing Avapritinib to patients.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".