Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) caused by niraparib: a novel antineoplastic agent
Bibliographic record
Abstract
BACKGROUND: Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) is a rare but potentially life-threatening hypersensitivity reaction characterized by skin rash, fever, lymphadenopathy, hematologic abnormalities, and organ involvement. Niraparib, a poly (ADP-ribose) polymerase (PARP) inhibitor, is used to treat ovarian, fallopian tube, or primary peritoneal cancer. Although niraparib is associated with cutaneous toxicities, no severe cutaneous adverse reactions (SCARs) have been reported until now. CASE PRESENTATION: We present a case of DRESS syndrome in a 73-year-old woman with high-grade serous ovarian cancer treated with niraparib. After 20 days of therapy, she developed a widespread maculopapular rash. Despite discontinuation of niraparib and treatment with corticosteroids, she exhibited pruritus, facial edema, lymphadenopathy, eosinophilia, and impaired liver and renal function. A RegiSCAR score of 6 confirmed the diagnosis of DRESS. Patch testing to niraparib 1% in DMSO was positive when performed nine weeks after DRESS resolution. CONCLUSIONS: This is the first reported case of DRESS by hypersensitivity due to niraparib. This case highlights the importance of recognizing DRESS as a potential adverse reaction to niraparib and the efficacy of early corticosteroid intervention. Further research is needed to understand and mitigate the risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".