Drugs associated with development of porokeratosis: A systematic review
Bibliographic record
Abstract
Porokeratosis is a rare disorder characterized by atrophic macules or patches, with a well-defined ridge-like hyperkeratotic border called cornoid lamella. Although the exact pathogenesis is unknown, drug associated cases have recently been reported in the literature. As such, we systematically reviewed and identified drugs associated with drug-induced porokeratosis, their resultant effects, and whether there was a casual relationship between the use of a drug and the development of porokeratosis. We searched for articles which reported drug-induced porokeratosis in MEDLINE and Embase in June 2020. After full-text review, 25 studies were included for analysis. We identified 26 patients with drug-induced porokeratosis. The most common therapies associated with development of porokeratosis is biologic use, phototherapy, and radiotherapy. The most common clinical variants were the disseminated superficial or actinic types (60%), which occurred in psoriasis patients undergoing phototherapy, and eruptive disseminated type (24%) which occurred in the context of biologic therapies. The Naranjo score ranged from possible to probable for the identified treatments. Clinicians should consider drug reactions as possible triggering events for porokeratosis, especially for patients taking biologics, phototherapy, and radiotherapy. Large-scale studies are required to confirm our findings and further explore the pathogenesis for drug-induced porokeratosis.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".