Drugs Associated With the Development of Palmoplantar Keratoderma: A Systematic Review
Bibliographic record
Abstract
Background Palmoplantar keratoderma (PPK) are a heterogenous group of hereditary and acquired disorders that are characterized by excessive epidermal thickening of the palms and/or soles. PPK has been described as a rare adverse event for some medications. The aim of this systematic review was to summarize outcomes in PPK associated with various medications. This data will assist dermatologists and other healthcare providers treating patients with drug-induced PPK. Methods EMBASE and MEDLINE databases were searched in accordance with PRISMA guidelines using the keyword “palmoplantar keratoderma.” 40 studies met the inclusion criteria. Results A total of 247 patients (mean age: 57.0 years) were included in the analysis. Among patients whose sex was reported, 60.3% ( n = 35/58) were male. PPK most frequently developed after treatment with BRAF inhibitors (73.7%, n = 182/247), BRAF inhibitors combined with MEK1/2 inhibitors (15.4%, n = 38/247), tyrosine kinase inhibitors (TKIs) (3.2%, n = 8/247), or chemotherapy (2.4%, n = 6/247). The mean latency period between initiation of the drug and onset of PPK was 7.6 months (range: 0.25-90 months). Improvement of PPK was reported in 24 cases, with 50% ( n = 12/24) achieving complete resolution and 50% ( n = 12/24) achieving partial resolution. All patients who achieved complete resolution stopped the suspected drug, with a mean resolution period of 2.4 months (range: 2 weeks-6 months). The most common treatments for PPK were keratolytic treatments ( n = 10) and topical corticosteroids ( n = 4). Conclusions PPK was most frequently associated with targeted kinase inhibitors, specifically BRAF, MEK1/2, and tyrosine kinase inhibitors.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".