Prospective Case Series of Cutaneous Adverse Effects Associated With Dabrafenib and Trametinib
Bibliographic record
Abstract
BACKGROUND: Dabrafenib, a novel selective small-molecule inhibitor of BRAF, has been shown to increase overall survival in patients with unresectable metastatic melanoma harboring the BRAF V600E mutation. The development of resistance has led to combination therapy with selective MEK inhibitor trametinib. Compared with vemurafenib, dabrafenib is a more recent BRAF inhibitor approved by the Food and Drug Administration in May 2013 for metastatic melanoma; fewer data are available in the current literature regarding cutaneous toxicity. OBJECTIVES: We sought to present additional cutaneous side effects of dabrafenib and trametinib and follow their evolution and management. METHODS: We carried out a prospective study of 14 patients treated with dabrafenib alone or with trametinib. Patients were followed every 4 weeks, and we collected detailed cutaneous symptoms, photos, and biopsy specimens. RESULTS: All patients presented with at least 1 adverse skin reaction. The mean duration of treatment was 24 weeks. The most common adverse effect was papillomas (7/14), followed by palmoplantar hyperkeratosis (5/14), alopecia (5/14), and seborrheic dermatitis-like eruption (2/14). Three patients who received trametinib developed an acneiform eruption (3/5). One patient developed a keratoacanthoma-like squamous cell carcinoma. Side effects presented as early as 2 weeks after starting therapy, with a mean time of onset of 9 weeks. CONCLUSION: Selective BRAF inhibitor dabrafenib and MEK inhibitor trametinib are associated with multiple skin adverse effects. Given their recent approval and the potential for malignant lesions to develop on treatment, awareness of potential adverse effects and their management is necessary.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".