Systemic Treatment of Cutaneous Adverse Events after Immune Checkpoint Inhibitor Therapy: A Review
Bibliographic record
Abstract
As treatment with immune checkpoint inhibitors (CPIs) for cancer increases, so has the incidence of immune-related cutaneous adverse events (irCAEs). These toxicities can significantly impact quality of life and may be dose-limiting. Current guidelines for irCAEs offer only corticosteroids or CPI discontinuation. Evidence supports biologic immunomodulatory therapies when corticosteroids fail or need avoidance. A review of literature from 2010 to 2020 yielded 45 articles, resulting in 185 irCAEs, including bullous pemphigoid-like eruption (n = 55), psoriasis/psoriasiform dermatitis (n = 41), and maculopapular rash (n = 31). Treatments included immunomodulators, intravenous immunoglobulin, aprepitant, acitretin, tetracyclines, and biologic agents. Overall, 92.3% of patients saw improvement or resolution of their rash. Bullous pemphigoid-like eruptions were treated with a tetracycline +/- niacinamide (94.7% success [18/19]), omalizumab (100% success [7/7]), and rituximab (100% success [10/10]). Although prospective research is required, this review provides a comprehensive list of successful, non-corticosteroid treatment options for irCAEs to improve compliance with lifesaving cancer therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".