Cutaneous Immune-Related Adverse Events (irAEs) to Immune Checkpoint Inhibitors: A Dermatology Perspective on Management
Bibliographic record
Abstract
Immune checkpoint inhibitors have proven to be efficacious for a broad spectrum of solid organ malignancies. These monoclonal antibodies lead to cytotoxic T-cell activation and subsequent elimination of cancer cells. However, they can also lead to immune intolerance and immune-related adverse event (irAEs) that are new and specific to these therapies. Cutaneous irAEs are the most common, arising in up to 34% of patients on PD-1 inhibitors and 43% to 45% on CTLA-4 inhibitors. The most common skin manifestations include maculopapular eruption, pruritus, and vitiligo-like lesions. A grading system has been proposed, which guides management of cutaneous manifestations based on the percent body surface area (BSA) involved. Cutaneous irAEs may prompt clinicians to reduce drug doses, add systemic steroids to the regiment, and/or discontinue lifesaving immunotherapy. Thus, the goal is for early identification and concurrent management to minimize treatment interruptions. We emphasize here that the severity of the reaction should not be graded based on BSA involvement alone, but rather on the nature of the primary cutaneous pathology. For instance, maculopapular eruptions rarely affect <30% BSA and can often be managed conservatively with skin-directed therapies, while Stevens-Johnson syndrome (SJS) affecting even 5% BSA should be managed aggressively and the immunotherapy should be discontinued at once. There is limited literature available on the management of the cutaneous irAEs and most studies present anecdotal evidence. We review the management strategies and provide recommendations for psoriatic, immunobullous, maculopapular, lichenoid, acantholytic eruptions, vitiligo, alopecias, vasculitides, SJS/toxic epidermal necrolysis, and other related skin toxicities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".