Cutaneous Adverse Events Associated with Immune Checkpoint Inhibitors: A Review Article
Bibliographic record
Abstract
Immune checkpoint inhibitors (ICIs) have emerged as novel options that are effective in treating various cancers. They are monoclonal antibodies that target cytotoxic T-lymphocyte antigen 4 (CTLA-4), programmed cell death 1 (PD-1), and programmed cell death-ligand 1 (PD-L1). However, activation of the immune systems through ICIs may concomitantly trigger a constellation of immunologic symptoms and signs, termed immune-related adverse events (irAEs), with the skin being the most commonly involved organ. The dermatologic toxicities are observed in nearly half of the patients treated with ICIs, mainly in the form of maculopapular rash and pruritus. In the majority of cases, these cutaneous irAEs are self-limiting and manageable, and continuation of the ICIs is possible. This review provides an overview of variable ICI-mediated dermatologic reactions and describes the clinical and histopathologic presentation. Early and accurate diagnosis, recognition of severe toxicities, and appropriate management are key goals to achieve the most favorable outcomes and quality of life in cancer patients.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".