Case Report: A Presentation of Early-Onset Immune-Mediated Bullous Pemphigoid in a Patient with Urothelial Cancer
Bibliographic record
Abstract
Cutaneous immune-related adverse events (cirAEs) are the most common side effects of immune checkpoint inhibitor (ICI) therapy (30-50% for all grades). The vast majority of them are low or mild and can be treated without ICI interruption. Autoimmune blistering disorders, such as immune-mediated bullous pemphigoid (IBP), are rare (<1%) but potentially serious conditions that must be early detected. The onset generally occurs within the first months of the treatment, and it appears to be more common with antiprogrammed death-1 or antiprogrammed ligand 1 (anti-PD1/PDL1) than with anticytotoxic T-lymphocyte-associated protein 4 (anti-CTLA4). We present a case of a three-day severe IBP onset after receiving the first cycle of atezolizumab. This exceptional early presentation could suggest the presence of some predisposing condition and demonstrates the need to better understand predictive toxicity-related biomarkers in candidate patients for immunotherapy.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".