Severe Cytomegalovirus Gastritis after Pembrolizumab in a Patient with Melanoma
Bibliographic record
Abstract
Immunotherapy has emerged as a standard of cancer treatment, with an increasing number of indications. Recently, opportunistic infections have been reported in several cases in which immunotherapy has led to an increased susceptibility to infection. The present case is the first report of cytomegalovirus (cmv) gastritis occurring in a patient with melanoma during immunotherapy without immune-related adverse events (iraes) and without the use of immunosuppressant agents. A 43-year-old woman presented with stage iii malignant melanoma. She underwent wide excision of skin, with lymph node dissection, and she started immunotherapy with a 3-week cycle of pembrolizumab. The patient demonstrated stable disease response, and no iraes were observed during her initial treatment courses. However, after the 9th treatment cycle, she began to experience epigastric pain that worsened significantly, requiring a visit to the emergency centre. Imaging by computed tomography (ct) and integrated positron-emission tomography/ct revealed severe diffuse gastroduodenitis with acute pancreatitis. Esophagogastroduodenoscopy showed diffuse oozing, hemorrhagic, edematous, and exfoliative mucosa involving the entire gastric wall, defined as acute hemorrhagic gastritis. Biopsies of the gastric wall revealed cmv infection. Those findings were consistent with a diagnosis of cmv gastritis, and the patient received antiviral therapy with ganciclovir. After treatment, she recovered enough to resume immunotherapy. This case report presents a rare occurrence of cmv gastritis related to immunotherapy. As more patients are treated with immunotherapy, incidences of cmv infections are expected to increase; a high index of clinical suspicion is therefore needed in symptomatic patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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 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".