Sequential Use of Prednisolone and Cyclosporine Is Effective in the Management of Immunotherapy-Related Hemolytic Anemia
Bibliographic record
Abstract
Immune checkpoint inhibitors (CPIs) can cause immune-related organ dysfunctions, including nephritis, pneumonitis, thyroiditis, hepatitis, colitis and more rarely hematological toxicities like immune-related autoimmune hemolytic anemia (irAIHA). Very few cases of irAIHA associated with immunotherapy have been reported, and treatment protocols remain unclear. This is partly because not all irAIHA cases are Coomb's test positive. Causes of anemia in cancer patients undergoing treatment with chemotherapy with or without immunotherapeutic agents can also be multiple. This makes it difficult to initially diagnose irAIHA, especially when CPIs are used concurrently with chemotherapy. Once alternate causes have been ruled out, a treatment plan for irAIHA is initiated based on grade of the anemia. Grade 1-2 irAIHA cases are managed with supportive interventions. However, cessation of therapy is recommended for life-threatening (grade 4) toxicity, severe (grade 3) toxicity that is recurring, or moderate (grade 2) toxicity that does not resolve with appropriate treatment for 3 months. Management of irAIHA usually involves methylprednisolone for 2 - 4 weeks with a slow taper after hemoglobin has normalized. But some cases do not respond to steroids alone and require cessation of immunotherapy or selecting alternate immunosuppressive agents. We report a protocol for treatment of grade 4 irAIHA secondary to programmed death protein 1 (PD-1) blocker pembrolizumab.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".