Spectrum of Immune Checkpoint Inhibitor Anemias: Results From a Single Center, Early-Phase Clinical Trials Case Series Experience
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Immune checkpoint inhibitor anemias (ICI-A) are a rare entity which can be potentially life-threatening without prompt identification. The goal of the study is to characterize the presentation, evaluation, and outcomes of ICI therapy in early phase clinical trial setting to guide future research and to develop standardized care guidelines. Retrospective chart review of 333 patients who participated in early phase clinical trials at the University of Texas MD Anderson Cancer Center revealed four cases with ICI-A between 2016 and 2020. We identified a spectrum of four cases which included ICI-related autoimmune hemolytic anemias, hemophagocytic lymphohistiocytosis and thrombotic microangiopathy as a result of combinatory investigational therapies involving ICI. Patient presentation, evaluation, bone marrow pathology, interventions, and clinical course were reviewed. The median time to onset of hematological immune-related adverse events (heme-irAEs) in this retrospective series was 3.5 weeks (2 - 6 weeks). One patient had pre-existing untreated chronic lymphocytic leukemia. Glucocorticoids are an effective first-line treatment in most patients although most patients were not rechallenged but successfully had complete recovery and pursued further non-immunotherapy-based therapies. Cognizance of ICI-A in clinical trial setting is paramount to early recognition of heme-irAEs. Further research is needed to identify and stratify risk factors during clinical trial enrollment and optimal management strategies for immune-mediated hematologic toxicities.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 it