Immunotherapy for myelodysplastic syndrome and acute myeloid leukemia: where do we stand?
Bibliographic record
Abstract
INTRODUCTION: Myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) are generally characterized by a poor prognosis with currently available therapies. Immunotherapies have already seen success in treating a variety of malignant disorders, and their role in managing myeloid cancers is evolving rapidly. AREAS COVERED: This is a review of the immunotherapies tested in MDS and AML, including immune checkpoint inhibitors, bispecific antibodies, and cell therapies such as chimeric antigen receptor (CAR) T cell therapy, T cell receptor (TCR) engineered T cells, and natural killer (NK) cells, with a focus on clinical trials conducted to date and future directions. EXPERT OPINION: Initial clinical trials exploring checkpoint inhibitors in MDS and AML have demonstrated high toxicity and disappointing efficacy. However, ongoing trials adding novel checkpoint inhibitors to standard therapy are more promising. Technological advances are improving the outlook for bispecific antibodies, and cellular therapies like adoptive NK cell infusion have favorable efficacy and tolerability in early trials. As our understanding of the immune microenvironment in MDS and AML improves, the role for immunotherapy in the treatment of these diseases will become clearer.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".