Mast Cell Leukemia: Comprehensive Review of Literature With Current Insights and Updates on Management
Bibliographic record
Abstract
Mast cell leukemia (MCL) is an exceedingly rare and aggressive variant of systemic mastocytosis (SM). MCL is classified as primary, occurring de novo without prior mast cell disorders or secondary, from a pre-existing SM, and acute aggressive form with C-findings that indicate organ damage or chronic indolent form without organ damage. 60-65% of cases are aleukemic with <10% circulating mast cells in the peripheral blood, and the rest of the cases are leukemic with >10% mast cells. Diagnosis is typically confirmed by bone marrow biopsy revealing greater than 20% atypical or immature mast cells (MC) in the smear. Specific MCL-targeted treatments are limited, and treatment modalities used for SM and acute myeloid leukemia (AML) have been tried in MCL with limited success and variable survival benefit. These include chemotherapeutic agents such as cladribine, cytarabine, daunorubicin, and interferon-alpha (IFN-alpha), immunomodulator therapies (thalidomide, cromolyn, and glucocorticoids), antibody drug conjugates, allogenic hematopoietic stem cell transplantation (HSCT), and targeted therapies (tyrosine kinase inhibitors). The management has significantly advanced since the implication of the KIT D816V mutation in the pathogenesis of SM and MCL. The two targeted therapies approved for MCL are midostaurin, a multikinase inhibitor, and avapritinib, a selective KIT D816V mutation-targeted tyrosine kinase inhibitor. Drugs that are under evaluation in clinical trials for MCL include bezuclastinib, ripretinib, elenestinib, brentuximab vedotin, and tagraxofusp. MCL has a poor prognosis with a median overall survival of around 1.5 years. Further advancements and research are essential to develop treatments that may enhance median OS. In this article, we conducted a systematic yet simplified review of MCL, focusing primarily on its clinical manifestations and recent updates on management. We also identified the areas that require further research and emphasized the aggressive nature and poor prognosis associated with this disease. Our aim is to enhance clinician awareness of MCL and contribute to the limited literature available on this extremely rare disease.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".