Optimization of cytarabine (ARA-C) therapy for acute myeloid leukemia
Bibliographic record
Abstract
Cytarabine (cytosine arabinoside) is one of the most effective drugs for the treatment of acute myeloid leukemia. The standard dose of cytarabine used to treat this leukemia is 100 mg per square meter. In an attempt to improve the effectiveness of cytarabine against acute myeloid leukemia, a high-dose treatment (3,000 mg per square meter) was introduced into therapy. The side effects of high-dose cytarabine was a major concern, especially its neurological toxicity. A review of recent clinical trials indicates that this high-dose cytarabine can be replaced by the intermediate-dose of 1,000 mg per square meter without loss of efficacy and with less toxicity. This is an important step to improve the efficacy of cytarabine for the treatment of acute myeloid leukemia. Despite the improvements in the therapy for this leukemia, the current overall survival rate for adult patients is less than 30%. To optimize the cytarabine therapy, it is important to determine how some leukemic stem cells survive treatment. Preclinical data suggest that survival of the leukemic stem cells could be due to the long 12 hour interval between infusions of cytarabine, which permits some leukemic cells to escape its S phase specific action. Among the other factors that can lead to leukemic cell survival are the high levels in the liver and spleen of cytidine deaminase, the enzyme that inactivates cytarabine and drug resistance due to deficiency in deoxycytidine kinase, the enzyme that activates the prodrug, cytarabine. Several approaches are proposed in this commentary to overcome these impediments with the goal of increasing the effectiveness of cytarabine for the treatment of acute myeloid leukemia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 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".