Intermediate dose cytarabine improves survival and relapse-free rate compared with standard-dose cytarabine as post-remission treatment for acute myeloid leukemia
Bibliographic record
Abstract
ABSTRACT: The exact dose of cytarabine still remain controversial for the management of patients with acute myeloid leukemia (AML) after complete remission (CR), but recent studies favor lower doses. This study aimed to investigate the toxic effects of single-intermediate dose (ID) cytarabine in patients with AML after achieving CR, compared with standard-dose cytarabine.In this retrospective study, AML patients who achieved CR after consolidation therapy before enrollment between 07/2008 and 05/2019 were included. All patients were divided into single-ID cytarabine and standard-dose cytarabine. The Kaplan-Meier method was used to compare overall survival (OS) and relapse-free time (RFS). Cox regression models were used to assess factors independently associated with OS and RFS. The toxic side effects of hematology and non-hematology were observed.52 patients were enrolled. There were 33 in ID group, 19 in Standard dose group. The 3-year RFS rate (40.4% vs 22.2%, P = .031) was better in the ID group than in the standard-dose group, while the 3-year OS rate was not different between the 2 groups (50.2% vs 27.8%, P = .074). Treatment stratage of ID cytarabine chemotherapy significantly improve the prognosis of AML regardless of patient age, risk grade, WBC count. There were no significant differences between the 2 groups in grade 3 to 4 bone marrow suppression, gastrointestinal symptoms, blood transfusion, infections.Patients with AML receiving ID cytarabine showed better survival and similar toxicity profiles compared with patients who received standard-dose cytarabine.
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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) | 0.000 | 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 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".