Current Clinical Practice: Acute Myeloblastic Leukemia: Management with High-Dose Cytosine Arabinoside, Daunorubicin and Marrow Transplantation
Bibliographic record
Abstract
Combination high-dose cytosine arabinoside (ARA-C) and daunorubicin (DNR) for primary remission induction of patients with acute myeloblastic leukemia (AML) was evaluated in a single institution study. Patients aged 55 or less with an HLA-sibling received an allogeneic bone marrow transplant (alloBMT) in first remission; other responders were offered autologous BMT (autoBMT). For remission induction 93 patients aged less than 60 received DNR 45 mg/m(2) BSA x 3 and ARA-C 2 gm/m(2) BSA every 12 hours for 12 doses; 53 aged 60 or older DNR 25 mg/m(2) daily x 3 and ARA-C 1.5-2.0 gm/m(2) BSA every 12 hours for 12 doses. Consolidation doses of DNR were the same but ARA-C 100 mg/m(2) BSA/day x 5 was given by continuous intravenous infusion. The complete remission rate for patients less than 60 years was 69.9% (95% CI: 59.5-79.0%) and 47.2% (95% CI: 33.3-61.4%) for the older patients. The median duration of first remission for the younger patients was 13.0 months and of overall survival 17.9 months; for patients over 60 years 5.6 and 10.0 months respectively. Disease-free survival and overall survival of the 19 patients receiving alloBMT and the 13 patients undergoing autoBMT aged less than 55 years and in first or second complete remission were significantly increased compared with 22 patients in remission but not having BMT (p < 0.001 and p < 0.013). The results support the effectiveness of high-dose ARA-C for remission induction, a need for intensive consolidation therapy and a role for BMT in the management of AML.
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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 | 0.001 |
| 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 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".