A comparison of allogeneic bone marrow transplantation, autologous bone marrow transplantation, and aggressive chemotherapy in children with acute myeloid leukemia in remission: a report from the Children's Cancer Group
Bibliographic record
Abstract
Intensive, myelosuppressive therapy is necessary to maximize outcomes for patients with acute myeloid leukemia (AML). A comparison was made of 3 aggressive postremission approaches for children and adolescents with AML in a randomized trial, CCG-2891. A total of 652 children and adolescents with AML who achieved remission on 2 induction regimens using identical drugs and doses (standard and intensive timing) were eligible for allocation to allogeneic bone marrow transplantation (BMT) based on matched related donor status (n = 181) or randomization to autologous BMT (n = 177) or to aggressive high-dose cytarabine-based chemotherapy (n = 179). Only 115 patients (18%) refused to participate in the postremission phase of this study. Overall compliance with the 3 allocated regimens was 90%. At 8 years actuarial, 54% +/- 4% (95% confidence interval) of all remission patients remain alive. Survival by assigned regimen ("intent to treat") is as follows: allogeneic BMT, 60% +/- 9%; autologous BMT, 48% +/- 8%; and chemotherapy, 53% +/- 8%. Survival in the allogeneic BMT group is significantly superior to autologous BMT (P =.002) and chemotherapy (P =.05); differences between chemotherapy and autologous BMT are not significant (P =.21). No potential confounding factors affected results. Patients receiving intensive-timing induction therapy had superior long-term survival irrespective of postremission regimen received (allogeneic BMT, 70% +/- 9%; autologous BMT, 54% +/- 9%; chemotherapy, 57% +/- 10%). Allogeneic BMT remains the treatment of choice for children and adolescents with AML in remission, when a matched related donor is available. For all others, there is no advantage to autologous BMT; hence, aggressive nonablative chemotherapy should be used.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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 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".