Outcome of Myeloablative Conditioning and Unrelated Donor Hematopoietic Cell Transplantation for Childhood Acute Lymphoblastic Leukemia in Third Remission
Bibliographic record
Abstract
We conducted a retrospective study of 155 children who underwent unrelated donor hematopoietic cell transplantation (HCT) between 1990 and 2005 for acute lymphoblastic leukemia in third remission. The median patient age was 11 years, the median time from diagnosis to first relapse was 36 months, and the median time from first relapse to second relapse was 26 months. Stem cell sources were bone marrow (n = 115), peripheral blood (n = 11), and cord blood (n = 29). All patients received a myeloablative pretransplantation conditioning regimen. The 5-year estimates of leukemia-free survival, relapse, and nonrelapse mortality were 30%, 25%, and 45%, respectively. In multivariate analysis, the only risk factor associated with relapse was the interval between the first relapse and the second relapse. Second relapses occurring >26 months from the first relapse were associated with lower risk for post-HCT relapse compared with second relapses occurring at ≤26 months (relative risk, 0.4; P = .01). Relapse risk was lowest when late second relapse was preceded by late first relapse (>36 months from diagnosis), as demonstrated by a 3-year relapse rate of 9% (P = .0009). Our data indicate that long-term leukemia-free survival can be achieved in children with acute lymphoblastic leukemia in third remission using unrelated donor HCT, especially when the second relapse occurs late.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".