Allogeneic, but not autologous, hematopoietic cell transplantation improves survival only among younger adults with acute lymphoblastic leukemia in first remission: an individual patient data meta-analysis
Bibliographic record
Abstract
Hematopoietic cell transplantation (HCT) and prolonged chemotherapy are standard postremission strategies for adult acute lymphoblastic leukemia in first complete remission, but the optimal strategy remains controversial. There are no randomized trials of allogeneic HCT. In the present study, updated individual patient data were collected and analyzed from studies with information on availability of matched sibling donor (used to mimic randomization) and from randomized trials of autograft versus chemotherapy. Data from 13 studies including 2962 patients, excluding Philadelphia chromosome-positive patients, showed a survival benefit for having a matched sibling donor for patients < 35 years of age (OR = 0.79; 95% CI, 0.70-0.90, P = .0003) but not for those ≥ 35 years of age (OR = 1.01; 95% CI, 0.85-1.19, P = .9; heterogeneity P = .03) because of the higher absolute risk of nonrelapse mortality for older patients. No differences were seen by risk group. There was a trend toward inferior survival for autograft versus chemotherapy (OR = 1.18; 95% CI, 0.99-1.41; P = .06). No beneficial effect of autografting was seen compared with chemotherapy in this analysis. We conclude that matched sibling donor myeloablative HCT improves survival only for younger patients, with an absolute benefit of approximately 10% at 5 years. Improved chemotherapy outcomes and reduced nonrelapse mortality associated with allogeneic HCT may change the relative effects of these treatments in the future.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.047 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".