Inferior outcomes with reduced intensity conditioning followed by allogeneic hematopoietic cell transplantation in fit individuals with acute lymphoblastic leukemia: a Canadian single-center study and a comparison to registry data
Bibliographic record
Abstract
Allogeneic hematopoietic cell transplantation (HCT) can offer cure to some patients with acute lymphoblastic leukemia (ALL). It remains unclear how conditioning intensity affects transplant outcomes in ALL. In this retrospective study, we compared outcomes between 27 patients <60 who received reduced intensity conditioning (RIC) at Princess Margaret Hospital Cancer Center (PMCC) and 226 Cell Therapy Transplant Canada (CTTC) age-matched controls who received myeloablative conditioning (MAC) between 2007 and 2018. Compared to CTTC patients, PMCC patients had an inferior 2-y OS: 0.29 (95% CI: 0.11–0.49) vs 0.63 (0.56–0.70), HR = 2.10 (1.23–3.55), p = 0.006, higher TRM: 0.41 (0.22–0.60) vs 0.24 (0.18–0.30), HR = 2.00 (1.05–3.81), p = 0.04 and a trend toward increased risk of relapse: 0.36 (0.17–0.56) versus 0.17 (0.12–0.22), HR = 1.72 (0.82–3.62), p = 0.15. In multivariate analysis, RIC and the use of T-cell depletion (TCD) were associated with inferior OS. In ALL patients <60, the use of RIC with TCD is associated with inferior allogeneic HCT outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".