Pretransplant Blinatumomab Improves Outcomes in B Cell Acute Lymphoblastic Leukemia Patients Who Undergo Allogeneic Hematopoietic Cell Transplantation
Bibliographic record
Abstract
BACKGROUND: Blinatumomab, a bispecific monoclonal antibody, effectively controls refractory B cell acute lymphoblastic leukemia (ALL) and promotes measurable residual disease (MRD) negativity. This study investigated the impact of pretransplant blinatumomab on allogeneic hematopoietic cell transplantation (HCT) outcomes in B cell ALL patients. METHODS: We analyzed the effect of pretransplant blinatumomab on transplant outcomes of 117 adults undergoing allogeneic HCT for B cell ALL at Princess Margaret Hospital, Toronto, between 2010 and 2021. Outcomes assessed included overall survival (OS), graft-versus-host disease and relapse-free survival (GRFS), cumulative incidences of relapse (CIR), and nonrelapse mortality (NRM). RESULTS: The median follow-up was 36 months. Thirty-one participants (26.5%) received blinatumomab. Blinatumomab group had higher proportions of individuals with high disease risk index, primary induction failure and was more likely to receive dual T cell depletion with antithymocyte globulin and post-transplant cyclophosphamide. Two-year OS, GRFS, NRM, and CIR in the blinatumomab and nonblinatumomab groups were, respectively: 65.4% versus 45.6% (P = .05), 42.2% versus 17.3% (P = .01), 3.2% versus 43.0% (P = .007) and 34.4% versus 14.4% (P = .02). Blinatumomab was associated with a lower incidence of day-100 grade 2 to 4 and grade 3 to 4 acute graft-versus-host disease (aGVHD): 27.5% versus 56.7% (P = .009), and 10.9% versus 34.7% (P = .04), respectively. Multivariate analysis confirmed the association between pretransplant blinatumomab and improved OS and NRM. CONCLUSIONS: Pretransplant blinatumomab is associated with improved OS and lower risk of NRM in B cell ALL patients undergoing allogeneic HCT, likely reflecting lower burden of treatment-related toxicity in this population. Larger prospective trials are warranted to validate our findings.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".