Safety of allogeneic hematopoietic cell transplant in adults after CD19-targeted CAR T-cell therapy
Bibliographic record
Abstract
Allogeneic hematopoietic cell transplantation (allo-HCT) is offered to selected patients after chimeric antigen receptor-modified T-cell (CAR-T) therapy. Lymphodepleting chemotherapy and CAR-T therapy have immunosuppressive and immunomodulatory effects that could alter the safety profile of subsequent allo-HCT. We reviewed our experience with 32 adults (acute lymphoblastic leukemia [ALL], n = 19; B-cell non-Hodgkin lymphoma [NHL]/chronic lymphocytic leukemia [CLL], n = 13) who received an allo-HCT after CAR-T therapy, with a focus on posttransplant toxicities. Myeloablative conditioning (MAC) was used in 74% of ALL patients and 39% of NHL/CLL patients. The median time from CAR-T therapy to allo-HCT was 72 days in ALL patients and 122 days in NHL/CLL patients. Cumulative incidences of grade 3-4 acute graft-versus-host disease (GVHD) and chronic GVHD were 25% and 10%, respectively. All patients had neutrophil recovery (median, 18.5 days) and all but 3 had platelet recovery (median, 12 days). Twenty-two percent had viral or systemic fungal infection within 100 days after allo-HCT. The 100-day and 1-year cumulative incidences of NRM were 16% and 21%, respectively, for ALL patients and 15% and 33%, respectively, for NHL/CLL patients. In ALL patients, later utilization of allo-HCT after CAR-T therapy was associated with higher mortality. In NHL/CLL patients, MAC was associated with higher mortality. Toxicities did not exceed the expected incidences in this high-risk population.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".