Safety and efficacy of allogeneic hematopoietic stem cell transplantation in R/R B-NHL patients with disease progression after CAR-T therapy
Bibliographic record
Abstract
Abstract Background: R/R B-NHL patients with disease progression after CAR-T therapy have poor prognosis and no standard chemotherapy regimen has been defined. We aimed to explore whether receiving allo-HSCT could improve the outcomes of R/R B-NHL patients who have disease progression after CAR-T therapy.Methods: From October 2017 to June 2021, we retrospectively report outcomes of R/R B-NHL patients with disease progression after CAR-T cell treatment, then receiving allo-HSCT. Results: Among 9 patients, 4 were males and 5 females, with a median age of 44 (27-52) years. 5 patients were diagnosed refractory/relapsed diffuse large B cell lymphoma, 1 patient was Burkitt lymphoma, 1 was B lymphoblastic lymphoma, 1 was transformed DLBCL and 1 was gray zone lymphoma. 8/9 donors were haploidentical family member, 1/9 donor was identical sibling. The median time from CAR-T treatment to transplantation was 2.3 (1.0-12.3) months. 9/9 patients obtained complete engraftment. The median time of neutrophil implantation was 12 (11- 19) days, and 13 (9-20) days of platelet implantation. The median follow-up was 7.9 (3.4-48.6) months. 4/9 patients received CR and 1/9 patient received PR during the follow up. The objective response rate (ORR) was 55.6%. The six-months overall survivaln (OS) and progression-free survival (PFS) were 66.7% and 33.3%, respectively. 1 case experienced acute graft-versus-host disease（aGVHD）grade Ⅱ, 1 case with aGVHD grade Ⅲ. Among 5 survivals, localized chronic GVHD occurred in 1 patient. During the follow up, four patients have died and the causes were disease relapses and progressions (2 patients), acute renal failure (1 patient), severe pulmonary infection (1 patient). No-relapse mortality was 22.2%.Conclusion: The present study demonstrated that allo- HSCT is a feasible and safe choice with favorable outcome for R/R B-NHL patients with disease progression after CAR-T therapy.
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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 | 0.001 |
| 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) | 0.000 | 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".