Less Is More: Superior Graft-versus-Host Disease-Free/Relapse-Free Survival with Reduced-Intensity Conditioning and Dual T Cell Depletion in Acute Myelogenous Leukemia
Bibliographic record
Abstract
In this study, we compared the outcomes of patients with acute myelogenous leukemia (AML) in complete remission treated with myeloablative conditioning (MAC) and those treated with reduced-intensity conditioning (RIC) before allogeneic hematopoietic stem cell transplantation (allo-HCT). In addition, we explored the efficacy of dual T cell depletion using anti-thymocyte globulin (ATG) and post-transplantation cyclophosphamide (PTCy) for the prevention of graft-versus-host disease (GVHD) in patients undergoing RIC allo-HCT. Our study cohort comprised 356 adults with AML in complete remission who underwent allo-HCT between 2013 and 2018. One hundred eleven patients (31.2%) received a MAC regimen, and 245 (68.8%) received an RIC regimen. One hundred seventy-one of the patients who received an RIC regimen (68.4%) received ATG, PTCy, and cyclosporine (ATG-PTCY-CsA) for GVHD prophylaxis in accordance with our institutional protocol. Data were collected retrospectively and updated in July 2019. With a median follow-up of 14.5 months (range, 0 to 76 months), 161 patients (45.2%) died, and 66 (18.5%) relapsed. Two-year overall survival (OS), relapse-free survival (RFS), and GVHD-free/RFS (GRFS) were 55%, 52.6%, and 35%, respectively. The intensity of the conditioning regimen, with or without ATG-PTCY-CsA, did not have a significant impact on OS and RFS. However, RIC in combination with ATG-PTCY-CsA was associated with a significantly lower cumulative incidence of acute GVHD and chronic GVHD. The use of RIC with ATG-PTCy-CsA was a significant predictor for higher GRFS secondary to the reduction of clinically relevant GVHD (P= .0001). In patients with AML, RIC allografts and dual T cell modulation with ATG and PTCy led to superior GRFS. The use of this GVHD prophylaxis strategy, along with mitigation of conditioning toxicity using RIC, may result in better long-term quality of life for allo-HCT recipients.
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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) | 0.000 | 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".