Prophylactic or Preemptive Low-Dose Azacitidine and Donor Lymphocyte Infusion to Prevent Disease Relapse following Allogeneic Transplantation in Patients with High-Risk Acute Myelogenous Leukemia or Myelodysplastic Syndrome
Bibliographic record
Abstract
Because of the persistently high rates of relapse of patients with high-risk acute myelogenous leukemia (AML) and myelodysplastic syndrome (MDS) following allogeneic hematopoietic stem cell transplantation (allo-HSCT), post-transplantation maintenance therapy has been proposed. We previously initiated a Phase II trial in which epigenetic therapy was combined with immunotherapy in an attempt to reduce disease relapse. In that study, low-dose azacitidine (AZA) and escalating doses of donor lymphocyte infusion (DLI) were given as post-allo-HSCT maintenance treatment. In the present study, we retrospectively analyze a larger cohort of patients receiving post-transplantation maintenance therapy and provide updates on some patients of the earlier study. The objectives of the present study were to analyze the cumulative incidence of relapse (CIR), overall survival (OS), and progression-free survival (PFS) and the incidence of acute and chronic graft-versus-host disease (GVHD) of patients with high-risk AML or MDS receiving post-transplantation maintenance treatment with AZA with or without DLI. We retrospectively analyzed 77 patients (54 with AML, 23 with MDS) considered at high risk based on either their genomic or clinical status at transplantation. Following allogeneic transplantation, they received at least 1 cycle of prophylactic or preemptive low-dose AZA with or without escalating doses of DLI to prevent disease relapse. Almost one-half of the patients (47%) were able to receive the full 12 cycles of scheduled AZA, and a majority (79%) received at least 1 DLI. With a median follow-up of 24 months, 19 patients (25%; 16 with AML, 3 with MDS) relapsed, at a median of 9.8 months (range, 4 to 58.6 months), giving a 22% CIR at 24 months. OS and PFS at 24 months were 70.8% and 68.3%, respectively. The cumulative incidences of grade II-IV acute GVHD and chronic GVHD were 27.4% and 45%, respectively. Only a minority of patients (11%) required delayed administration of AZA. These findings confirm that AZA-DLI maintenance is both tolerable and effective in reducing the risk of post-transplantation relapse.
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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) | 0.000 | 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".