Improved survival in steroid‐refractory acute graft <i>versus</i> host disease after non‐myeloablative allogeneic transplantation using a daclizumab‐based strategy with comprehensive infection prophylaxis
Bibliographic record
Abstract
Approximately 15% of patients undergoing non-myeloablative allogeneic haematopoietical cell transplantation (NMHCT) develop steroid-refractory acute-graft versus host disease (aGVHD), a usually fatal complication. We encountered 18 cases of steroid-refractory aGVHD in 146 patients, undergoing NMHCT from a related human leucocyte antigen-compatible donor following cyclophosphamide/fludarabine-based conditioning. Our initial cohort of steroid-refractory aGVHD patients treated with antithymocyte globulin (ATG) and mycophenolate mofetil (regimen-1: n = 6) had high GVHD-related mortality. Therefore, we investigated an alternative strategy for subsequent patients developing this complication (regimen-2: n = 12), consisting of daclizumab (alone or combined with infliximab/ATG) and targeted broad spectrum antibacterial and aspergillus prophylaxis in conjunction with rapid tapering of steroids to minimize opportunistic infections. In a retrospective analysis, patients receiving regimen-2 were significantly more likely to have complete resolution of GVHD compared with those receiving regimen-1 [12/12 (100%) vs. 1/6 (17%); P < 0.001]. When compared with those receiving regimen-1, regimen-2 patients also had a higher probability of survival at day 100 (100% vs. 50%) and day 200 (73% vs. 17%) post-transplant, and improved overall survival (median 453 d vs. 42 d from aGVHD onset; P < 0.0001). GVHD-related mortality was 89% for regimen-1 patients vs. 17% for regimen-2 patients (P < 0.0001). These data suggest that a co-ordinated approach using immunoregulatory monoclonal antibodies, pre-emptive antimicrobial therapy and judicious steroid withdrawal can dramatically improve outcome in steroid-refractory aGVHD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".