Transplant-Related Mortality in Patients ≥50 Years of Age Is No Lower after Transplantation from Young Fully Matched Unrelated Donors (MUD) Than from Matched Siblings When All Patients Are Given the FLUBUP Regimen with Thymoglobulin.
Bibliographic record
Abstract
Abstract There are reports indicating that older patients (pts) may have better outcomes after stem cell transplantation (SCT) from young fully matched unrelated donors (MUD) than from matched siblings (MRD) perhaps because of donor age. In some of these studies MUD and MRD recipients may have been treated differently, for example with more intense GVHD prophyaxis for MUD SCT such as antithymocyte globulin (ATG). We have compared outcomes of SCT pts receiving myeloablative fludarabine & busulfan based conditioning (FLUBUP) between 05/99 and 05/05. Only 10/10 (HLA–A, −B, C, DR & DQ) matched SCT were considered. Recipients of MRD SCT were ≥50 years old, MUD SCT recipients were unselected for age but their donors were ≤30 years old. All pts received fludarabine 50mg/m2 on days −6 to −2 and IV busulfan (Busulfex, PDL Pharma) at a myeloablative dose of 3.2 mg/kg once daily days −5 to −2 inclusive (FLUBUP) +/− TBI 200cGy x 2 on day −1 or 0. Prophylaxis for GVHD was cyclosporine A, methotrexate with folinic acid and Thymoglobulin (Genzyme) 4.5 mg/kg in divided doses over 3 consecutive days pretransplant finishing D0.[table 1]These data demonstrate that TRM for older SCT pts given the FLUBUP regimen with ATG is similar to that for adults in general transplanted from young MUD. When using these protocols in older pts there is usually no justification for the expense and inconvenience of using a young MUD in preference to a matched sibling. Patient, donor & SCT characteristics and outcomes Unrelated Related p * at 5 years Number 41 63 Patient age median (range) 44 (16–61) 55 (50–65) <0.0001 Donor age median (range) 24 (19–30) 52 (37–71) <0.0001 Low risk (Acute leukemia CR1/2, CML CP1) 22 (54%) 14 (22%) 0.0015 CMV+ve recipient or donor 31 (76%) 53 (84%) ns Female to male SCT 8 (20%) 18 (29%) ns Blood cells 20 (49%) 56 (89%) <0.0001 CD 34+ cell dose x 10e6 median (range) 5.35 (0.91–15.47) 4.23 (0.83–13.52) 0.08 TBI (not TRM risk factor) 19 (46%) 10 (16%) 0.0014 Acute GVHD II–IV 21±7% 16±5% ns Acute GVHD III–IV 10±5% 5±3% ns Chronic GVHD 64±7% 61±9% ns Pts≥50 TRM * 26±15% (n = 12) 16±5% ns Low risk TRM 5±5% 0% ns High risk TRM 31±12% 23±7% ns BCT TRM 10±7% 19±6% ns All pts TRM 16±6% 16±5% ns
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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) | 0.002 | 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".