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Effect of Donor on Outcomes after Myeloablative Conditioning with Daily IV Busulfan and Fludarabine (FLUBUP) +/− TBI with Thymoglobulin: Transplants from Mismatched Unrelated Donors (MMUD) Have Worse Survival Due to Higher Transplant-Related Mortality (TRM).

2006· article· en· W2587866926 on OpenAlexaff
James A. Russell, Leanne Kmet, Mary Lynn Savoie, Nizar J. Bahlis, M. Ahsan Chaudhry, Diana Quinlan, Michelle Geddes, A. Robert Turner, Loree Larratt, Christopher Brown, Jan Storek, Douglas A. Stewart

Bibliographic record

VenueBlood · 2006
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsFoothills Medical Centre
Fundersnot available
KeywordsThymoglobulinBusulfanFludarabineMedicineFolinic acidInternal medicineGastroenterologyTransplantationSurgeryHematopoietic stem cell transplantationChemotherapyOncologyUrologyCyclophosphamideKidney transplantationFluorouracil

Abstract

fetched live from OpenAlex

Abstract Historically myeloablative hematopietic stem cell transplants (SCT) from donors other than genotypically identical siblings (MRD) have had worse outcomes when the same conditioning and GVHD prevention is used. It is important to know if this is still the case when all patients receive better tolerated regimens, using i.v. rather than oral busulfan for example, and more aggressive GVHD prophyaxis. We have compared outcomes of pateints (pts) receiving myeloablative fludarabine/busulfan based conditioning (FLUBUP) between 05/99 and 05/05 according to donor. 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 daily days -5 to -2 inclusive +/− TBI 200cGy × 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. Patients were divided into four groups depending on donor - MRD, genotypically mismatched family members (MMRD), unrelated donors matched for HLA-A, -B, C, DR & DQ (MUD) and MMUD. Of 40 MMUD 32 were mismatched for one antigen, 7 for 2 and one for 3 at least at the allelic level. Baseline and transplant characteristics MRD MMRD MUD MMUD Number 201 22 81 40 Pt age (yrs) range/mean (SD) 18–66/45 (11.0) 19–63/44 (14.9) 16–61/40 (12.3) 19–64/40 (12.2) Donor age (yrs) range/mean (SD) 15–71/44 (11.1) 10–65/35 (19.1) 19–57/32 (8.5) 21–54/33 (8.2) Male pt % 63.7 54.6 58.0 65.0 Low risk (Acute leukemia CR1/2, CML CP1) % 41.8 54.6 55.6 32.5 TBI % (not risk factor for TRM) 23.9 31.8 42.0 47.5 Blood cell SCT % 87.6 90.9 43.2 65.0 Female to male SCT % 26.9 27.3 19.8 30.0 CMV+ve donor or recipient % 77.1 54.6 69.1 55.0 CD34+ cell dose/kg - range/median (IQR) 0.8–13.6/4.7(3.4–6.0) 2.0–10.3/4.1(3.3–6.9) 0.4–23.9/3.7(2.4–7.7) 0.9–17.7/5.0(3.0–7.0) Five-year survival (OS) estimates (95% CI) were MRD 60% (52%–67%), MMRD 58% (34%–75%), MUD 57% (45%–67%), MMUD 38% (23%–53%). By Cox regression analysis MRD, MMRD and MUD SCT had similar outcomes and were combined for a more robust analysis. The hazard ratio for OS for MMUD vs all others was 2.03 (95% CI 1.31–3.16, p = 0.002). After adjusting for gender, risk group, patient age (continuous), donor age (continuous), TBI, stem cell source, female donor to male recipient, CMV status and CD34+ cell dose (continuous) the hazard ratio was 1.69 (1.04–2.74) (p = 0.03). The cumulative incidence of relapse mortality was silmiar across all 4 groups, the difference in outcome was mostly attributable to TRM. Thus the cumulative incidence of TRM at 3 years was 31.6% (17.5%–46.7%) for MMUD vs 14.5% (10.8%–18.8%) for all others. We conclude that the FLUBUP protocol +/− TBI with Thymoglobulin gives comparable OS for recipients of SCT from all donors apart from MMUD and patients should be advised of the increased risk when the latter donors are the only ones available.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.007
GPT teacher head0.234
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2006
Admission routes1
Has abstractyes

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