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Record W4406071558 · doi:10.1016/j.jtct.2024.12.021

Donor Type Does Not Impact Late Graft Failure Following Reduced-Intensity Allogeneic Hematopoietic Cell Transplantation with Post-Transplant Cyclophosphamide-Based Graft-Versus-Host Disease Prophylaxis

2025· article· en· W4406071558 on OpenAlexaff
Cindy Lynn Hickey, Mei‐Jie Zhang, Mariam Allbee-Johnson, Rizwan Romee, Navneet S. Majhail, Monzr M. Al Malki, Joseph H. Antin, Cara L. Benjamin, Christopher Bredeson, Saurabh Chhabra, Michael R. Grunwald, Yoshihiro Inamoto, Christopher G. Kanakry, Filippo Milano, Robert J. Soiffer, Scott R. Solomon, Stephen R. Spellman, Claudio G. Brunstein, Corey Cutler

Bibliographic record

VenueTransplantation and Cellular Therapy · 2025
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsOttawa HospitalMemorial University of Newfoundland
FundersNational Institute of Environmental Health SciencesNational Cancer Institute
KeywordsHematopoietic cellMedicineGraft-versus-host diseaseCyclophosphamideHematopoietic stem cell transplantationDiseaseTransplantationSurgeryOncologyImmunologyHaematopoiesisInternal medicineChemotherapyStem cellBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Post-transplant cyclophosphamide (PTCy) is a commonly used graft-vs-host disease (GVHD) prophylaxis, particularly in the setting of haploidentical (haplo) hematopoietic cell transplantation (HCT). The rate of graft failure has been reported to be as high as 12% to 20% in haplo-HCT recipients using PTCy. The objective of this study was to determine whether donor type influenced the risk of late graft failure following reduced-intensity conditioning (RIC) HCT using PTCy-based GVHD prophylaxis. STUDY DESIGN: A retrospective cohort analysis using the Center for International Blood and Marrow Transplant Research (CIBMTR) database among adult patients who underwent first RIC haplo or 8/8 matched unrelated donor (MUD) HCT between 2011 and 2018 for acute myeloblastic leukemia (AML), acute lymphoblastic leukemia (ALL) or myelodysplastic syndrome (MDS) with PTCy GVHD prophylaxis. The primary outcome was incidence of late graft failure, defined as secondary graft loss in the absence of relapse or poor graft function requiring a cellular therapy intervention. RESULTS: A total of 1336 patients met the eligibility criteria (1151 haplo, 185 MUD). Patients in the MUD group were older (65 vs. 61 years), less ethnically diverse (95% vs. 72% White), received fewer bone marrow grafts (45% vs. 16%), and had younger donors (median age, 28 vs. 37 years old). Conditioning regimens were predominately fludarabine, cyclophosphamide, and total body irradiation (TBI; 87% haplo and 38% MUD). At 2 years, the adjusted probabilities of late graft failure for the haplo group was 6.5% (95% confidence interval [CI], 5.2-8.0) versus 5.9% (95% CI, 2.7%-10.9%) for the MUD group (P = .79). Multivariate analysis for risk factors associated with late graft failure found associations with a diagnosis of MDS (HR, 1.98; 95% CI, 1.22-3.20; P = .005), and earlier year of HCT (2015-2018 vs. 2011-2014; HR, 0.39; 95% CI, 0.24-0.64; P = .0002). A post-hoc sensitivity analysis was performed to evaluate the effect of donor age and use of peripheral blood stem cell (PBSC) grafts. Graft failure did not differ between haplo and MUD HCT (HR, 1.19; P = .67) when adjusted for donor age nor when restricted to PBSC grafts only (HR, 0.85; P = .70). CONCLUSION: In this registry-based analysis of patients undergoing RIC HCT for AML, ALL, or MDS using GVHD prophylaxis with PTCy, there was no significant difference in late graft failure rates between haplo and MUD donors. Overall rates of late graft failure were high.

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)0.001
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.010
GPT teacher head0.247
Teacher spread0.237 · 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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Citations3
Published2025
Admission routes1
Has abstractno

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