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Record W4407976323 · doi:10.1016/j.jtct.2025.01.450

Gvhd Prophylaxis with ATG and Ptcy Vs Ptcy-Based Regimens in Haploidentical Stem Cell Transplantation: A Cell Therapy Transplant Canada Registry Study

2025· article· en· W4407976323 on OpenAlexaffabout
Alejandro Garcia‐Horton, Kristjan Paulson, Grace Musto, Matthew D. Seftel, Tony H. Truong, Kevin A. Hay, Anca Prica, Sita Bhella, Ivan Pašić

Bibliographic record

VenueTransplantation and Cellular Therapy · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity of TorontoUniversity of CalgaryCanadian Blood ServicesCancerCare ManitobaPrincess Margaret Cancer CentreUniversity of ManitobaJuravinski HospitalJuravinski Cancer Centre
Fundersnot available
KeywordsMedicineTransplantationStem cellOncologyGraft-versus-host diseaseInternal medicineImmunologyBiology

Abstract

fetched live from OpenAlex

Introduction Allogeneic stem cell transplantation using a related haploidentical donor (haploSCT) is an alternative option for patients without a suitable fully matched donor. Post-transplant cyclophosphamide-based (PTCy) prophylaxis is the most used regimen in Canada to prevent graft-vs-host disease (GVHD) in haploSCT. Although effective at preventing severe forms of acute (aGVHD) and chronic GVHD (cGVHD), efforts remain to optimize this regimen to further decrease risks without increasing non-relapse mortality (NRM) or relapse. The Princess Margaret Cancer Centre (PMCC) transplant program has added anti-thymocyte globulin (ATG)(4.5mg/kg over days -3 to -1) to PTCy (50mg/kg/day on days +3 and +4) as their standard regimen in haploSCT. Thus, we sought to compare haploSCT outcomes between ATG+PTCy and PTCy-based regimens in the Canadian context. Methods We conducted a retrospective study using data from PMCC (ATG+PTCy-based cohort) and the Cell Therapy Transplant Canada (CTTC) registry (PTCy-based cohort). Adult recipients of a haploSCT for a hematologic malignancy in a Canadian centre between 2016-2023 were included. The Kaplan-Meier method was used to estimate OS and GVHD-relapse free survival (GRFS). Cumulative incidence functions were used for relapse, NRM, aGVHD, and cGVHD estimation. Results A total of 385 patients were included, with 148 receiving ATG+PTCy and 237 PTCy. Transplant indications were AML (51%), MDS (18%), ALL (15%), lymphoma (8%), and MPNs (8%). Median age was 58 years and 62% were male. Karnofsky Performance Status (KPS) was >80% in 72% of the patients. Myeloablative conditioning was utilized in 36% of transplants. Primary disease was the most common cause of death in the cohort. ATG+PTCy resulted in less moderate or severe cGVHD as assessed by NIH consensus criteria when compared to PTCy (2-year cumulative incidence (CI) 11% vs 23%; 95%CI 1.2-3.4; p=0.009). There was no difference in grade 2-4 aGVHD (CI 22% vs 30%; 95%CI 0.84-1.83; p=0.29). No difference was found in 2-year OS (56% vs 61%; 95%CI 0.2-1.18; p=0.25), 2-year GRFS (44% vs 45%; 95%CI 0.72-1.08; p=0.24), or 2-year CI of relapse (25% vs 28%; 95%CI 0.76-1.33; p=0.97). 2-year NRM was higher when ATG+PTCy was used as compared to PTCy alone (27% vs 18%; 95%CI 0.42-0.99; p=0.047). Conclusion This study is the largest real-world cohort to compare ATG+PTCy and PTCy-based GVHD prophylaxis regimens in haploSCT recipients. We show that combining ATG+PTCy significantly decreases the incidence of moderate to severe cGVHD without impacting relapse, OS, or GRFS. This possibly translates into improvements in recipients’ quality of life and healthcare utilization. The addition of ATG to PTCy was associated with an increased incidence of NRM. More data are required to optimize a promising prophylactic regimen in this group of patients.

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)0.002
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 score0.377
Threshold uncertainty score0.758

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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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Citations1
Published2025
Admission routes2
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