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Record W2913874211 · doi:10.1016/j.bbmt.2018.12.379

Combination of ATG and Post-Transplant Cyclophosphamide for Gvhd Prophylaxis in Matched and Mismatched Donor Peripheral Blood Stem Cell Transplants for Myeloid Malignancies

2019· article· en· W2913874211 on OpenAlexaff
Shruti Prem, Maria Queralt Salas Gay, Arjun Law, Wilson Lam, Santhosh Thyagu, Fotios V. Michelis, Dennis Dong Hwan Kim, Jeffrey H. Lipton, Rajat Kumar, Auro Viswabandya

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2019
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineFludarabineInternal medicineCyclophosphamideThymoglobulinGastroenterologyBusulfanCohortMyeloidHematopoietic stem cell transplantationTransplantationSurgeryChemotherapyTacrolimus

Abstract

fetched live from OpenAlex

Introduction ATG and post-transplant cyclophosphamide (PTCy) have been individually shown to be efficacious in reducing rates of GVHD in HLA matched and mismatched transplants. We adopted a combination regimen of ATG and PTCy for GVHD prophylaxis in HLA matched and mismatched transplants for myeloid malignancies in our centre, to decrease the rates of acute and chronic GVHD. Objectives We assessed the overall and progression free survival, incidence of acute and chronic GVHD, relapse rates and non-relapse mortality with this protocol. Patients and Methods Reduced intensity conditioning protocol consisted of iv Fludarabine, iv Busulphan, and low dose TBI. GVHD prophylaxis was with Thymoglobulin total dose 4.5mg/kg, PTCy total dose 100 mg/kg and cyclosporine. The stem cell source was G-CSF stimulated PBSCs. Results 169 patients (median age 58 y, range 19-74y) with high-risk myeloid malignancies (AML-64.5%, MDS-19%, MPN-12%) were treated with this protocol after obtaining institutional approval. The donor types were as follows-10/10 matched unrelated donor (MUD) in 67, 9/10 mismatched unrelated (MMUD) in 24, 10/10 matched related donor(MRD) in 35 and haplo-identical (HI) donors in 43 patients. The median follow-up in the entire cohort was 12 months. The 1year OS in the MUD, MMUD, MRD and HI groups were 73%, 54%, 74% and 56% respectively and the corresponding 1 year PFS were 66%, 38%, 49% and 51% respectively. The percentage of graft failure (primary and/or secondary) in the 4 groups were 1.5%, 12.5%, 0% and 16.3% respectively. The relapse rates were 21% in MUD, 42% in MMUD, 29% in MRD and 14% in HI groups. The MMUD patients had significantly inferior OS (p=0.03), and PFS (p=0.003), and significantly higher risk of relapse(p=0.009), compared to MUD patients. The overall incidence of grade 3-4 acute GVHD in our patients was 10 % and of moderate/severe NIH stage chronic GVHD was 11.6% which is low compared to conventional GVHD prophylaxis regimes. The percentages for grade 3-4 acute GVHD according to donor type were 16.4% in MUD, 4.2% in MMUD, 5.8% in MRD and 9.3% in HI groups and that of moderate/severe NIH stage chronic GVHD were 7.5%, 8.4%, 11.4% and 16.3% respectively. There were high rates of viral reactivation observed with this dual T lymphocyte suppression strategy. The overall incidences of CMV, and EBV reactivation and BK cystitis were 48%, 33% and 17% respectively. In addition, there were 12 pathologically confirmed cases of post-transplant lympho-proliferative disorder. Conclusion Our experience shows that PT-Cy and ATG can be combined for GVHD prophylaxis in PBSCTs for high risk myeloid malignancies and results in low rates of Gr3-4 acute GVHD and moderate/severe chronic GVHD across different donor types with acceptable relapse rates. High rates of viral re-activation are a concern and need close monitoring.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 spread0.216 · 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
Published2019
Admission routes1
Has abstractyes

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