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Effective Strategy to Prevent Acute Graft-Versus-Host Disease in Unrelated Donor Allogeneic Hematopoietic Cell Transplants By Using a Combination of Anti-Thymocyte Globulin (ATG), Post-Transplant Cyclophosphamide and Cyclosporine

2016· article· en· W2745093822 on OpenAlexaff
Uday Deotare, David Loach, Fotios V. Michelis, Dennis Dong Hwan Kim, Santhosh Thyagu, Jeffrey H. Lipton, Hans A. Messner, Auro Viswabandya

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineAnti-thymocyte globulinCyclophosphamideGraft-versus-host diseaseHematopoietic stem cell transplantationInternal medicineTransplantationCalcineurinBusulfanImmunologyCohortGastroenterologyStem cellChemotherapyBiology

Abstract

fetched live from OpenAlex

Abstract Introduction:Acute Graft-versus-Host Disease (aGVHD) is a frequent complication of Allogeneic Hematopoietic cell transplants (allo-HCT); aGVHD, especially Grade III-IV, can be lethal with increased morbidity and mortality and can occur in upto 40-50% of allo-HCT. GVHD prophylaxis has been used for control of GVHD, with use of calcineurin inhibitors, anti-metabolites and anti T cell antibodies. Use of Post-transplant Cyclophosphamide (PTCy) has recently been used extensively in haplo-identical transplant setting with promising results. However, PtCy has mainly been used in patients with BM as the stem cell source. In those patients with PBSC as the stem cell source, alone PTCy has been associated with clinically significant acute and chronic GVHD. As most of our patients use PBSC as the graft source, we hypothesized to combine both ATG and PTCy to reduce incidence of both acute and chronic GVHD in our patient cohort. Here we present a small cohort data using a combination of all these agents to effectively reduce aGVHD in hematological malignancies.. Methods:A total of 28 patients with hematological malignancies, who had an unrelated donor underwent allo-HCT at our center from 1 Oct 2015 to 31 Mar 2016. The characteristics of the patients are summarized in Table 1. The conditioning regimen was either myeloablative (MAC, namely FBT400) or Reduced Intensity (RIC, namely FBT200) in patients with age ≤ 60 and >60 years, respectively. After interim analysis when increased non-hematological toxicity was observed in the MAC arm, all patients subsequently received FBT 200 conditioning. Peripheral blood was used as the stem cell source in all patients. Filgrastim was used from day +7 onwards for 13 patients. Special emphasis was given to incidence of acute GVHD, infections, regimen related toxicities and engraftment. Results:Out of total of 28 patients, aGVHD was seen in only 6 (21.4%) patients, five of which had skin involvement (Grade I-II) and one suspected liver involvement (Grade III), all of which responded rapidly to steroids. However, we did observe increased toxicities such as sinusoidal obstruction syndrome (32%), bacterial infections (68%) and viral infections (46%; CMV reactivations in 64%). Primary disease relapse, secondary graft failure and EBV reactivations were seen in 10% of cases, with documented Post Transplant Lymphoproliferative Disorder (PTLD) in only 2 patients. The overall survival of the entire cohort was 67.8% with a median duration of 6 months (range; 3-8 months). In comparison to MAC, RIC regimen was found to be superior with no Gr III-IV aGVHD, less toxicity and improved survival (RIC-82% vs MAC-45%). Conclusions: Combination of ATG-PTCy-CsA is an effective strategy to reduce aGVHD in unrelated donor transplants, albeit with moderate increase in toxicities. RIC with this combination was associated with less organ damage and superior survival. However, a long term follow up is needed to assess relapse and cGVHD. Disclosures No relevant conflicts of interest to declare.

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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 head0.247
Teacher spread0.239 · 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 designNon-randomized trial
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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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