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Outcome of Stem Cell Transplantation for Pediatric Acute Lymphoblastic Leukemia: Comparison of Matched Related Donor Verses Matched Unrelated Donor. Important Role of Graft Versus Host Disease in Preventing Relapse.

2004· article· en· W2556106584 on OpenAlexaff
Adam Gassas, Lillian Sung, Prabodha Kumar Das, Jonanne K. Hitzler, Ronald Grant, Sheila Weitzman, John Doyle

Bibliographic record

VenueBlood · 2004
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineTransplantationTotal body irradiationMethotrexateCyclophosphamideGraft-versus-host diseaseGastroenterologySurgeryInternal medicineLeukemiaStem cellAcute lymphocytic leukemiaAcute leukemiaLymphoblastic LeukemiaChemotherapyBiology

Abstract

fetched live from OpenAlex

Abstract Seventy percent of children with acute lymphoblastic leukemia (ALL) who benefit from stem cell transplantation (SCT) lack a human leukocyte antigen (HLA) matched related donor (MRD). For these children SCT from a matched unrelated donor (MUD) represents an alternative therapeutic option. Our objective was, to review the outcome of children (0–18years) with ALL whom received a fully matched marrow allografts at our institution between July 1998 - December 2003. All children were conditioned with cyclophosphamide (50mg/kg infused over 1 hour daily for 4 days) followed by fractionated total body irradiation (TBI; 1200cGy, 6 fractions over 3 days). Cyclosporine A and a short course of methotrexate were used for graft versus host disease (GVHD) prophylaxis. Results: We performed 23 fully MRD and 23 fully MUD SCT during the study period. Median age at time of SCT was 10.2 y (range 2.2–17.5) and 8.2 y (range 1–16.5) for the MRD and MUD groups, respectively. Remission status at time of SCT; For the MRD group, complete remission (CR) 1, 2 and 3 were 5, 15 and 3 patients, respectively. For the MUD group, CR 1, 2 and 3 were 6, 14 and 3 patients, respectively. All patients engrafted for neutrophils (defined as absolute neutrophil count (ANC) of > 0.5 x 109/l for 2 consecutive days) with a median time of 18 days (range 12–28) and 16 days (range 10–25) for the MRD and MUD groups, respectively. In both groups, low grade acute(a) GVHD (I-II) occurred in 50% of the cases. However, high grade aGVHD (III-IV) occurred in 7/23 patients in the MUD group compared to only 1 patient with grade III aGVHD in the MRD group. Three years event free survival (EFS) for the whole group was 47 ± 8% with overall survival (OS), 50 ± 8%. EFS (3y) according to remission status was; 64 ± 15% for CR1, 51 ± 10% for CR2 and 33 ± 19% for CR3, P = 0.06. Twelve out of thirteen deaths in the MRD group were caused by leukemia relapse versus 3 out of 8 deaths in the MUD group. Transplant related mortality (TRM) was 5/8 deaths in the MUD group versus 1/13 deaths in the MRD group. Three years EFS and overall survival (OS) were, 37 ± 11%, 39 ± 11% for the MRD group and 63 ± 10%, 64 ± 10% (P = 0.16) for the MUD group. For the whole group, EFS according to aGVHD was, 29 ± 15% for no aGVHD, 51 ± 11% for low grade aGVHD and 60 ± 15% for high grade. Conclusion: Acute graft versus host disease is associated with less relapse post SCT for pediatric ALL, presumably through a graft-versus-leukemia effect. Our data suggests that outcomes can be improved further through exploring means of inducing aGVHD while reducing the toxicity of SCT. In MRD SCT where the likelihood of aGVHD is less and therefore relapse rate is higher, and in order to maximize survival in the non aGVHD group, attempts for aGVHD induction by early manipulation of the immunosuppressive medications or a low dose pre-emptive donor lymphocyte infusion in the first 60 days post engraftment, need to be explored in future studies.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.016
GPT teacher head0.282
Teacher spread0.266 · 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
Published2004
Admission routes1
Has abstractyes

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