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Record W4224303257 · doi:10.1017/cts.2022.125

236 Optimizing Haploidentical Donor Selection for Pediatric Hematopoietic Cell Transplant

2022· article· en· W4224303257 on OpenAlex
Nicole Liberio, Bronwen E. Shaw, Greg Yanik, Muna Qayed, Kirk R. Schultz, Larisa Broglie

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Clinical and Translational Science · 2022
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesOffice of Naval ResearchLegend BiotechPharmacyclicsTakeda OncologyHealth Resources and Services AdministrationMorphoSysSeagenSwedish Orphan BiovitrumVertex PharmaceuticalsOmeros CorporationAstellas PharmaAdaptive BiotechnologiesPfizerIncyteKiadis Pharmabluebird bioMedacJazz PharmaceuticalsBeiGeneHistoGeneticsAtara BiotherapeuticsCareDxActinium PharmaceuticalsNational Cancer InstituteGilead SciencesSanofiNational Heart, Lung, and Blood InstituteNovartis Pharmaceuticals CorporationCSL BehringBristol-Myers SquibbAstraZenecaGateway for Cancer ResearchAlexion PharmaceuticalsMallinckrodt PharmaceuticalsAstellas Pharma USAmgen
KeywordsMedicineSiblingLogistic regressionTransplantationOncologyInternal medicineCohortGraft-versus-host diseaseHematopoietic cellHematopoietic stem cell transplantationPopulationRetrospective cohort studyIncidence (geometry)HaematopoiesisStem cell

Abstract

fetched live from OpenAlex

OBJECTIVES/GOALS: Patients who require a hematopoietic cell transplant (HCT) and dont have an HLA-matched related or unrelated donor may rely on a haploidentical donor. The optimal haploidentical donor and guidance for selection is limited. We aim to determine how donor characteristics affect outcomes following haploidentical-HCT for pediatric patients. METHODS/STUDY POPULATION: This is a retrospective cohort study evaluating the effect of donor age and relationship on post-HCT outcomes in children (0-18y) from 2008-2018. Multivariable logistic regression analysis will identify if donor age or donor relationship affect the development of graft-versus-host-disease (GVHD), while adjusting for other patient, donor, and transplant related variables. Two-year overall survival & event-free survival will be determined using Kaplan-Meier curves, stratified by donor age group and donor relationship, and compared by log-rank testing. Sub-analyses will be performed for myeloablative transplants and reduced intensity conditioning, as well as for malignant and non-malignant diseases. RESULTS/ANTICIPATED RESULTS: Our primary aim to is determine the effect of donor age and the effect of donor relationship to patient on the development of GVHD. We hypothesize that utilization of a younger donor will decrease the incidence of GVHD. Further, we hypothesize that utilizing a sibling haploidentical donor will result in less GVHD than a parental donor. Secondary aims include evaluating the effect of donor age and donor relationship on overall survival, event-free survival, non-relapse mortality, relapse, graft failure and time to engraftment. The results of this study will help us to develop criteria for optimal haploidentical donor selection. If donor selection is optimized, this could result in improved outcomes following haploidentical transplants. DISCUSSION/SIGNIFICANCE: Haploidentical donors are increasingly used as many patients, especially ethnic minorities, do not have an HLA-matched donor. This will be the largest study of haploidentical HCT in children. The data gathered will allow us to identify important donor characteristics to help guide physician decision-making when choosing a haploidentical donor.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.084
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0000.000

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 head0.047
GPT teacher head0.355
Teacher spread0.308 · 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