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Trends in volumes and survival after hematopoietic cell transplantation in racial/ethnic minorities

2024· article· en· W4395465396 on OpenAlexfundno aff
Nandita Khera, Sikander Ailawadhi, Ruta Brazauskas, Jinalben Patel, Benjamin Jacobs, Celalettin Üstün, Karen K. Ballen, Muhammad Bilal Abid, Miguel Ángel Díaz, A. Samer Al‐Homsi, Hasan Hashem, Sanghee Hong, Reinhold Munker, Raquel M. Schears, Hillard M. Lazarus, Stefan O. Ciurea, Sherif M. Badawy, Bipin N. Savani, Baldeep Wirk, Charles F. LeMaistre, Neel S. Bhatt, Amer Beitinjaneh, Mahmoud Aljurf, Akshay Sharma, Jan Černý, Jennifer M. Knight, Amar H. Kelkar, Jean A. Yared, Tamila L. Kindwall‐Keller, Lena E. Winestone, Amir Steinberg, Staci D. Arnold, Sachiko Seo, Jaime M. Preussler, Nasheed Hossain, Warren Fingrut, Vaibhav Agrawal, Shahrukh K. Hashmi, Leslie Lehmann, William A. Wood, Hemalatha G. Rangarajan, Wael Saber, Theresa Hahn

Bibliographic record

VenueBlood Advances · 2024
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsnot available
FundersCancer MoonshotNational Institute of Environmental Health SciencesNational Institute of Allergy and Infectious DiseasesOffice of Naval ResearchPharmacyclicsTakeda OncologyGenentechHealth Resources and Services AdministrationNational Institutes of HealthMorphoSysLegend BiotechSangamo TherapeuticsBeiGeneAstellas PharmaAdaptive BiotechnologiesKiadis Pharmabluebird bioAtara BiotherapeuticsNovavaxJazz PharmaceuticalsStemCyteaTyrCSL BehringSt. Jude Children's Research HospitalHistoGeneticsCareDxActinium PharmaceuticalsNational Cancer InstituteGilead SciencesMoonshot Research and Development ProgramSanofiGlaxoSmithKlineBristol-Myers SquibbAstraZenecaGateway for Cancer ResearchSwedish Orphan BiovitrumOmeros CorporationVertex PharmaceuticalsAlexion PharmaceuticalsMallinckrodt PharmaceuticalsAstellas Pharma USAmgenNational Heart, Lung, and Blood InstituteNovartis Pharmaceuticals CorporationIncytePfizer
KeywordsEthnic groupHematopoietic cellHaematopoiesisTransplantationHematopoietic stem cell transplantationMedicineDemographyImmunologyInternal medicineBiologyStem cellPolitical scienceGeneticsSociologyLaw

Abstract

fetched live from OpenAlex

ABSTRACT: There has been an increase in volume as well as an improvement in overall survival (OS) after hematopoietic cell transplantation (HCT) for hematologic disorders. It is unknown if these changes have affected racial/ethnic minorities equally. In this observational study from the Center for International Blood and Marrow Transplant Research of 79 904 autologous (auto) and 65 662 allogeneic (allo) HCTs, we examined the volume and rates of change of autoHCT and alloHCT over time and trends in OS in 4 racial/ethnic groups: non-Hispanic Whites (NHWs), non-Hispanic African Americans (NHAAs), and Hispanics across 5 2-year cohorts from 2009 to 2018. Rates of change were compared using Poisson model. Adjusted and unadjusted Cox proportional hazards models examined trends in mortality in the 4 racial/ethnic groups over 5 study time periods. The rates of increase in volume were significantly higher for Hispanics and NHAAs vs NHW for both autoHCT and alloHCT. Adjusted overall mortality after autoHCT was comparable across all racial/ethnic groups. NHAA adults (hazard ratio [HR] 1.13; 95% confidence interval [CI] 1.04-1.22; P = .004) and pediatric patients (HR 1.62; 95% CI 1.3-2.03; P < .001) had a higher risk of mortality after alloHCT than NHWs. Improvement in OS over time was seen in all 4 groups after both autoHCT and alloHCT. Our study shows the rate of change for the use of autoHCT and alloHCT is higher in NHAAs and Hispanics than in NHWs. Survival after autoHCT and alloHCT improved over time; however, NHAAs have worse OS after alloHCT, which has persisted. Continued efforts are needed to mitigate disparities for patients requiring alloHCT.

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 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)0.000
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 score0.138
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.282
Teacher spread0.269 · 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 teacher head, 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".

Quick stats

Citations19
Published2024
Admission routes1
Has abstractyes

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