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Enregistrement W4253348189 · doi:10.1182/blood-2019-126814

Genetic Ancestry and Skeletal Toxicities Among Childhood Acute Lymphoblastic Leukemia Patients in the DFCI 05-001 Cohort

2019· article· en· W4253348189 sur OpenAlexaff
Qianqian Zhu, Song Yao, Peter D. Cole, Justine M. Kahn, Marian H. Harris, Emily Schiller, Uma H. Athale, Luis A. Clavell, Caroline Laverdière, Jean‐Marie Leclerc, Bruno Michon, Marshall A. Schorin, Jennifer Welch, Stephen E. Sallan, Lewis B. Silverman, Kara M. Kelly

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Lymphoblastic Leukemia research
Établissements canadiensCentre hospitalier de l'Université LavalCentre Hospitalier Universitaire Sainte-JustineMcMaster UniversityMcMaster Children's Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineCumulative incidenceProportional hazards modelCohortEthnic groupInternal medicineIncidence (geometry)Hazard ratioGenetic genealogyDemographyOncologyPopulationConfidence interval

Résumé

récupéré en direct d'OpenAlex

Background: Despite outstanding cure rates of pediatric acute lymphoblastic leukemia (ALL), Blacks and Hispanics have inferior survival than Whites. We recently reported that among 794 children from DFCI ALL Consortium Protocol 05-001 trial, Hispanic patients had significantly lower rates of fracture and osteonecrosis, but higher risk of relapse and death compared with non-Hispanic Whites (PMID: 29090520). Studies from other groups have reported inferior ALL outcomes in children with Native American ancestry, however the association between genetic ancestry and skeletal toxicities has not been explored. We examined whether genetic inheritance could provide an explanation for the reduced incidence of skeletal toxicities in Hispanic patients in DFCI 05-001. Methods: A total of 576 DNA samples extracted from bone marrow samples or blood samples obtained during remission, including 2% blind duplicates, were genotyped using the Illumina OmniExpress Beadchip array. After data QC and cleaning, 449 ALL patients were retained in the final analysis. Estimates of global genetic ancestry were derived from STRUCTURE program, which was used to re-classify individuals with discordant clinical race/ethnicity as reported by study site, and to assign individuals with unknown race/ethnicity information to an ethnic group when possible. Regression model for the subdistribution hazard of the cumulative incidence function was used to relate clinical race/ethnicity, genetically reclassified race/ethnicity, and genetic ancestry respectively with risk of fracture and osteonecrosis, with death and recurrence as competing risk factors while controlling for age, gender and baseline clinical factors. Cox proportional regression models were used to test race/ethnicity and ancestry with overall survival (OS) and event-free survival (EFS). Results: Among the 449 patients analyzed, average age was 6.7 years; 26% of patients were ≥10 years and 44% were female. The demographic and clinical characteristics of patients with genotype data were similar to those of the overall cohort, although the proportion of Hispanics was slightly lower in the genotyped sub-cohort (17% vs. 21%), whereas the rates of fracture and osteonecrosis were higher (fracture: 25% vs. 18%; osteonecrosis: 10% vs. 8%). Based on clinical race/ethnicity, 66% of patients were non-Hispanic White, 17% were Hispanic, 5% were non-Hispanic Black, 3% were Asian, and 10% were reported as Other. Genetic ancestry analyses revealed that non-Hispanic White patients had a median of 96% European ancestry, non-Hispanic Black patients had a median of 76% African ancestry, and Asian patients had a median of 58% Asian ancestry. The genetic make-up of Hispanic patients in the 05-001 cohort was more admixed, with 23% Native American and 17% African ancestry, higher than the national average (18% and 6%, respectively). After genetic reassignment, racial/ethnic groups were as follows: 68% non-Hispanic White, 17% Hispanic, 9% non-Hispanic Black, 6% Asian, and 1% unassigned. In analysis of genetically reassigned race/ethnicity with skeletal toxicities, Hispanic and Black patients had significantly lower risk of fracture compared with white patients (Hispanic: subdistribution hazard ratio [SHR]=0.42, 95% confidence interval [CI]=0.22, 0.81; Black: HR=0.28, 95%CI=0.10, 0.75). These groups also had significantly less osteonecrosis (Hispanic: SHR=0.24, 95%CI=0.08, 0.78; Black: SHR=0.12, 95%CI=0.02, 0.93). Similar results were observed when using clinical race/ethnicity. Further analyses revealed that African genetic ancestry, but not Native American ancestry was associated with lower risk of fracture and osteonecrosis in a dose-dependent manner (Table 1). In analysis of death and recurrence, those with higher proportion of Native American ancestry had significantly higher risk of death/recurrence after adjustment (OS: hazard ratio [HR]=4.00, 95%CI=1.45, 11.02; EFS: HR=2.07, 95%CI=1.13, 3.79). Analysis of single variants and polygenic risk scores with skeletal toxicities and survival outcomes is ongoing. Conclusion: Hispanic children and adolescents from the DFCI 05-001 cohort, had highly heterogenous genetic ancestral make-up. Among Hispanic patients, the observed lower risk of skeletal toxicities might be driven by African ancestry, whereas poorer survival observed might be driven by Native American ancestry. Disclosures Silverman: Servier: Consultancy, Research Funding; Takeda: Consultancy.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,030

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,006
Tête enseignante GPT0,231
Écart entre enseignants0,225 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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