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Enregistrement W2964704906 · doi:10.1182/blood.v130.suppl_1.607.607

Survival By Race/Ethnicity in Children and Adolescents with Hodgkin Lymphoma Treated on Cooperative Group Trials in the U.S. and Canada: A Pooled Analysis of Children's Oncology Group Trials

2017· article· en· W2964704906 sur OpenAlexaboutno aff
Justine M. Kahn, Kara M. Kelly, Qinglin Pei, Debra L. Friedman, Frank G. Keller, Rizvan Bush, Smita Bhatia, Tara O. Henderson, Cindy L. Schwartz, Sharon M. Castellino

Notice bibliographique

RevueBlood · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineCogInternal medicineEthnic groupPopulationClinical trialHazard ratioDemographyIncidence (geometry)CancerProportional hazards modelOncologyConfidence interval

Résumé

récupéré en direct d'OpenAlex

Introduction: While survival in Hodgkin Lymphoma (HL) is excellent, disparities by race/ethnicity have been described. Population-based and single center studies of children and adolescents with HL suggest that those who are black or Hispanic (vs. non-Hispanic white) have worse outcomes (Grubb Pediatr Blood Cancer 2016; Metzger JCO 2008). Whether race/ethnicity is predictive of survival in children and adolescents with HL after adjusting for clinical features and treatment-related variables is unknown. Our objective was to examine whether race/ethnicity was predictive of event-free survival (EFS), relapse, and overall survival (OS) in patients enrolled on contemporary Children9s Oncology Group (COG) trials with response-based therapy for treatment of newly diagnosed HL. Methods: We conducted a pooled analysis of individual level data in children and adolescents enrolled on 3 consecutive Phase III clinical trials for treatment of intermediate, low and high-risk HL (AHOD0031, AHOD0431, AHOD0831). Five-year EFS and OS were compared across racial/ethnic groups and were estimated using the Kaplan-Meier method. Cumulative incidence of relapse was similarly constructed with K-sample tests. Cox regression models were constructed to examine the influence of race/ethnicity on EFS and OS, and were adjusted for age, sex, insurance status, histology, Ann Arbor stage, B symptoms, bulk disease, COG study, and radiation therapy (RT). Results: Between 2002 and 2012, 2155 patients 1-21 years of age enrolled on 3 COG trials, 2071 (96%) of whom were included in this analysis. Patients treated outside the US and Canada (n=84) were excluded. The distribution of race/ethnicity as reported to COG by treating institutions was: 64% non-Hispanic white (N=1334), 11% non-Hispanic black (N=236), 16% Hispanic (N=329), 3% Asian/Pacific Islander (N=66), and 5% other (N=106). Compared to other groups, more non-Hispanic white patients had private (vs. government) insurance (p Survival: In pooled analysis, with a median follow-up of 6.9 years, 5-year EFS was 83%, OS was 97%, and neither outcome differed by race/ethnicity (EFS: p=0.98; OS: p=0.29). Cumulative incidence of relapse was 16.8% and did not differ by race/ethnicity (p=0.93). In the multivariable model for EFS, there was no significant effect of race/ethnicity (p=0.95). Similarly, race/ethnicity was not significant in the multivariable model for OS (p=0.14). Finally, race/ethnicity was not significantly associated with EFS or OS in multivariable models by individual study, accounting for risk group. Conclusion: We observed no difference in survival by race/ethnicity among children and adolescents treated for HL with contemporary, risk adapted response-based therapy on COG Phase III trials. This suggests that the survival gap observed in population-based studies is largely reduced by access to clinical trials and by receipt of comparable therapy between cohorts. In light of this, it can be hypothesized that inequities in access to high-quality care, rather than differences in individual disease biology may underlie racial disparities observed in the community oncology setting. To examine whether response-based paradigms mitigated biologic differences between groups, further analyses will explore early response to treatment by race/ethnicity. Further analyses will also examine treatment-related toxicities and second malignant neoplasms by race/ethnicity, as well as the independent contribution of socioeconomic status to outcomes. Disclosures No relevant conflicts of interest to declare.

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)0,027
score de la tête « metaresearch » (Gemma)0,036
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,919
Score d'incertitude au seuil0,162

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0270,036
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0050,013
Bibliométrie0,0050,007
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,021
Tête enseignante GPT0,293
Écart entre enseignants0,272 · 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

Citations2
Publié2017
Routes d'admission1
Résumé présentoui

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