Abstract A091: Clinical and demographic differences between children and young adult US-born and non-US-born Latinos diagnosed with classical Hodgkin Lymphoma in the MESH Study Cohort
Notice bibliographique
Résumé
Abstract Background: The incidence of classical Hodgkin lymphoma (CHL) varies by demographic factors including race/ethnicity and birthplace. For this study, we aimed to describe differences in demographic and clinical characteristics between US-born and non-US-born Latinos diagnosed with CHL overall in our study cohort. As age has a known association with histological subtype and other clinical characteristics in CHL, we further stratified by age and evaluated Adolescent and Young Adult (AYA) (15 to 39 years old at time of diagnosis) and older adults (40+ years old at time of diagnosis) separately Methods: For the (M)ulti (E)thnic (S)tudy of (H)odgkin Lymphoma (MESH) we collected formalin-fixed paraffin-embedded (FFPE) tumor blocks from 912 multiethnic cases of CHL from multiple sites, including cancer centers, hospitals, and Residual Tissue Repositories. Cases in our study cohort were diagnosed between 1986 and 2019. We utilized Fisher's exact test to assess statistical differences of categorical demographics and clinical characteristics between Latino cases with US and non-US birthplace in our cohort. Logistic regression models were used where the dependent variable was each binary "Characteristic" with independent variables: birthplace (nonUS-born vs US-born), age at diagnosis, and sex. Results: Three hundred fifty-eight cases (39.3%) were identified as Latino based on available records. We were able to confirm the country of birth for 202 (56.4%) of these cases, with 71 US-born and 131 nonUS-born Latinos. Among nonUS-born cases, 79% reported Mexico as their birthplace. The country of origin is representative of our local population. nonUS-born Latinos were older (p=<0.001 ) and had a higher prevalence of late stage disease at the time of diagnosis (p <0.001) than their US-born counterparts. nonUS-born Latinos were more likely to be of low socioeconomic status (SES) compared to US-born Latinos (P-value=0.003). We observed no significant differences in sex, first course of treatment, B symptoms, histology, or Epstein-Barr virus (EBV) tumor status between the two groups. Within AYA cases, we found a significant difference in stage with US-born Latinos having earlier stages at diagnosis (P-value <0.001) compared to Latin American-born AYA Latinos in our cohort. We also noted a trend towards Latin American- born Latinos having a lower SES (P-value=0.009). There were no significant differences in sex, first course of treatment, B symptoms, histology, or EBV status. These trends were also evident after adjusting for age and sex. Specifically, after adjusting for age and sex, there was a 7.24 and 4.83 times higher odds of having later stage (P=0.0002) and lower SES (P=0.01), respectively, among non-US-born compared to US born. Conclusions: We observed significant differences in age, stage at diagnosis, and socioeconomic status in cases by birthplace. Compared to US-Born AYA Latino patients, nonUS-born AYA Latino patients had a higher likelihood of having later stage and lower SES. Thus, targeting the disparities in this age group will be critical. Citation Format: Jose Alejandro. Aparicio, Jia Angel. Wan, Esther Lam, Mallory Bernstein, Sheeja T. Pullarkat, Deepthi Karunasiri, Anthony Colombo, Joo Song, Chun Chao, Brenda Hernandez, Tomohiro Aoki, Pamela B. Allen, Christopher R. Flowers, Sophia Wang, Juanita Evans, Owen Chen, Elva Jiménez Hernández, Juan Carlos Núñez Enríquez, José Arellano Galindo, María del Rosario Mora Campos, Susana Elizabeth Anaya Aguirre, David Scott, Megan Lim, Leon Bernal-Mizrachi, Jakub Svoboda, Christian Steidl, David Conti, Imran Siddiqi, Juan Manuel Mejia Arangure, Wendy Cozen. Clinical and demographic differences between children and young adult US-born and non-US-born Latinos diagnosed with classical Hodgkin Lymphoma in the MESH Study Cohort [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr A091.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».