Abstract B016: Survival differences after diagnosis of early-onset colorectal cancer by race/ethnicity and neighborhood-level socioeconomic status
Notice bibliographique
Résumé
Abstract Background: The incidence of early-onset colorectal cancer (eoCRC), diagnosed age <50 years, is increasing in the United States. Prior studies using national and state cancer databases have observed higher eoCRC mortality after diagnosis among non-Hispanic Black (NHB) patients. These studies, however, did not account for insurance status or healthcare access, which may contribute to the observed disparities. Here we examined the associations between race/ethnicity and census tract-level median household income with all-cause and colorectal cancer (CRC)-specific mortality among eoCRC cases in a large integrated healthcare delivery system whose racially/ethnically diverse members have relative equal access to care. Methods: We included Kaiser Permanente Southern California (KPSC) members diagnosed with eoCRC (age 15-49 years) between 2009-2021 and followed them through 12/31/2023. Patients with <12 months of prior KPSC membership or unspecific CRC site were excluded. Bivariate and multivariable Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between race/ethnicity and census tract-level household income and all-cause and CRC-specific mortality. Multivariable models were adjusted for age at diagnosis, sex, Charlson comorbidity score, obesity, stage at diagnosis, cancer site, and histologic subtype. Subgroup analyses were conducted by stage at diagnosis (localized, regional, distant). Results: Of 1,719 eoCRC cases included, we observed 471 deaths (423 (92.4%) were CRC-specific deaths) over a mean follow-up time of 6.8 years. In the adjusted models, NHB and non-Hispanic Asian/Pacific Islander (NH API) patients, but not Hispanic patients (HR=1.06, 95% CI: 0.84-1.30), had significantly higher all-cause mortality (HR=1.55, 95% CI: 1.10-2.20, p=0.01; HR=1.43, 95% CI: 1.07-1.91, p=0.02, respectively) compared with non-Hispanic White (NHW) patients. In the subgroup analyses, race/ethnicity was not associated with all-cause mortality among patients with localized disease. However, among patients diagnosed with regional disease, NHB patients had a significantly higher risk of all-cause mortality compared with NHW patients (HR=1.94, 95% CI: 1.07-3.50, p=0.03). Among patients diagnosed with distant stage disease, both NHB and NH API patients had elevated risk of all-cause mortality compared with NHW patients (HR=1.59, 95% CI: 0.99-2.57, p=0.06 and HR=1.63, 95% CI: 1.10-2.43, p=0.02, respectively). Similar findings were observed for CRC-specific mortality, overall and by cancer stage. Census-tract level median household income was not significantly associated with all-cause or CRC-specific mortality. Conclusions: In this insured population, NHB and NH API race/ethnicity were associated with increased risk of CRC-specific mortality among those diagnosed with advanced stage eoCRC. However, the number of NHB and NH API patients diagnosed at distant stage were small. Therefore, future research is needed to confirm these findings and better understand potential survival disparities. Citation Format: Talar S. Habeshian, Lanfang Xu, Kimberly L. Cannavale, Alec Gilfillan, Darios Getahun, Chun R. Chao. Survival differences after diagnosis of early-onset colorectal cancer by race/ethnicity and neighborhood-level socioeconomic status [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr B016.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».