Abstract B029: Clinical and Sociodemographic Associations Between Early-Onset and Late-Onset Colorectal Cancer in a U.S.–Mexico Border Population
Notice bibliographique
Résumé
Abstract Colorectal cancer (CRC) is the second leading cause of cancer mortality for both men and women in the United States. While the general incidence of CRC among older adults has decreased since the 1990s, CRC incidence in younger adults has increased during the same time span. Surveillance data specifically reveal a hotspot of CRC incidence along the U.S.-Mexico border near El Paso, Texas, with an upward trend even as statewide rates have plateaued. Despite these observed disparities, there is limited data on early-onset CRC patterns in border communities. This study is a secondary analysis of data derived from a case-control study conducted between 2011 and 2023 to describe the health status of an outpatient population in El Paso, Texas. The sample population (n = 818) was identified from patients in the parent study who were cases and had a CRC diagnosis. This study investigated differences in the health status, comorbidities, and biomarkers in individuals diagnosed with CRC before age 50 (early-onset, EO-CRC) and those diagnosed at or after age 50 (late-onset, LO-CRC) in a predominantly Hispanic population along the U.S.-Mexico border. Results indicated that EO-CRC patients had higher rates of being uninsured (22.6%), having private insurance (54.1%), and reporting higher household incomes (p = 0.047). They were also more likely to have metastatic cancer (OR: 0.650; 95% CI: 0.457, 0.925; p = 0.016) and to have a family history of cancer (OR: 0.276; 95% CI: 0.117, 0.652; p = 0.002). In contrast, LO-CRC patients exhibited greater comorbidity burden, including significantly higher prevalence of heart failure, hypertension, renal failure, and type II diabetes. LO-CRC patients were also more likely to have been prescribed medications such as aspirin (OR: 5.472; 95% CI: 2.819, 10.618; p < 0.001) and statins (OR: 3.470; 95% CI: 2.092, 5.758; p < 0.001). Biomarker analysis revealed that EO-CRC patients had higher aspartate aminotransferase, alanine aminotransferase, high-density lipoprotein, and alkaline phosphatase levels compared to LO-CRC patients, while LO-CRC patients had higher blood urea nitrogen, creatinine, glucose, and potassium levels. These findings underscore meaningful clinical and demographic distinctions between EO-CRC and LO-CRC that may reflect unique etiologic pathways, access challenges, and behavioral factors. Younger CRC patients tended to have lower Elixhauser risk scores and fewer comorbidities, which aligns with previous studies suggesting that EO-CRC patients may otherwise be relatively healthy at diagnosis. The higher metastatic burden among younger patients adds urgency to improving symptom recognition in younger adults. It suggests that existing screening and diagnostic models may miss warning signs in younger populations. As EO-CRC incidence increases, particularly among Hispanic populations, targeted, age-sensitive approaches to prevention, diagnosis, and care are essential for improving outcomes and reducing disparities. Citation Format: Atharva Railkar, Amir Hernandez, Jennifer Molokwu. Clinical and Sociodemographic Associations Between Early-Onset and Late-Onset Colorectal Cancer in a U.S.–Mexico Border Population [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 B029.
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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 ».