Abstract C023: Studying early onset cancer: benefits and limitations of studies within the Military Health System
Notice bibliographique
Résumé
Abstract Studies of the small numbers of younger cases in older existing cohorts will not allow us to clearly understand the factors associated with the rising rates of early onset cancers in the last 25 years. While clearly genetic susceptibility plays a role in the etiology of cancer, population genetics are not changing as rapidly as the rates of early onset cancers. We must make use of existing prospective data from young individuals, in the birth cohorts for whom cancer rates are increasing, to investigate contemporary exposures. Cancer rates have increased in the population of more than 1.3 million individuals in the U.S. military in parallel to the general population despite the required military health and fitness standards. This population and their linked data available in the Military Health System provides a valuable resource to investigate environmental exposures alone or in combination with genetic susceptibility and the associations with early onset cancers. The average age of this racially and ethically diverse population is ∼29 years old with those >30 years old increasing in recent decades. Although the cohort is predominantly male, females still make up about 18% of the active-duty force. For those on active duty, information collected during their service from the military medical, occupational, and pharmaceutical databases with analyses of serial serum samples, obtained approximately every two years since the late 1980’s, can be analyzed to identify factors that impact the risk of early onset cancers. Even if all information of interest may not be available and the number and volume of samples for each subject is limited, researchers can still glean a great deal from studies of this population. Considering the methodological factors of both calendar time in measured exposures and timing with respect to diagnosis allows for the potential identification of the relevant windows of susceptibility to specific exposures. The most appropriate study design and methods for implementation as well as the limitations to consider will be presented. Ongoing nested-case-control studies focusing on testicular, breast, colorectal, thyroid, and pancreatic cancers use these resources to study the environmental determinants of early onset cancers in this population. Access to these resources is currently available through collaboration with Department of Defense researchers. Plans are developing for wider access with future linkage with the national virtual pooled cancer registry that will enable identification of those diagnosed after leaving military service. The views expressed are those of the author and do not necessarily reflect the official views of the Uniformed Services University of the Health Sciences or the Department of Defense. Citation Format: Celia Byrne. Studying early onset cancer: benefits and limitations of studies within the Military Health System [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 C023.
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 | 0,010 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».