Abstract 3592: Hospital-treated infectious diseases and pancreatic cancer risk: Findings from a large population-based cohort
Notice bibliographique
Résumé
Abstract Rationale: Inflammation has been established as a mechanism for pancreatic cancer development. The longitudinal relationship between infection, and the resulting inflammation, and pancreatic cancer risk has yet to be elucidated. A large population-based cohort, such as the United Kingdom (UK) Biobank, offers a unique opportunity to assess these relationships with long follow-up time and a large number of infections. Objectives: Estimate the effect of hospital-treated infection on pancreatic cancer risk by infection type and infection burden. Methods: UK Biobank participants with no record of pancreatic cancer at cohort entry were included. Follow-up was to February 29, 2020 and January 31, 2021 for participants from England and Wales, and Scotland, respectively. Hospital-treated infection status was obtained through linkage to hospital inpatient data and allowed for characterization of exposure to over 900 infectious diseases using the International Classification of Diseases and Related Health Problems 10th Revision. Incident pancreatic cancer diagnosis was obtained through linkage to national cancer registries. Relative risk (RR) and associated 95% confidence intervals (CI) were estimated for infectious disease groups and infectious disease burden categories using negative binomial regression models. Results: From cohort entry to the end of follow up, 502, 219 people were included in the cohort. 93, 123 participants had at least one recorded exposure to hospital-treated infection preceding pancreatic cancer diagnosis and 1, 255 were diagnosed with pancreatic cancer throughout the follow up period. Exposure to any hospital-treated infection was associated with increased risk of pancreatic cancer (aRR 2.56 [95% CI 2.27, 2.88]). When considering infection burden, a dose-response relationship was seen (ptrend < 0.001) where a greater number of infections was associated with a greater risk of pancreatic cancer. When compared to those with no infection, participants had increasing risk with 1 infection (aRR 1.99 [95% CI 1.69, 2.35]), 2 infections (aRR 2.84 [95% CI 2.34, 3.43]), and >3 infections (aRR 3.21 [95% CI 2.72, 3.78]). Conclusions: Infections which require treatment in hospital are associated with risk of pancreatic cancer. This association was strongest when considering bacterial infection and its impact on longitudinal risk of pancreatic cancer. Further, the dose-response relationship observed when investigating infection burden may suggest a cumulative risk of pancreatic cancer conferred with severe infections. Citation Format: Kiera R. Murison, Rayjean J. Hung. Hospital-treated infectious diseases and pancreatic cancer risk: Findings from a large population-based cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3592.
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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».