The Association of Dyslipidemia with the Development of Chronic Lymphocytic Leukemia: A Population-Based Study
Notice bibliographique
Résumé
Abstract Background: Metabolic syndrome (MetS) is a risk factor for the development of cancer. Pre-clinical data suggests that chronic lymphocytic leukemia (CLL) cells are dependent on adipocytes and fatty acids for growth and that aberrant lipid metabolism is an important pathogenic mechanism in CLL. Our objective was to determine whether patients with CLL have a higher incidence of MetS prior to their CLL diagnosis compared to those without CLL and to determine the impact of lipid-lowering medications including statins on survival. Methods: We conducted a population-based retrospective cohort study in Ontario, Canada using administrative databases (i.e., Ontario Cancer Registry, Ontario Drug Benefit dataset, Aggregated Diagnostic Groups (ADGs), postal codes/income) of adults >66 years old to compare the prevalence of MetS and its components (diabetes, dyslipidemia, hypertension) in CLL patients that preceded their diagnosis. This was compared to age and sex-matched controls without CLL. Logistic regression was used to study the association between MetS and its components to CLL, adjusting for location (rural vs. urban), disease comorbidity burden (ADGs) and socioeconomic status. The Kaplan-Meier method was used to illustrate survival. Results: We identified 2,124 persons with CLL and 7,935 controls from January 1, 2000 to December 31, 2005 with follow-up until death or March 31, 2014. The mean age was 75.6 and 42.1% were female. Overall, 14.1% had diabetes, 63.1% had hypertension and 28.0% had dyslipidemia. On univariable analysis, only dyslipidemia alone (OR 1.35; 95% CI 1.21 to 1.50) and the combination of diabetes and dyslipidemia (OR 1.18; 95% CI 1.00 to 1.39) were associated with the development of CLL, whereas MetS and diabetes alone were not. On multivariable analysis only dyslipidemia was independently significant (OR 1.30; 95% CI 1.16 to 1.47; see table). Notably, on univariable survival analysis the use of lipid-lowering agents comprised primarily of statins at any time (prior or subsequent to CLL diagnosis) was associated with a significantly improved median overall survival in patients with CLL (7.9 years, 95% CI 7.3 to 8.5 vs. 4.1 years, 95% CI 3.7 to 4.5 years; p < 0.0001; see figure 1). Conclusions: We demonstrate a higher prevalence of dyslipidemia preceding a diagnosis of CLL compared to controls, supporting pre-clinical data. Also, the association of MetS and CLL appears to be driven primarily by dyslipidemia. Lipid-lowering medications and in particular statins appear to confer a survival advantage in CLL. Further multivariable survival analysis and ultimately prospective studies are needed to confirm these results and test their potential application to intervention strategies. Table. Exposure Odds Ratio (CLL vs. Control) metabolic syndrome 1.10 (95% CI 0.92 to 1.32) diabetes + dyslipidemia 1.17 (95% CI 0.98 to 1.40) diabetes 1.03 (95% CI 0.90 to 1.17) dyslipidemia 1.30 (95% CI 1.16 to 1.47) Figure 1. Figure 1. Disclosures Spaner: Roche: Honoraria; Lundbeck: Honoraria; Novartis: Research Funding; Janssen: Honoraria. Buckstein:Celgene: Honoraria, Other: Advisory Board.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 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 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 ».