Statin and COX-2 Inhibitor Exposure Is Associated with Improved Survival in 4913 Newly Diagnosed DLBCL Patients: A Large Population Based Study
Notice bibliographique
Résumé
Background: In the era of chemo-immunotherapy, risk factors associated with survival in patients with diffuse large B-cell lymphoma (DLBCL) are largely limited to biologic characteristics of disease. Laboratory based studies have postulated that statins (through inhibition of the geranylgeranylation pathways) can induce apoptosis in DLBCL cells; pre-clinical data suggests an anti-cancer potential for metformin (through inhibition of cancer cell growth by activation of AMPK and inhibition of mTOR pathways) and cox-2 inhibitors (anti-proliferative effects through blockade of PI3K pathway, inhibition of angiogenesis and proliferation by blocking eicosanoid receptors). To date, these potential in-vitro benefits have not been demonstrated consistently in "real world" studies. Our objective was to assess the impact of medicines with a biologic potential on lymphoma outcome in the era of rituximab. Methods: We performed a retrospective population-based study of adults ≥66 years diagnosed with DLBCL or transformed lymphoma treated in Ontario, Canada. Administrative databases held at ICES were used to assess the impact of select medications on patient outcomes. All patients treated, with curative intent, with a rituximab containing regimen between January 2005 and December 2015 were included. A 1-year lookback of medication exposure prior to commencing rituximab was used. Cox regression analyses were performed to determine the relationship between medication exposure and lymphoma outcomes. Additional analyses were completed to control for known confounders of survival, including the number of comorbid conditions. Results: A total cohort of 4913 patients were treated with a rituximab containing regimen, most frequently R-CHOP, during the study timeframe. Median age was 75 years (IQR 70-80); 51% were male. The median number of cycles of chemotherapy was 6 (IQR 3-6). The median number of comorbidities was 11 (IQR 9-14). Sixty-nine percent had a high comorbidity score (≥10); 26.4% moderate (6-9); and 4.7% low (0-5). Where mortality data was available, 52.1% of the cohort died at a median of 1 year, of whom 67% died due to DLBCL. In the year prior to commencing lymphoma therapy 45.7% received statin therapy; 16.3% metformin; and 25.0% cox-2 inhibitor. In the univariate analysis, statin exposure (HR 0.88; 0.8 - 0.97) was associated with improved survival, but exposure to cox-2 inhibitor (HR 0.82; 0.65 - 1.04) and metformin (HR 1.11; 0.98 - 1.26) had a no impact, during this timeframe. Adjusting for time varying exposure and demographic variables including socio-economic factors and comorbidities, we demonstrated that additional exposure to statin and cox-2 inhibitors in the 365 days prior to commencing lymphoma therapy was associated with a survival advantage, when compared to those who were never exposed. Statin exposure for 30 days (HR 0.97 [0.96-0.98]), 180 days (HR 0.84 [0.80-0.89]) and 365 days (HR 0.71 [0.63-0.79]) and cox-2 inhibitor exposure for 30 days (HR 0.95 [0.95-0.98]), 180 days (HR 0.76 [0.66-0.86]) and 365 days (HR 0.57 [0.43-0.74]) were independently associated with improved survival. In contrast metformin exposure had no impact on survival in this cohort. Patients with moderate (HR 1.69; 1.25 - 2.29) and high comorbidity scores (HR 3.16; 2.36 - 4.21) had significantly higher risk of mortality (p<0.0001). Increasing age (p<0.001; HR 1.05 [1.05-1.06]) and male sex (p=0.003; HR 1.13 [1.04-1.23]) were also associated with increased mortality.
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) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».