UNDERSTANDING THE IMPACT OF CYP2D6-MEDIATED VENLAFAXINE PHARMACOKINETICS ON TREATMENT OUTCOMES IN LATE-LIFE DEPRESSION
Notice bibliographique
Résumé
Abstract Background Aging makes older adults more susceptible to antidepressant-induced side effects due to homeostatic reserve, comorbidity, poly-pharmacy, and age-related pharmacokinetic (PK) changes. Depression in older adults is often treated with venlafaxine, a serotonin-norepinephrine reuptake inhibitor metabolized by the enzyme CYP2D6. CYP2D6 is highly genetically polymorphic and thus might affect venlafaxine treatment outcomes by affecting venlafaxine PK. Aims and Objectives The study aims to investigate whether CYP2D6 metabolizers have different VEN- related PK parameters and examine the impact of these parameters on treatment outcomes in late-life depression. Method Data from participants from the Incomplete Response in Late-Life Depression: Getting to Remission study (IRL-GRey, NCT00892047) were analyzed in this study (N = 325) [1]. We used the software NONMEM to adapt a population PK analyses of VEN and its main metabolite O- desmethylvenlafaxine (ODV) [2]. The PK model was adjusted for CYP2D6 metabolizer status and age. The ANOVA was performed to identify differences in PK model-estimated PK parameters between CYP2D6 metabolizer groups. Treatment efficacy (measured using MADRS) and adverse effects (measured using UKU) were analyzed using regression models to see if they were associated with PK model-estimated drug exposure, followed by sex-stratified analyses for each outcome. Results CYP2D6 metabolizers had significantly different PK model-estimated VEN clearance, VEN exposure, and active moiety (venlafaxine plus ODV) exposure. None of the exposure was associated with treatment efficacy in either whole sample or sex-stratified analyses. The overall presence of adverse effects was associated with higher ODV exposure (OR = 1.5 [1.0, 2.2], p = 0.04) and higher AM exposure (OR = 1.7 [1.2, 2.5], p = 0.003). Only females showed a significant association between overall adverse effects and higher active moiety exposure (OR = 2.0 [1.3, 3.2], p = 0.004). Specifically, higher risk of nausea/vomiting was associated with higher venlafaxine exposure and higher active moiety exposure in both the whole sample (venlafaxine, OR = 1.1 [1.0, 1.2], p = 0.04; active moiety, OR = 2.0 [1.2, 3.4], p = 0.01) and females (venlafaxine, OR = 1.1 [1.0, 1.2], p = 0.02; active moiety, OR = 2.2 [1.2, 4.0], p = 0.01), but not in males. In the whole sample, orthostatic dizziness is associated with higher venlafaxine exposure (OR = 1.1 [1.0, 1.2], p = 0.02) and higher active moiety exposure (OR = 2.0 [1.2, 3.4], p = 0.01). For this adverse effect, females showed had association only with higher venlafaxine (OR = 1.1 [1.0, 1.2], p = 0.02), while males showed significant associations in higher ODV (OR = 5.2 [1.2, 23.0], p = 0.03) and higher active moiety exposure (OR = 5.5 [1.1, 26.8], p = 0.03). Discussion & Conclusions Our study indicated that CYP2D6 metabolizer groups had a significant impact on PK model-estimated VEN-related PK parameters. Higher venlafaxine-related exposure is associated with a higher risk of active effects, especially nausea/vomiting and orthostatic dizziness. Sex might also be an important factor in venlafaxine treatment outcomes. Overall, our study highlights the importance of personalized medicine and its clinical implications in older adults with depression. References 1.Lenze, E. J. et al. Efficacy, safety, and tolerability of augmentation pharmacotherapy with aripiprazole for treatment-resistant depression in late life: a randomised, double-blind, placebo- controlled trial. The Lancet 386, 2404–2412 (2015). 2.Lindauer, A. et al. Pharmacokinetic/pharmacodynamic modelling of venlafaxine: pupillary light reflex as a test system for noradrenergic effects. Clin. Pharmacokinet. 47, 721–731 (2008).
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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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».