Risk of Death Due to Breast Cancer in Women Treated with Selective Serotonin Reuptake Inhibitor Antidepressants and Tamoxifen.
Notice bibliographique
Résumé
Abstract Background: Tamoxifen is widely prescribed to women with breast cancer, but is a prodrug converted by cytochrome P450 2D6 (CYP 2D6) to its active metabolite endoxifen. Selective serotonin re-uptake inhibitor antidepressants (SSRIs) are commonly co-prescribed with tamoxifen, but inhibit CYP 2D6 to varying degrees and may decrease the effectiveness of tamoxifen.Materials and methods: We conducted a population-based retrospective cohort study of women in Ontario, Canada aged 66 years of age or older who were treated with tamoxifen for breast cancer between 1993 and 2005 and had overlapping SSRI therapy. Following completion of tamoxifen therapy, we modeled the risk of death from breast cancer as a function of the proportion of time on tamoxifen during which each SSRI had been co-prescribed.Results: We identified 24,430 women aged 66 years and older who started tamoxifen therapy during the 13 year study period. Of these, 7489 (30.6%) received at least one antidepressant during tamoxifen therapy. After excluding those treated with no SSRI or with multiple SSRIs, those with poor adherence to tamoxifen therapy, and those with unknown cause of death, the primary analysis included 2430 women. Paroxetine was the most commonly prescribed SSRI (n=630; 25.9%) followed by sertraline (n=541; 22.3%), citalopram (n=467; 19.2%), venlafaxine (n=365; 15.0%) fluoxetine (n=253; 10.4%) and fluvoxamine (n=174; 7.2%). A total of 1074 (44.2%) women died during follow-up and there were 374 (34.8%) breast cancer deaths. After adjustment for age, duration of tamoxifen therapy, and other potential confounders absolute increases of 25%, 50%, and 75% in the percentage of time co-prescribed paroxetine during tamoxifen therapy were associated with 24%, 54% and 91% increases in the risk of death from breast cancer respectively (p<0.05 for each comparison). In contrast, we found no such risk with fluoxetine, sertraline, fluvoxamine or citalopram. We observed a nonsignificant trend toward reduced breast cancer mortality among venlafaxine users, which may reflect the common practice of using venlafaxine for tamoxifen-related hot flashes, a putative predictor of better outcomes in women receiving tamoxifen. We replicated our analyses using death from any cause as the outcome of interest (n=1074). After adjusting for potential confounders, we found that absolute increases of 25%, 50% and 75% in paroxetine exposure during tamoxifen therapy were associated with relative increases of 13%, 28% and 46%, respectively, in the risk of death from any cause. In contrast, we found no such increased risk in all-cause mortality associated with exposure to the other SSRIs in women receiving tamoxifen for breast cancer.Discussion: Paroxetine use during tamoxifen therapy is associated with an increased risk of death due to breast cancer. This supports the hypothesis that paroxetine-mediated CYP 2D6 inhibition can reduce or abolish the beneficial effects of tamoxifen. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 2049.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».