Do Genetic Contributors to Warfarin Responsiveness or Common Thrombophilias Influence the Risk of Major Bleeding in Patients on Extended Duration Vitamin K Antagonist (VKA) for Venous Thromboembolic Disease?
Notice bibliographique
Résumé
Abstract Background: Recent studies have indicated that genetic factors such as polymorphisms in the CYP2C9 and the VKORC1 genes play an important role in vitamin K antagonist (VKA) response and perhaps bleeding. There are also data to suggest, especially for factor V Leiden, that thrombophilia may confer a decreased risk of bleeding (which could explain its persistence and high prevalence in the population). The influence of major genetic factors on risk of bleeding have not previously been evaluated in large prospective cohort studies of patients with VTE on extended (treatment after the first 3 to 6 months) VKA therapy. Aims: We sought to determine the effect of genetic variants that influence warfarin metabolism and thrombophilias on the rates of major bleeding during extended VKA therapy in patients with VTE disease. Methods: The Bleeding Risk study is a multicentre, multinational prospective cohort study of patients on extended VKA for unprovoked VTE, or provoked VTE with prior VTE. Patients were enrolled after at least 3 months of VKA. All major bleeding events during long term VKA were captured and adjudicated. A blood sample was taken from each patient at their first study visit and analysed in a central lab to identify the following genetic variant types: CYP2C9*2 (C/T), CYP2C9*3 (T/G), 1639G-A (G/A), Factor V Leiden (G/A: FVL), CYP4F2 (G/A), and Prothrombin gene 20210 variant (PGV). Rates of major bleeding were then evaluated for patients with each genetic variant in isolation and in combination. Results: 2290 of the 2514 patients enrolled at 12 sites have contributed over 7000 years of observation and were included in this analysis. The mean patient age was 60.2±14.7 years, 64% were male, 92% Caucasian, average BMI was 31.3, and 9% of patients were on antiplatelet agents. Patients were followed for a mean of 2.8 years (range, 0.1 to 6.8 years. 121 patients (4.8%) experienced at least one episode of major bleeding. The annual rate of bleeding was 1.7 per 100 patient-years of observation. The CYP2C9*2 variant heterozygous/homozygous versus wildtype (476 patients vs 1584) was protective against bleeding (Incidence risk ratio 0.5, p =0.01), CYP2C9*3 variant heterozygous/homozygous versus wildtype (215 patients vs 1845) was associated with major bleeding (Incidence risk ratio 2.0, p =0.01), VKORC1 and CYP4F2 had no association with major bleeding, and CYP2C9*3 variant heterozygous/homozygous in combination with wildtype CYP2C9*2 (186 patients) was associated with major bleeding (Incidence risk ratio 3.24, p =0.02). Both FVL (19% of patients) and PGV (8% of patients) had no effect on major bleeding, with p values > 0.35 for comparison of the wildtype to heterozygous/homozygous. Conclusion: This is the largest study we are aware of to determine if warfarin metabolic genotype variants and common thrombophilias influence major bleeding risk in patients followed long-term with extended duration VKA therapy for VTE. The thrombophilias do not influence bleeding risk but those with CYP2C9*3 hetero/homozygous inheritance had double the risk and CYP2C9*2 hetero/homozygous inheritance half the risk. There appears to be an interaction between the CYP2C9*2 and *3 genotypes. Disclosures Wells: BMS/Pfizer: Research Funding; Bayer Healthcare: Other: Speaker Fees and Advisory Board; Janssen Pharmaceuticals: Consultancy; Itreas: Other: Served on a Writing Committee. Kovacs:LEO Pharma: Honoraria; Bayer: Honoraria, Research Funding; Daiichi Sankyo Pharma: Research Funding; Pfizer: Honoraria, Research Funding. Anderson:Bayer Healthcare: Research Funding. Rodger:Canadian Agency for Drugs and Technologies in Health: Consultancy; Boehringer Ingelheim: Research Funding.
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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 | 0,001 | 0,003 |
| 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 ».