Development and Validation of the DOAC Score: A Novel Bleeding Risk Prediction Tool for Patients With Atrial Fibrillation on Direct-Acting Oral Anticoagulants
Notice bibliographique
Résumé
BACKGROUND: Current clinical decision tools for assessing bleeding risk in individuals with atrial fibrillation (AF) have limited performance and were developed for individuals treated with warfarin. This study develops and validates a clinical risk score to personalize estimates of bleeding risk for individuals with atrial fibrillation taking direct-acting oral anticoagulants (DOACs). METHODS: Among individuals taking dabigatran 150 mg twice per day from 44 countries and 951 centers in this secondary analysis of the RE-LY trial (Randomized Evaluation of Long-Term Anticoagulation Therapy), a risk score was developed to determine the comparative risk for bleeding on the basis of covariates derived in a Cox proportional hazards model. The risk prediction model was internally validated with bootstrapping. The model was then further developed in the GARFIELD-AF registry (Global Anticoagulant Registry in the Field-Atrial Fibrillation), with individuals taking dabigatran, edoxaban, rivaroxaban, and apixaban. To determine generalizability in external cohorts and among individuals on different DOACs, the risk prediction model was validated in the COMBINE-AF (A Collaboration Between Multiple Institutions to Better Investigate Non-Vitamin K Antagonist Oral Anticoagulant Use in Atrial Fibrillation) pooled clinical trial cohort and the Quebec Régie de l’Assurance Maladie du Québec and Med-Echo Administrative Databases (RAMQ) administrative database. The primary outcome was major bleeding. The risk score, termed the DOAC Score, was compared with the HAS-BLED score. RESULTS: Of the 5684 patients in RE-LY, 386 (6.8%) experienced a major bleeding event, within a median follow-up of 1.74 years. The prediction model had an optimism-corrected C statistic of 0.73 after internal validation with bootstrapping and was well-calibrated based on visual inspection of calibration plots (goodness-of-fit P =0.57). The DOAC Score assigned points for age, creatinine clearance/glomerular filtration rate, underweight status, stroke/transient ischemic attack/embolism history, diabetes, hypertension, antiplatelet use, nonsteroidal anti-inflammatory use, liver disease, and bleeding history, with each additional point scored associated with a 48.7% (95% CI, 38.9%–59.3%; P <0.001) increase in major bleeding in RE-LY. The score had superior performance to the HAS-BLED score in RE-LY (C statistic, 0.73 versus 0.60; P for difference <0.001) and among 12 296 individuals in GARFIELD-AF (C statistic, 0.71 versus 0.66; P for difference = 0.025). The DOAC Score had stronger predictive performance than the HAS-BLED score in both validation cohorts, including 25 586 individuals in COMBINE-AF (C statistic, 0.67 versus 0.63; P for difference <0.001) and 11 945 individuals in RAMQ (C statistic, 0.65 versus 0.58; P for difference <0.001). CONCLUSIONS: In individuals with atrial fibrillation potentially eligible for DOAC therapy, the DOAC Score can help stratify patients on the basis of expected bleeding risk.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».