The efficacy and safety of the prasugrel, ticagrelor, and clopidogrel dual antiplatelet therapies following an acute coronary syndrome: A systematic review and Bayesian network meta-analysis
Notice bibliographique
Résumé
ABSTRACT Background The dual-antiplatelet therapies (DAPT) of clopidogrel, prasugrel, or ticagrelor in concomitant use with acetylsalicylic acid are the contemporary treatment regimens for acute coronary syndromes (ACS). Systematic comparative effectiveness and safety analyses currently lack clinically meaningful interpretations of the summarized evidence. Methods We systematically searched MEDLINE, EMBASE, CENTRAL, and clinicaltrials.gov for randomized controlled trials (RCTs) that reported on either the efficacy or safety between clopidogrel, prasugrel, or ticagrelor DAPTs in ACS patients. The primary efficacy endpoint was a composite of all-cause mortality, a recurrent non-fatal myocardial infarction, or non-fatal stroke. The primary safety endpoint was study-reported major bleeding events. A Bayesian network meta-analysis was performed using a generalized linear model logit transformation with a log-transformation of ‘time’ for varying lengths of study follow-up. Studies published in either English or French with a minimum of 6 months of follow-up and a “low” rating from the Cochrane risk of bias assessment tool were included in the main analyses. Fixed and random effects models fit was assessed by the deviance information criterion (DIC) and node-splitting methods were used to assess the consistency of direct and indirect network evidence. An HR >0.9 and <1.11 were set as our clinically important thresholds, and represented the range of practical equivalence (ROPE). Results From a total of 15,232 articles identified, 138 were selected for full-text review. From a total of 29 identified RCT’s, 17 trials, representing 57,814 subjects, were identified as a “low” risk of bias and were included in the final Bayesian network meta-analysis. Compared to clopidogrel, prasugrel and ticagrelor reduced major acute coronary events (MACE) endpoints by a median of 13% (Hazard ratio [HR]PC, 0.87; 95% credible interval [95% CrI]: 0.74, 1.06) and 5% (HRTC, 0.95; 95% CrI: 0.81, 1.14), respectively. The HR posterior distributions estimated that prasugrel had a 67.5% chance of producing a clinically meaningful – greater than 10% (HR<0.9) – decrease in the risk of MACE outcomes, while ticagrelor only had a 22.4% chance of exceeding the clinically important threshold. The primary safety outcome found prasugrel (HRPC, 1.23; 95% CrI: 1.04, 1.40) and ticagrelor (HRTC, 1.07; 95% CrI: 0.99, 1.17) DAPTs to be associated with a median increase in events relative to clopidogrel. This translates to a probability of a clinically meaningful increase (HR>1.11) in major bleeding of 83.7% for prasugrel and 67.7% for ticagrelor, when compared to clopidogrel. Conclusion When compared with ACS patients assigned to clopidogrel, prasugrel and ticagrelor were associated with moderate and modest probabilities respectively in clinically meaningful MACE reductions. Prasugrel and ticagrelor had high and modest probabilities respectively of clinically meaningful increases in bleeding. Despite guideline recommendations, the net clinical benefit for these drugs compared to clopidogrel appears uncertain.
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 | 0,032 | 0,062 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,017 | 0,034 |
| Bibliométrie | 0,015 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».