REDUCE-IT: total ischemic events reduced across the full range of baseline LDL cholesterol and other key subgroups
Notice bibliographique
Résumé
Abstract Background REDUCE-IT (Reduction of Cardiovascular Events with Icosapent Ethyl-Intervention Trial), a study of 8,179 randomized statin-treated patients with elevated triglycerides (TG) and increased cardiovascular (CV) risk followed for a median of 4.9 years, demonstrated robust results. Icosapent ethyl (IPE), a pure and stable prescription form of eicosapentaenoic acid, 4g/day reduced both time-to-first and total primary endpoint ischemic events (CV death, nonfatal myocardial infarction [MI], nonfatal stroke, coronary revascularization, or hospitalization for unstable angina) by 25% (HR 0.75; 95% CI 0.68–0.83; p<0.0001) and 30% (rate ratio 0.70; 95% CI 0.62–0.78; p<0.0001), respectively. Similar substantial reductions in first and total key secondary endpoint ischemic events (composite of CV death, nonfatal MI, or nonfatal stroke) were also observed. Demographic and baseline disease characteristics were generally balanced across treatment groups. Time-to-first event analyses showed robust and generally consistent benefit across subgroups. Previous total event analyses by baseline TG demonstrated large, consistent, statistically significant reductions across tertiles, suggesting the CV benefit of IPE is tied primarily to non-TG factors. Purpose Further explore the extent to which IPE reduced total primary and key secondary events across prespecified baseline demographic, disease, treatment, and lipid/lipoprotein/inflammatory biomarker subgroups. Methods Total events across subgroups were assessed with the prespecified negative binomial regression method. Main outcomes were total (first and subsequent) primary and key secondary composite endpoint events. Results Median baseline LDL-C levels in ascending tertiles were 58, 76, and 96 mg/dL; there were large, significant relative reductions in total primary endpoint events with IPE across tertiles (35%, 28%, and 27%, respectively; interaction p=0.62), with parallel substantial absolute risk reductions. Similar, significant relative reductions of 33%, 28%, and 24% in total key secondary endpoint events were observed, along with substantial absolute risk reductions. Total events analyses of prespecified subgroups also demonstrated robust and generally consistent findings for the primary and key secondary composite endpoints. Conclusion REDUCE-IT demonstrated substantial reductions in first and total primary and key secondary endpoint ischemic events, with robust and generally consistent results across baseline TG and LDL-C levels, as well as other prespecified baseline biomarker, demographic, disease, and treatment subgroups. These analyses provide useful insights for clinicians considering the range of patients who may benefit from IPE therapy and suggest that mechanisms beyond the lipid/lipoprotein/inflammatory pathways tested, including mechanisms beyond the LDL receptor pathways, may contribute to the observed substantial reductions in total ischemic burden with IPE therapy. Funding Acknowledgement Type of funding source: Other. Main funding source(s): The study was funded by Amarin Pharma, Inc.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| 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) | 0,003 | 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 ».