Efficacy and safety of inclisiran in patients with polyvascular disease: pooled, post hoc analysis of the ORION-9, ORION-10 and ORION-11, phase 3 randomised controlled trials
Notice bibliographique
Résumé
Abstract Background Approximately 25% of patients (pts) with atherosclerotic cardiovascular disease (ASCVD) have polyvascular disease (PVD), which involves ≥2 coronary, cerebrovascular, and peripheral artery beds. PVD is an independent predictor of major adverse cardiovascular (CV) events (MACE) and death.[1,2] Agents that inhibit proprotein convertase subtilisin-kexin type 9 (PCSK9) resulted in reduced low-density lipoprotein cholesterol (LDL-C) concentration and MACE incidence in pts with PVD.[3,4] Inclisiran is a small interfering RNA (siRNA) agent targeting PCSK9 messenger RNA that provided effective and sustained reduction in LDL-C concentration and was well tolerated.[5] Purpose To describe the effect inclisiran versus placebo (pbo) in pts with and without PVD. Methods This was a post hoc analysis from the ORION-9 (NCT03397121), ORION-10 (NCT03399370) and ORION-11 (NCT03400800) trials. Pts with heterozygous familial hypercholesterolaemia, ASCVD or risk equivalents were randomised 1:1 to receive 300 mg inclisiran sodium (equivalent to 284 mg inclisiran) or pbo at baseline, Day 90, and 6-monthly thereafter. LDL-C percentage change from baseline to Day 510 and corresponding time-averaged change from Day 90 and to Day 540 were evaluated by presence or absence of PVD (intention-to-treat population). Safety was assessed over 540 days (safety population). Results Of 3454 pts, 470 (13.6%) had PVD and 2984 (86.4%) did not. Baseline characteristics were generally balanced between treatment arms in both groups (Table 1). A greater proportion of pts with vs without PVD had CV risk factors at baseline. Mean LDL-C concentration at baseline was lower in pts with vs without PVD (Table 1). Mean (95% CI) pbo-corrected LDL-C percentage change from baseline to Day 510 with inclisiran was −48.9 (−55.6 to −42.2) in pts with PVD and −51.5 (−53.9 to −49.1) in pts without PVD (Table 2). Proportions of pts with treatment-emergent adverse events (TEAE) and treatment-emergent serious adverse events (TESAE) were similar between treatment arms irrespective of PVD status although reported TESAEs were numerically greater in both treatment arms for pts with PVD (Table 2). Clinically relevant TEAEs at the injection site were reported more frequently with inclisiran vs pbo in both groups but all were mild or moderate (Table 2). Proportions of pts with clinically relevant laboratory measurements were low and similar between treatment arms for both groups (Table 2). Conclusions Twice-yearly dosing with inclisiran (after the initial and 3-month doses) provided effective and sustained LDL-C lowering in pts, irrespective of their PVD status, with a safety profile similar to pbo, except for a modest excess of mainly mild TEAEs at the injection site. Notably, TESAEs were reported more frequently in pts with PVD, which was likely due to their more advanced disease. Since pts with PVD are at high risk of CV events, intensive LDL-C lowering may be beneficial to reduce this risk. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Novartis Pharma AG, Basel, Switzerland
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 | 0,014 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,010 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».