通过模拟试验来预测新型降脂药物对心血管的保护作用:通过 SIRIUS 计划的设计来说明。

IF 8.4 2区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
D Angoulvant, S Granjeon-Noriot, P Amarenco, A Bastien, E Bechet, F Boccara, J P Boissel, B Cariou, E Courcelles, A Diatchenko, A Filipovics, R Kahoul, G Mahé, E Peyronnet, L Portal, S Porte, Y Wang, P G Steg
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引用次数: 0

摘要

简介Inclisiran是一种靶向肝脏PCSK9 mRNA的siRNA,在III期试验中,每年给药两次(在首次给药和3个月给药后)可持续大幅降低低密度脂蛋白胆固醇(LDL-C)。使用 inclisiran 降低低密度脂蛋白胆固醇是否会降低主要不良心血管事件(MACE)的风险,目前尚未确定。将疾病计算模型应用于接受新疗法的虚拟患者的硅内试验可以模拟大规模的长期临床试验。SIRIUS ilico 试验计划旨在预测 inclisiran 对已确诊动脉粥样硬化性心血管疾病(ASCVD)患者心血管事件的疗效:SIRIUS 虚拟人群包括已确诊的 ASCVD 患者(既往有心肌梗死 (MI)、既往有缺血性中风 (IS)、既往有症状性下肢外周动脉疾病 (PAD),定义为间歇性跛行且踝肱指数透视/结论:SIRIUS 虚拟人群包括已确诊的 ASCVD 患者(既往有心肌梗死 (MI)、既往有缺血性中风 (IS)、既往有症状性下肢外周动脉疾病 (PAD),定义为间歇性跛行且踝肱指数透视/结论):SIRIUS 尼基试验计划将提供有关 inclisiran 对 ASCVD 患者 MACE 潜在影响的早期见解,这比正在进行的 CV 结果试验(ORION-4 和 VICTORION-2-P)的结果要早几年。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In-silico trial emulation to predict the cardiovascular protection of new lipid-lowering drugs: an illustration through the design of the SIRIUS programme.

Introduction: Inclisiran, an siRNA targeting hepatic PCSK9 mRNA, administered twice-yearly (after initial and 3-month doses), substantially and sustainably reduced LDL-cholesterol (LDL-C) in Phase III trials. Whether lowering LDL-C with inclisiran translates into a reduced risk of major adverse cardiovascular events (MACE) is not yet established. In-silico trials applying a disease computational model to virtual patients receiving new treatments allow to emulate large scale long term clinical trials. The SIRIUS in-silico trial programme aims to predict the efficacy of inclisiran on CV events in individuals with established atherosclerotic cardiovascular disease (ASCVD).

Methods: A knowledge-based mechanistic model of ASCVD was built, calibrated, and validated to conduct the SIRIUS programme (NCT05974345) aiming to predict the effect of inclisiran on CV outcomes.The SIRIUS Virtual Population included patients with established ASCVD (previous myocardial infarction (MI), previous ischemic stroke (IS), previous symptomatic lower limb peripheral arterial disease (PAD) defined as either intermittent claudication with ankle-brachial index <0.85, prior peripheral arterial revascularization procedure, or vascular amputation) and fasting LDL-C ≥ 70 mg/dL, despite stable (≥ 4 weeks) well-tolerated lipid lowering therapies.SIRIUS is an in-silico multi-arm trial programme. It follows an idealized crossover design where each virtual patient is its own control, comparing inclisiran to 1) placebo as adjunct to high-intensity statin therapy with or without ezetimibe, 2) ezetimibe as adjunct to high-intensity statin therapy, 3) evolocumab as adjunct to high-intensity statin therapy and ezetimibe.The co-primary efficacy outcomes are based on time to the first occurrence of any component of 3P-MACE (composite of CV death, nonfatal MI or nonfatal IS) and time to occurrence of CV death over 5 years.

Perspectives/conclusion: The SIRIUS in-silico trial programme will provide early insights regarding a potential effect of inclisiran on MACE in ASCVD patients, several years before the availability of the results from ongoing CV outcomes trials (ORION-4 and VICTORION-2-P).

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来源期刊
European journal of preventive cardiology
European journal of preventive cardiology CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
12.50
自引率
12.00%
发文量
601
审稿时长
3-8 weeks
期刊介绍: European Journal of Preventive Cardiology (EJPC) is an official journal of the European Society of Cardiology (ESC) and the European Association of Preventive Cardiology (EAPC). The journal covers a wide range of scientific, clinical, and public health disciplines related to cardiovascular disease prevention, risk factor management, cardiovascular rehabilitation, population science and public health, and exercise physiology. The categories covered by the journal include classical risk factors and treatment, lifestyle risk factors, non-modifiable cardiovascular risk factors, cardiovascular conditions, concomitant pathological conditions, sport cardiology, diagnostic tests, care settings, epidemiology, pharmacology and pharmacotherapy, machine learning, and artificial intelligence.
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