Comparing Three Evidence-Based Strategies to Reduce Cardiovascular Disease Burden: An Individual-Based Cardiometabolic Policy Simulation

Sylvia Lutze, Steve Bachmeier, Alison Bowman, Nicole DeCleene, Hussain Jafari, Matthew Kappel, Caroline Kinuthia, Paulina Lindstedt, Megan Lindstrom, Rajan Mudambi, Christian Razo, Kjell Swedin, Abraham Flaxman, Gregory A. Roth
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Abstract

Background: Understanding the real-world impact of clinical trials is important for informing health care policy. This is particularly true when trials are designed to show changes in surrogate endpoints such as changes in risk factors rather than events or mortality. We developed an agent-based microsimulation that estimates the population-level benefits in each US state for cardiometabolic health interventions shown to improve risk factors. Methods: We designed a large-scale, location-specific agent-based simulation model with a population of 51 million in silico individuals and estimated results for the years 2023 to 2040 in 30-day steps for each of the 50 states and District of Columbia. Input data reflected current cardiometabolic health in each state and the effects of interventions and risk factors on outcomes. We constructed three health policy intervention scenarios based on successful randomized controlled trials designed to improve cardiometabolic population health: improved access to fixed-dose combination (FDC) antihypertensive medication, a pharmacist-led intervention to increase adherence to statin and antihypertensives medications at the time they are initiated (Pharmacy), and a community-based lifestyle and behavior intervention designed to prevent diabetes (Community). Outcomes included myocardial infarction, ischemic and non-ischemic heart failure, and ischemic stroke events, deaths, and disability-adjusted life years (DALYs). Results: Our simulation included a representative population of the United States, accurate at the age, sex, and state level, with individual people simulated over 17 years. By the year 2040, the FDC intervention was estimated to have prevented 776,000 (95% UI 578,000?956,000) CVD DALYs and 44,600 (95% UI 32,700?55,600) deaths annually. Reductions in ischemic heart disease deaths accounted for 76.5% of the total reductions in CVD deaths. The Pharmacist intervention prevented 170,000 (95% UI 129,000?208,000) CVD DALYs, and the Community intervention prevented 152,000 (95% UI 128,000?173,000) CVD DALYs. Conclusions: A fixed-dose combination of antihypertensives could prevent 1.2% of total CVD DALYs, with smaller benefits from adherence and lifestyle-focused programs and impact of interventions varying by state. The greatest reduction was in incident myocardial infarctions and ischemic heart disease deaths. Providing accurate population-level estimates at the state level can help local health policy decision-makers implement the most impactful interventions.
降低心血管疾病负担的三种循证策略比较:基于个人的心脏代谢政策模拟
背景:了解临床试验对真实世界的影响对于制定医疗政策非常重要。当试验旨在显示代用终点(如风险因素的变化而非事件或死亡率的变化)的变化时,尤其如此。我们开发了一种基于代理的微观模拟,可以估算出美国各州在心脏代谢健康干预措施改善风险因素方面的人群受益情况:方法:我们设计了一个大规模的、针对特定地区的基于代理的模拟模型,该模型拥有 5100 万硅基个体,并以 30 天为一个步骤,对美国 50 个州和哥伦比亚特区中的每个州估算了 2023 年至 2040 年的结果。输入数据反映了各州当前的心脏代谢健康状况以及干预措施和风险因素对结果的影响。我们根据成功的随机对照试验构建了三种健康政策干预方案,旨在改善心血管代谢人群的健康状况:改善固定剂量联合(FDC)降压药的可及性;药剂师主导的干预措施,以提高他汀类药物和降压药在用药时的依从性(药房);以及基于社区的生活方式和行为干预措施,旨在预防糖尿病(社区)。结果包括心肌梗死、缺血性和非缺血性心力衰竭、缺血性中风事件、死亡和残疾调整生命年(DALYs):我们的模拟包括具有代表性的美国人口,在年龄、性别和州一级都非常准确,每个人的模拟时间超过 17 年。据估计,到 2040 年,FDC 干预每年可预防 776,000 (95% UI 578,000?956,000) 个心血管疾病 DALYs 和 44,600 (95% UI 32,700?55,600) 例死亡。缺血性心脏病死亡人数的减少占心血管疾病死亡总人数减少的 76.5%。药剂师干预预防了 170,000 (95% UI 129,000?208,000) 例心血管疾病残疾调整寿命年,社区干预预防了 152,000 (95% UI 128,000?173,000) 例心血管疾病残疾调整寿命年。结论固定剂量的联合降压药可预防 1.2% 的心血管疾病致死残疾调整寿命年数,而坚持治疗和注重生活方式的计划带来的益处较小,干预措施的影响因州而异。减少最多的是心肌梗死和缺血性心脏病死亡。在州一级提供准确的人口估计值有助于地方卫生政策决策者实施最具影响力的干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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