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Optimal cholesterol treatment plans and genetic testing strategies for cardiovascular diseases

机译:胆固醇治疗计划和心血管疾病的遗传学检测策略

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Atherosclerotic cardiovascular disease (ASCVD) is among the leading causes of death in the US. Although research has shown that ASCVD has genetic elements, the understanding of how genetic testing influences its prevention and treatment has been limited. To this end, we model the health trajectory of patients stochastically and determine treatment and testing decisions simultaneously. Since the cholesterol level of patients is one controllable risk factor for ASCVD events, we model cholesterol treatment plans as Markov decision processes. We determine whether and when patients should receive a genetic test using value of information analysis. By simulating the health trajectory of over 64 million adult patients, we find that 6.73 million patients undergo genetic testing. The optimal treatment plans informed with clinical and genetic information save 5,487 more quality-adjusted life-years while costing $1.18 billion less than the optimal treatment plans informed with clinical information only. As precision medicine becomes increasingly important, understanding the impact of genetic information becomes essential.
机译:动脉粥样硬化性心血管疾病(ASCVD)是美国的主要死亡原因之一。尽管研究表明ASCVD具有遗传因素,但对基因检测如何影响其预防和治疗的理解有限。为此,我们对患者的健康轨迹进行随机建模,并同时确定治疗和检测决策。由于患者的胆固醇水平是ASCVD事件的一个可控风险因素,我们将胆固醇治疗计划建模为马尔可夫决策过程。我们利用信息价值分析确定患者是否以及何时应该接受基因检测。通过模拟6400多万成年患者的健康轨迹,我们发现673万患者接受了基因检测。根据临床和遗传信息制定的最佳治疗计划比仅根据临床信息制定的最佳治疗计划节省了5487个经质量调整后的生命年,同时成本降低了11.8亿美元。随着精确医学变得越来越重要,了解基因信息的影响变得至关重要。

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