A System to Monitor Safety in Interventional Cardiology

描述（由申请人提供）：介入心脏病学是一个动态发展的医学领域，代表了美国用于治疗冠状动脉疾病的最常见血运重建策略。在过去的几年里，已经引入了许多新的医疗设备，这大大扩大了可以成功治疗的患者范围。虽然新器械的批准受到严格监管，但上市后的安全性评价却没有明确规定。目前评估医疗器械安全性的做法依赖于供应商的自愿报告，存在报告不足、时间延迟和无法评估不良事件发生率的问题。我们建议开发一个系统，利用贝叶斯更新策略来监测引入临床介入心脏病学实践的新医疗器械的安全性，以解决其中的一些缺陷。 贝叶斯方法将有关医疗器械安全性的现有知识（通常来自已发表的临床试验数据）以及观察到的数据纳入不良事件风险估计中。使用经验证的风险分层方法，我们建议监测不良事件的频率，以评估手术随时间推移的当前风险状态。我们计划根据历史和前瞻性数据评价方法学，探索在介入心脏病学中使用两种新兴器械类别（药物洗脱支架和滤器型远端保护器械）的相关风险。对309例接受旋切术的患者进行的方法学初步探索证明了在研究期间监测风险估计演变的可行性。 我们建议开发一个正式的理论框架，建立先验概率估计以及方法比较结果的贝叶斯系统的经典统计。然后，我们将开发安全监测分析软件，实施贝叶斯方法和经典统计方法，并将该系统部署为我们设施中现有的结果跟踪数据库系统的一个组成部分。我们提出了一个详细的分析，这将有助于确定贝叶斯框架是否有任何优势，在监测介入心脏病学设备的安全性的经典方法。一旦验证，分析软件将公开提供。

DESCRIPTION (provided by applicant): Interventional cardiology is a dynamically evolving field of medicine and represents the most frequent revascularization strategy used for the treatment of coronary artery disease in the United States. Over the past several years, numerous new medical devices have been introduced, which have greatly expanded the spectrum of patients that can be successfully treated. While the approval for the release of new devices is rigorously regulated, the post-marketing evaluation of safety is less clearly defined. Current practices for assessing the safety of medical devices depend on voluntary reporting by providers, and suffer from underreporting, temporal delays and the inability to assess rates of adverse events. We propose to develop a system to monitor the safety of new medical devices introduced into clinical interventional cardiology practice, utilizing a Bayesian updating strategy that addresses some of these deficiencies. The Bayesian methodology incorporates existing knowledge regarding the safety of a medical device, typically from published clinical trial data, as well as observed data into the estimate of the risk of an adverse event. Using validated risk stratification methods, we propose to monitor the frequency of adverse events in order to assess the current state of risk of a procedure over time. We plan to evaluate the methodology on both historical and prospective data exploring the risks associated with the use of two emerging device classes within interventional cardiology: drug eluting stents, and filter-type distal protection devices. Preliminary exploration of the methodology for 309 patients who underwent rotational atherectomy demonstrates the feasibility of monitoring the evolution of risk estimates over the study period. We propose to develop a formal theoretic framework for the establishment of prior probability estimates as well as methods for comparing results from the Bayesian system to that of classical statistics. We will then develop the safety monitoring analytic software, implementing both the Bayesian methodology as well as classical statistical methods, and deploy the system as a component of the outcomes tracking database system in existence in our facility. We propose a detailed analysis that will help determine if the Bayesian framework has any advantages over classical methods in monitoring device safety in interventional cardiology. Once validated, the analytic software will be made publicly available.