Optimal Decision Making in Aortic Valve Replacement

主动脉瓣置换术的最佳决策

• 批准号: 8635238
• 负责人: Suzanne Victoria Arnold
• 金额: $ 12.29万
• 依托单位: SAINT LUKE'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-01 至 2019-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8635238
• 关键词: Aftercare; Aortic Valve Stenosis; Back; Benefits and Risks; Blood Vessels; Cardiac Surgery procedures; Cardiovascular Diseases; Caring; Cessation of life; Characteristics; Clinic; Clinical; Clinical Trials; Comorbidity; Data; Decision Making; Disease; Economic Models; Economics; Elderly; Emerging Technologies; Evaluation; Frail Elderly; Goals; Health Care Costs; Health Care Reform; Healthcare; Heart Valve Diseases; Heterogeneity; Individual; Intervention; Life Expectancy; Living Costs; Longevity; Medical; Medical Technology; Methods; Modeling; Online Systems; Operative Surgical Procedures; Outcome; Outpatients; Patients; Policies; Policy Maker; Population; Procedures; Prospective Studies; Public Policy; Quality of Care; Quality of life; Randomized; Research Infrastructure; Risk; Stroke; Technology; Testing; Time; Vision; adverse outcome; alternative treatment; aortic valve replacement; base; care preference; career; career development; clinical care; cost; cost effective; cost effectiveness; data modeling; economic cost; evidence base; experience; feeding; improved; innovation; interest; mortality; novel; older patient; patient oriented; patient population; programs; public health relevance; response; shared decision making; tool; treatment effect; valve replacement

DESCRIPTION (provided by applicant): Aortic stenosis is a highly prevalent disease among elderly patients and causes reduced life expectancy, poor quality of life (QoL), and increased healthcare costs. In the setting of severe, symptomatic aortic stenosis, valve replacement is the mainstay of treatment, which has traditionally meant open-heart surgery. Recently, transcatheter aortic valve replacement (TAVR) has emerged as a less-invasive approach to valve replacement, and is particularly attractive in elderly patients with multiple comorbidities. n the Placement of AoRTic TraNscathetER Valve (PARTNER) Trial, which randomized patients too ill to undergo surgery to medical therapy or TAVR, TAVR patients had improved survival and better QoL than those receiving medical therapy alone. Despite the benefits of TAVR, nearly 1/3 were dead within 1 year of treatment, and approximately half did not benefit from TAVR (either dead or no QoL improvement at 1 year). Given the upfront risks and costs of TAVR, identifying patients, prior to the procedure, who are unlikely to benefit can enable patients and practitioners to make a more informed decision about whether or not to undergo the procedure. Using data from the PARTNER trial and other ongoing prospective studies, we will build economic and QoL prediction models to support the most efficient use of this emerging technology. In order to accomplish these goals, we plan to use both multivariable statistical and decision analytic models of survival, QoL and costs try to clarify the potential risks and benefits of particular patients undergoing TAVR, thus quantifying the heterogeneity of treatment benefits and enabling these estimates to be calculated on a patient-by-patient basis. We then plan to feed this information back to patients and practitioners at the time when the treatment decision is being made using a novel web-based technology that can generate individualized estimates of patients' predicted risks and outcomes. These estimates of clinical outcomes (e.g. QoL) can then be incorporated into patient-specific shared decision-making tools. Providing these data prospectively to patients and practitioners will support a novel dialogue, based on the evidence-based, projected outcomes of the individual patient. In addition, the economic models can support policy decisions that allocate TAVR in the most cost-effective manner. Altogether, these studies will allow for the most effective and efficient application of this exciting and innovative medical technology.

描述（由申请人提供）：主动脉狭窄是老年患者的高度普遍疾病，导致预期寿命降低，生活质量差（QOL）和医疗保健成本的增加。在严重，有症状的主动脉狭窄的情况下，瓣膜置换是治疗的主要手段，传统上意味着心脏直视手术。最近，经导管主动脉瓣置换（TAVR）已成为替代瓣膜替代的一种侵入性方法，并且在多种合并症的老年患者中特别有吸引力。 n主动脉经导管瓣（伴侣）试验的放置，该试验的随机患者对医疗疗法或TAVR进行了手术，TAVR患者的生存率和QOL比单独接受医疗疗法的患者更好。尽管塔夫（Tavr）受益，但在治疗后的1年内，将近1/3死亡，大约一半并未受益于TAVR（在1年时死亡或无QOL改进）。鉴于TAVR的前期风险和成本，在手术之前识别患者，不太可能受益的患者可以使患者和从业者能够 为了做出是否接受程序做出更明智的决定。使用合作伙伴试验和其他正在进行的前瞻性研究的数据，我们将建立经济和质量质量预测模型，以支持最有效地利用这一新兴技术。为了实现这些目标，我们计划同时使用生存的多变量统计和决策分析模型，QOL和成本，以阐明接受TAVR的特定患者的潜在风险和收益，从而量化治疗益处的异质性并使这些估计能够根据患者的依据进行计算。然后，我们计划在使用一种新型的基于Web的技术做出治疗决定时将这些信息馈回患者和从业人员，该技术可以对患者的预测风险和结果进行个性化估计。这些临床结果（例如QOL）的估计值可以纳入患者特定的共享决策工具中。前瞻性地向患者和从业人员提供这些数据将根据基于证据的个人患者的预测结果来支持新的对话。此外，经济模型可以支持以最具成本效益的方式分配TAVR的政策决策。总之，这些研究将允许最有效，最有效地应用这种令人兴奋和创新的 医疗技术。