Methods for studying treatment heterogeneity using large observational databases

我们提出了一个多阶段的研究计划，以开发、验证、应用和传播 评估和传达个人水平在有效性和安全性方面的异质性(针对一系列 患者/临床医生确定感兴趣的结果)进行非随机化比较有效性研究。这个 研究计划将把理论转化为实践，并为临床决策支持工具制作模板 可用于促进个性化医疗和知情决策，同时解决 个别病人的个人特征、病情和喜好。 分析随机临床试验的统计方法的最新创新涉及个体预测 患者体验益处和/或伤害的概率。在K99颁奖阶段，我将与 我的导师和合作者在我们为非随机化比较有效性研究开发方法时 这使我们能够根据一组患者预测不同个体水平的治疗效果 特点。在此期间，我将参加博士后医学信息学研究培训 哈佛医学院计划，重点是与临床和人口健康相关的培训 信息学。我还将积极参与有关患者/利益相关者等主题的教育和培训 通过布里格姆妇女医院(BWH)中心进行以患者为中心的比较 有效性研究(PCERC)。在颁奖的R00阶段，我将征求患者和 BWH PCERC患者和家庭咨询委员会(PFAC)的医生成员关于选择 在可供选择的降脂治疗策略之间。我将与他们合作，以确定安全和 效力结果是他们所代表和理解的利益相关者群体优先关注的问题 他们对个性化治疗信息的期望。我们将应用经过验证的方法来估计 在使用大型、多样化医疗保健数据库的研究中，个体水平的治疗异质性。这些研究将 旨在解决患者和提供者确定的优先问题。将会有持续的投入 来自患者和提供者，因为我致力于开发旨在沟通的临床决策支持工具 相关证据，使用医疗保健消费者理解的指标。我将使用通过 医学信息学培训计划和与临床信息学部门成员的合作 在BWH实施和测试循证临床决策支持工具，该工具与 医院信息基础设施。此工具可在办公室访问期间使用，帮助医生和患者 讨论每个患者在关键时刻所特有的预期风险和收益 当他们做出治疗决定时，去办公室拜访.

We propose a multi-phase program of research to develop, validate, apply and disseminate methods for estimating and communicating individual level heterogeneity in effectiveness and safety (for a range of patient/clinician identified outcomes of interest) for non-randomized comparative effectiveness research. The research program will translate theory to practice, and produce a template for clinical decision support tools that could be used to facilitate personalized medicine and informed decision making while addressing the personal characteristics, conditions and preferences of individual patients. Recent innovations in statistical methods for analyzing randomized clinical trials involve prediction of individual patient probabilities of experiencing benefit and/or harm. During the K99 phase of the award, I will work with my mentors and collaborators as we develop methods for non-randomized comparative effectiveness research which allow us to predict heterogeneous individual level treatment effects based on a constellation of patient characteristics. During this time, I will participate in the Postdoctoral Medical Informatics Research Training program at Harvard Medical School with a focus on training related to clinical and population health informatics. I will also be an active participant in education and training on topics such as patient/stakeholder engagement through the Brigham and Women's Hospital (BWH) Center for Patient Centered Comparative Effectiveness Research (PCERC). During the R00 phase of the award, I will solicit input from patient and physician members of the Patient and Family Advisory Councils (PFAC) at BWH PCERC regarding choices between alternative lipid lowering therapeutic strategies. I will work with them to identify safety and effectiveness outcomes that are priority concerns for the stakeholder groups they represent and understand what they expect from personalized treatment information. We will apply validated methods for estimating individual level treatment heterogeneity in studies using large, diverse healthcare databases. These studies will be designed to address the patient and provider identified priority questions. There will be continuous input from patients and providers as I work on developing clinical decision support tools designed to communicate relevant evidence, using metrics that healthcare consumers understand. I will use the skills developed through the Medical Informatics Training Program and collaborate with members of the Clinical Informatics Department at BWH to implement and test an evidence-based clinical decision support tool that is compatible with the hospital informatics infrastructure. This tool could be used during the office visit to help physicians and patients discuss the expected risks and benefits that are particular to each patient at a “critical moment”, during the office visit when they the treatment decision is being made.