Randomized Cardiovascular Trials Duplicated Using Prospective Longitudinal Insurance Claims: Applying Techniques of Epidemiology (RCT DUPLICATE)
Randomized Cardiovascular Trials Duplicated Using Prospective Longitudinal Insurance Claims: Applying Techniques of Epidemiology (RCT DUPLICATE)
批准号:
10392863
负责人:
Sebastian G. Schneeweiss
金额:
$71.34万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-01 至 2024-03-31
关键词:
Cardiovascular systemCharacteristicsClinicalDataData AnalysesDatabasesDecision MakingDrug ApprovalEducational workshopEnsureEpidemiologic MethodsEpidemiologyEvaluationExclusion CriteriaFactor AnalysisFutureGoldHealthHealthcareIndividualInternetKnowledgeLeadMeasuresMeta-AnalysisMethodologyMethodsModelingObservational StudyOutcomePatientsPerformancePharmaceutical PreparationsPopulationProviderPublic HealthPublishingRandomizedRandomized Controlled TrialsReportingResearchResearch DesignResearch PersonnelReview LiteratureSamplingSavingsTechniquesVariantWorkWorld Healthanalytical methodbasecostdesignhealth dataimprovedinnovationinsightinsurance claimspatient populationprospectiverandomized trialsearchable databasesuccesstreatment comparisontreatment effectunethical
中文摘要
项目摘要
随机对照试验(RCT)仍然是确定两者之间因果关系的黄金标准
药物和健康结果。然而,对于某些临床问题,随机对照试验可能不可行、不道德、
成本高昂,或仅适用于极少数人群。在这些情况下,常规观察研究
收集的“真实世界”健康数据(RWD)对于补充随机对照试验的证据至关重要。后行距离为
在心血管结果方面特别有用,这些结果通常在医疗保健中得到很好的体现
数据库,但对 RWD 研究有效性的担忧减轻了其影响。该项目的目的是
通过对大样本进行系统复制来实证评估 RWD 研究的有效性
心血管结局的随机试验,包括已完成的试验和已经获得结果的试验
正在进行的试验,结果尚未公布,以确保有效性不受
试验结果的可用性。 RWD 研究旨在尽可能匹配相应的 RCT,
包括暴露、结果和纳入/排除标准,RWD 研究采用多种设计
和分析方法,以便为可以在 RWD 中回答哪些问题提供指导
哪些方法。作为该项目的一部分,将开发一个新的荟萃分析模型来模拟
RCT 和 RWD 之间的治疗效果估计,结合 RWD 方法学方法的数据
以及临床问题。所有研究的所有治疗效果估计,包括 RCT 和 RWD
结果将在线报告,正在进行的随机对照试验的结果将在可用时添加。这个
该项目是第一个基于经验评估心血管结果 RWD 研究有效性的项目
在广泛的流行病学和分析领域的大样本临床问题中的表现
方法。研究结果将指导研究人员规划心血管结局的 RWD 研究,并增加
对 RWD 研究回答对患者、提供者和其他人员重要的问题的能力充满信心
利益相关者。
英文摘要
Project Abstract
Randomized controlled trials (RCTs) remain the gold standard for establishing the causal relationship between
medications and health outcomes. However, for some clinical questions RCTs may be infeasible, unethical,
costly, or generalizable to only a very narrow population. In these cases, observational studies from routinely
collected “real-world” health data (RWD) are crucial for supplementing the evidence from RCTs. RWD is
particularly useful in the context of cardiovascular outcomes, which are typically well-captured in healthcare
databases, but concern about the validity of RWD studies mitigate their impact. The purpose of this project is
to empirically evaluate the validity of RWD studies by conducting a systematic replication of a large sample of
randomized trials of cardiovascular outcomes, including both completed trials with results already available and
ongoing trials where results are not yet released, in order to ensure that validity is not influenced by the
availability of trial results. RWD studies are designed to match the corresponding RCT as closely as possible,
including exposures, outcomes, and inclusion/exclusion criteria, and RWD studies utilize a variety of design
and analysis approaches in order to provide guidance on which questions can be answered in RWD and with
which methods. As part of this project, a new meta-analysis model will be developed to model the variation in
treatment effect estimates between RCTs and RWD, combining data across RWD methodologic approaches
and across clinical questions. All treatment effect estimates for all studies, including both RCT and RWD
results, will be reported online, and the results of ongoing RCTs will be added as they become available. This
project is the first to evaluate the validity of RWD studies of cardiovascular outcomes based on empirical
performance in a large sample of clinical questions across a wide variety of epidemiologic and analytical
methods. Findings will guide investigators planning RWD studies of cardiovascular outcomes and increase
confidence in the ability of RWD studies to answer questions of importance to patients, providers, and other
stakeholders.
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专著(0)
科研奖励(0)
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