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)仍然是建立以下因果关系的金标准:
药物和健康结果。然而,对于某些临床问题,RCT可能是不可行的,不道德的,
昂贵的,或仅适用于非常狭窄的人群。在这些情况下,常规的观察性研究
收集的“真实世界”健康数据(RWD)对于补充RCT的证据至关重要。RWD是
在心血管结局的背景下特别有用,这通常在医疗保健中得到很好的捕获
数据库,但对RWD研究的有效性的关注减轻了其影响。本项目的目的是
通过对大样本进行系统复制,
心血管结局的随机试验,包括已完成且结果已获得的试验,
正在进行的试验,其结果尚未发布,以确保有效性不受
获得试验结果。RWD研究旨在尽可能匹配相应的RCT,
包括暴露、结局和入选/排除标准,RWD研究采用各种设计
和分析方法,以提供关于哪些问题可以在RWD中回答的指导,
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,以模拟
RCT和RWD之间的治疗效果估计,结合RWD方法学方法的数据
和临床问题。所有研究的所有治疗效应估计值,包括RCT和RWD
结果将在线报告,正在进行的RCT的结果将在可用时添加。这
该项目是第一个基于经验评估RWD心血管结局研究有效性的项目
在各种流行病学和分析性临床问题的大样本中的表现
方法.研究结果将指导研究者计划心血管结局的RWD研究,
对RWD研究回答患者、提供者和其他人重要问题的能力的信心
持份者
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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科研奖励(0)
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