Duke Clinical Research Institute, Durham, NC, USA.
Duke University School of Medicine, Durham, NC, USA.
Clin Trials. 2022 Dec;19(6):655-664. doi: 10.1177/17407745221114298. Epub 2022 Jul 24.
Despite the extensive use of real-world data for retrospective, observational clinical research, our understanding of how real-world data might increase the efficiency of data collection in patient-level randomized clinical trials is largely unknown. The structure of real-world data is inherently heterogeneous, with each source electronic health record and claims database different from the next. Their fitness-for-use as data sources for multisite trials in the United States has not been established.
For a subset of participants in the HARMONY Outcomes Trial, we obtained electronic health record data from recruiting sites or Medicare claims data from the Centers for Medicare & Medicaid Services. For baseline characteristics and follow-up events, we assessed the level of agreement between these real-world data and data documented in the trial database.
Real-world data-derived demographic information tended to agree with trial-reported demographic information, although real-world data were less accurate in identifying medical history. The ability of real-world data to identify baseline medication usage differed by real-world data source, with claims data demonstrating substantially better performance than electronic health record data. The limited number of lab results in the collected electronic health record data matched closely with values in the trial database. There were not enough follow-up events in the ancillary study population to draw meaningful conclusions about the performance of real-world data for identification of events. Based on the conduct of this ancillary study, the challenges and opportunities of using real-world data within clinical trials are discussed.
Based on a subset of participants from the HARMONY Outcomes Trial, our results suggest that electronic health record or claims data, as currently available, are unlikely to be a complete substitute for trial data collection of medical history or baseline lab results, but that Medicare claims were able to identify most medications. The limited size of the study population prevents us from drawing strong conclusions based on these results, and other studies are clearly needed to confirm or refute these findings.
尽管真实世界数据被广泛用于回顾性、观察性临床研究，但我们对于真实世界数据如何提高患者水平随机临床试验数据收集效率的理解还知之甚少。真实世界数据的结构本质上是异构的，每个电子健康记录和索赔数据库都与其他数据库不同。它们作为美国多地点试验数据源的适用性尚未确定。
对于 HARMONY 结局试验的一部分参与者，我们从招募地点获得了电子健康记录数据，或者从医疗保险和医疗补助服务中心获得了医疗保险索赔数据。对于基线特征和随访事件，我们评估了这些真实世界数据与试验数据库中记录的数据之间的一致性。
真实世界数据得出的人口统计学信息往往与试验报告的人口统计学信息一致，尽管真实世界数据在识别病史方面准确性较低。真实世界数据识别基线用药情况的能力因真实世界数据来源而异，索赔数据的表现明显优于电子健康记录数据。所收集的电子健康记录数据中的实验室结果数量有限，与试验数据库中的值非常吻合。在辅助研究人群中，随访事件的数量不足以对真实世界数据用于识别事件的性能得出有意义的结论。基于这项辅助研究的结果，讨论了在临床试验中使用真实世界数据的挑战和机遇。
基于 HARMONY 结局试验的一部分参与者，我们的结果表明，电子健康记录或索赔数据，如目前可用的，不太可能完全替代试验数据收集病史或基线实验室结果，但医疗保险索赔能够识别大多数药物。研究人群的规模有限，使我们无法根据这些结果得出强有力的结论，显然需要进行其他研究来证实或反驳这些发现。
