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利用真实世界数据复制临床试验证据的可行性。

Feasibility of Using Real-World Data to Replicate Clinical Trial Evidence.

机构信息

Yale School of Medicine, New Haven, Connecticut.

Department of Medicine, University of California, San Francisco School of Medicine, San Francisco.

出版信息

JAMA Netw Open. 2019 Oct 2;2(10):e1912869. doi: 10.1001/jamanetworkopen.2019.12869.

Abstract

IMPORTANCE

Although randomized clinical trials are considered to be the criterion standard for generating clinical evidence, the use of real-world evidence to evaluate the efficacy and safety of medical interventions is gaining interest. Whether observational data can be used to address the same clinical questions being answered by traditional clinical trials is still unclear.

OBJECTIVE

To identify the number of clinical trials published in high-impact journals in 2017 that could be feasibly replicated using observational data from insurance claims and/or electronic health records (EHRs).

DESIGN, SETTING, AND PARTICIPANTS: In this cross-sectional analysis, PubMed was searched to identify all US-based clinical trials, regardless of randomization, published between January 1, 2017, and December 31, 2017, in the top 7 highest-impact general medical journals of 2017. Trials were excluded if they did not involve human participants, did not use end points that represented clinical outcomes among patients, were not characterized as clinical trials, and had no recruitment sites in the United States.

MAIN OUTCOMES AND MEASURES

The primary outcomes were the number and percentage of trials for which the intervention, indication, trial inclusion and exclusion criteria, and primary end points could be ascertained from insurance claims and/or EHR data.

RESULTS

Of the 220 US-based trials analyzed, 33 (15.0%) could be replicated using observational data because their intervention, indication, inclusion and exclusion criteria, and primary end points could be routinely ascertained from insurance claims and/or EHR data. Of the 220 trials, 86 (39.1%) had an intervention that could be ascertained from insurance claims and/or EHR data. Among the 86 trials, 62 (72.1%) had an indication that could be ascertained. Forty-five (72.6%) of 62 trials had at least 80% of inclusion and exclusion criteria data that could be ascertained. Of these 45 studies, 33 (73.3%) had at least 1 primary end point that could be ascertained.

CONCLUSIONS AND RELEVANCE

This study found that only 15% of the US-based clinical trials published in high-impact journals in 2017 could be feasibly replicated through analysis of administrative claims or EHR data. This finding suggests the potential for real-world evidence to complement clinical trials, both by examining the concordance between randomized experiments and observational studies and by comparing the generalizability of the trial population with the real-world population of interest.

摘要

重要性

虽然随机临床试验被认为是产生临床证据的标准,但使用真实世界证据来评估医疗干预措施的疗效和安全性越来越受到关注。观察性数据是否可以用于解决传统临床试验所回答的相同临床问题尚不清楚。

目的

确定 2017 年发表在高影响力期刊上的可以使用医疗保险索赔和/或电子健康记录 (EHR) 中的观察数据来复制的临床试验数量。

设计、设置和参与者:在这项横断面分析中,检索了 PubMed,以确定 2017 年 1 月 1 日至 12 月 31 日期间发表在 2017 年最高影响的 7 种一般医学期刊中的所有基于美国的临床试验,无论是否随机。如果试验不涉及人类参与者、不使用代表患者临床结果的终点、不被描述为临床试验、并且没有在美国的招募地点,则将其排除在外。

主要结局和测量

主要结局是可以从医疗保险索赔和/或 EHR 数据中确定干预措施、适应证、试验纳入和排除标准以及主要终点的试验数量和百分比。

结果

在分析的 220 项美国试验中,有 33 项(15.0%)可以通过观察性数据复制,因为可以从医疗保险索赔和/或 EHR 数据中常规确定其干预措施、适应证、纳入和排除标准以及主要终点。在 220 项试验中,有 86 项(39.1%)的干预措施可以从医疗保险索赔和/或 EHR 数据中确定。在 86 项试验中,有 62 项(72.1%)有适应证可以确定。45 项(72.6%)的 62 项试验中,至少有 80%的纳入和排除标准数据可以确定。在这 45 项研究中,有 33 项(73.3%)至少有 1 个主要终点可以确定。

结论和相关性

本研究发现,2017 年发表在高影响力期刊上的基于美国的临床试验中,只有 15%可以通过分析行政索赔或 EHR 数据来复制。这一发现表明,真实世界证据具有补充临床试验的潜力,既可以通过检查随机试验和观察性研究之间的一致性,也可以通过比较试验人群与实际关注人群的可推广性。

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