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美国大型国家登记处终点判定自动化算法的开发与验证

Development and validation of an automated algorithm for end point adjudication for a large U.S. national registry.

作者信息

Friedman Daniel J, Pierre Dominique, Wang Yongfei, Gambone Louise, Koutras Christina, Segawa Claire, Farb Andrew, Vemulapalli Sreekanth, Varosy Paul D, Masoudi Frederick A, Lansky Alexandra, Curtis Jeptha P, Freeman James V

机构信息

Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT; Duke Clinical Research Institute, Durham, NC.

Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT.

出版信息

Am Heart J. 2022 Dec;254:102-111. doi: 10.1016/j.ahj.2022.08.006. Epub 2022 Aug 22.

Abstract

BACKGROUND

Clinical events committee (CEC) evaluation is the standard approach for end point adjudication in clinical trials. Due to resource constraints, large registries typically rely on site-reported end points without further confirmation, which may preclude use for regulatory oversight.

METHODS

We developed a novel automated adjudication algorithm (AAA) for end point adjudication in the National Cardiovascular Data Registry Left Atrial Appendage Occlusion (LAAO) Registry using an iterative process using CEC adjudication as the "gold standard." A ≥80% agreement rate between automated algorithm adjudication and CEC adjudication was prespecified as clinically acceptable. Agreement rates were calculated.

RESULTS

A total of 92 in-hospital and 127 post-discharge end points were evaluated between January 1, 2016 and June 30, 2019 using AAA and CEC. Agreement for neurologic events was >90%. Percent agreement for in-hospital and post-discharge events was as follows: ischemic stroke 95.7% and 94.5%, hemorrhagic stroke 97.8% and 96.1%, undetermined stroke 97.8% and 99.2%, transient ischemic attack 98.9% and 98.4% and intracranial hemorrhage 100.0% and 94.5%. Agreement was >80% for major bleeding (83.7% and 90.6%) and major vascular complication (89.1% and 97.6%). With this approach, <1% of site reported end points require CEC adjudication. Agreement remained very good during the period after algorithm derivation.

CONCLUSIONS

An AAA-guided approach for end point adjudication was successfully developed and validated for the LAAO Registry. With this approach, the need for formal CEC adjudication was substantially reduced, with accuracy maintained above an 80% agreement threshold. After application specific validation, these methods could be applied to large registries and clinical trials to reduce the cost of event adjudication while preserving scientific validity.

摘要

背景

临床事件委员会(CEC)评估是临床试验中终点判定的标准方法。由于资源限制,大型注册研究通常依赖于研究点报告的终点,而无需进一步确认,这可能使其无法用于监管监督。

方法

我们使用以CEC判定为“金标准”的迭代过程,为国家心血管数据注册研究左心耳封堵术(LAAO)注册研究开发了一种用于终点判定的新型自动判定算法(AAA)。预先设定自动算法判定与CEC判定之间≥80%的一致率为临床可接受。计算一致率。

结果

在2016年1月1日至2019年6月30日期间,使用AAA和CEC对总共92个住院终点和127个出院后终点进行了评估。神经系统事件的一致率>90%。住院和出院后事件的一致率如下:缺血性卒中为95.7%和94.5%,出血性卒中为97.8%和96.1%,未确定卒中为97.8%和99.2%,短暂性脑缺血发作为98.9%和98.4%,颅内出血为100.0%和94.5%。大出血(83.7%和90.6%)和主要血管并发症(89.1%和97.6%)的一致率>80%。采用这种方法,研究点报告的终点中<1%需要CEC判定。在算法推导后的时间段内,一致性仍然非常好。

结论

成功开发了一种用于LAAO注册研究终点判定的AAA指导方法并进行了验证。采用这种方法,大幅减少了正式CEC判定的需求,同时保持了高于80%一致阈值的准确性。经过特定应用验证后,这些方法可应用于大型注册研究和临床试验,以降低事件判定成本,同时保持科学有效性。

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