当前位置: X-MOL 学术J. Am. Soc. Nephrol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Optimizing the Design and Analysis of Future AKI Trials
Journal of the American Society of Nephrology ( IF 10.3 ) Pub Date : 2022-08-01 , DOI: 10.1681/asn.2021121605
Matthieu Legrand 1, 2 , Sean M Bagshaw 3 , Jay L Koyner 4 , Ivonne H Schulman 5 , Michael R Mathis 6 , Juliane Bernholz 7 , Steven Coca 8 , Martin Gallagher 9 , Stéphane Gaudry 2, 10, 11 , Kathleen D Liu 12 , Ravindra L Mehta 13 , Romain Pirracchio 14 , Abigail Ryan 15 , Dominik Steubl 16, 17 , Norman Stockbridge 18 , Fredrik Erlandsson 19 , Alparslan Turan 20, 21 , F Perry Wilson 22 , Alexander Zarbock 23 , Michael P Bokoch 1 , Jonathan D Casey 24 , Patrick Rossignol 2, 25, 26 , Michael O Harhay 27
Affiliation  

AKI is a complex clinical syndrome associated with an increased risk of morbidity and mortality, particularly in critically ill and perioperative patient populations. Most AKI clinical trials have been inconclusive, failing to detect clinically important treatment effects at predetermined statistical thresholds. Heterogeneity in the pathobiology, etiology, presentation, and clinical course of AKI remains a key challenge in successfully testing new approaches for AKI prevention and treatment. This article, derived from the "AKI" session of the "Kidney Disease Clinical Trialists" virtual workshop held in October 2021, reviews barriers to and strategies for improving the design and implementation of clinical trials in patients with, or at risk of, developing AKI. The novel approaches to trial design included in this review span adaptive trial designs that increase the knowledge gained from each trial participant; pragmatic trial designs that allow for the efficient enrollment of sufficiently large numbers of patients to detect small, but clinically significant, treatment effects; and platform trial designs that use one trial infrastructure to answer multiple clinical questions simultaneously. This review also covers novel approaches to clinical trial analysis, such as Bayesian analysis and assessing heterogeneity in the response to therapies among trial participants. We also propose a road map and actionable recommendations to facilitate the adoption of the reviewed approaches. We hope that the resulting road map will help guide future clinical trial planning, maximize learning from AKI trials, and reduce the risk of missing important signals of benefit (or harm) from trial interventions.



中文翻译:

优化未来 AKI 试验的设计和分析

AKI 是一种复杂的临床综合征,与发病率和死亡率风险增加相关,特别是在危重患者和围手术期患者群体中。大多数 AKI 临床试验尚无结论,未能在预定的统计阈值下检测到临床上重要的治疗效果。AKI 的病理学、病因、表现和临床病程的异质性仍然是成功测试 AKI 预防和治疗新方法的关键挑战。本文源自 2021 年 10 月举办的“肾脏疾病临床试验家”虚拟研讨会的“AKI”分会,回顾了针对患有 AKI 或有风险的患者进行临床试验的改进设计和实施的障碍和策略。本综述中包含的试验设计新方法涵盖了适应性试验设计,这些设计增加了从每个试验参与者获得的知识;务实的试验设计,允许有效招募足够多的患者,以检测微小但具有临床意义的治疗效果;以及使用一个试验基础设施同时回答多个临床问题的平台试验设计。本综述还涵盖了临床试验分析的新方法,例如贝叶斯分析和评估试验参与者对治疗反应的异质性。我们还提出了路线图和可行的建议,以促进经过审查的方法的采用。我们希望最终的路线图将有助于指导未来的临床试验规划,最大限度地从 AKI 试验中学习,并减少错过试验干预中有益(或危害)的重要信号的风险。

更新日期:2022-07-30
down
wechat
bug