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急性髓系白血病试验中临床终点的解读

Interpretation of clinical endpoints in trials of acute myeloid leukemia.

作者信息

Medeiros Bruno C

机构信息

Department of Medicine, Stanford University School of Medicine, 875 Blake Wilbur Dr, Stanford, CA, USA.

出版信息

Leuk Res. 2018 May;68:32-39. doi: 10.1016/j.leukres.2018.02.002. Epub 2018 Feb 7.

DOI:10.1016/j.leukres.2018.02.002
PMID:29524739
Abstract

Treatment regimens for acute myeloid leukemia (AML) have remained largely unchanged until recently. Molecular advances have opened the door to targeted therapies, many of which are in late-phase clinical trials. As new therapeutic opportunities arise, it is appropriate to review key aspects of clinical trial design, statistical interpretation of outcomes, and methods of data reporting. Complete remission and overall survival (OS) are common primary endpoints in early-phase AML clinical trials. OS and event-free survival are frequent primary endpoints in phase 3 trials. Clinical trials are designed to address the primary endpoint using prespecified α and power levels. Interpretation of additional endpoints (eg, secondary endpoints and subgroup analyses) must be viewed in light of a trial's statistical design. Furthermore, variations in reporting of endpoints must be considered in order to understand trial outcomes. Time-to-event endpoints are typically reported using Kaplan-Meier curves, which are visually informative. Statistical data derived from these curves can be complex, and a variety of factors may impact interpretation. The purpose of this review is to discuss the nuances of common AML trial endpoints and their data presentation to better inform evaluation and understanding of clinical trial data.

摘要

直到最近,急性髓系白血病(AML)的治疗方案在很大程度上仍未改变。分子学进展为靶向治疗打开了大门,其中许多靶向治疗正处于后期临床试验阶段。随着新的治疗机会出现,回顾临床试验设计的关键方面、结果的统计学解释以及数据报告方法是恰当的。完全缓解和总生存期(OS)是AML早期临床试验中常见的主要终点。OS和无事件生存期是3期试验中常见的主要终点。临床试验旨在使用预先设定的α水平和检验效能来解决主要终点问题。对其他终点(如次要终点和亚组分析)的解释必须结合试验的统计学设计来看待。此外,为了理解试验结果,必须考虑终点报告的差异。事件发生时间终点通常使用Kaplan-Meier曲线报告,该曲线具有直观的信息。从这些曲线得出的统计数据可能很复杂,多种因素可能会影响解释。本综述的目的是讨论AML常见试验终点及其数据呈现的细微差别,以便更好地为评估和理解临床试验数据提供信息。

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