Zhuang Rui, Chen Ying Qing
University of Washington, Seattle, WA 98195.
Vaccine and Infectious Disease Division and Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, U. S. A.
Stat Biosci. 2020 Dec;12(3):295-323. doi: 10.1007/s12561-019-09244-4. Epub 2019 Jun 4.
In clinical research, validated surrogate markers are highly desirable in study design, monitoring, and analysis, as they do not only reduce the required sample size and follow-up duration, but also facilitate scientific discoveries. However, challenges exist to identify a reliable marker. One particular statistical challenge arises on how to measure and rank the surrogacy of potential markers quantitatively. We review the main statistical methods for evaluating surrogate markers. In addition, we suggest a new measure, the so-called "population surrogacy fraction of treatment effect," or simply the -measure, in the setting of clinical trials. The -measure carries an appealing population impact interpretation and supplements the existing statistical measures of surrogacy by providing "absolute" information. We apply the new measure along with other prominent measures to the HIV Prevention Trial Network 052 Study, a landmark trial for HIV/AIDS treatment-as-prevention.
在临床研究中,经过验证的替代标志物在研究设计、监测和分析中非常受欢迎,因为它们不仅可以减少所需的样本量和随访时间,还能促进科学发现。然而,识别可靠的标志物存在挑战。一个特殊的统计挑战是如何定量测量和排序潜在标志物的替代程度。我们回顾了评估替代标志物的主要统计方法。此外,我们在临床试验背景下提出了一种新的测量方法,即所谓的“治疗效果的总体替代分数”,或简称为“-测量法”。“-测量法”具有吸引人的总体影响解释,并通过提供“绝对”信息来补充现有的替代统计测量方法。我们将这种新方法与其他重要方法一起应用于艾滋病预防试验网络052研究,这是一项关于艾滋病治疗即预防的里程碑式试验。