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Robust Statistical Methods to Identify and Use Surrogate Markers in Diabetes

识别和使用糖尿病替代标记的稳健统计方法

基本信息

批准号：
10613767
负责人：
Layla Parast
金额：
$ 17.37万
依托单位：
UNIVERSITY OF TEXAS AT AUSTIN
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-05-20 至 2023-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10613767
关键词：
Robust Statistical Methods Identify Use

项目摘要

Project Summary/Abstract Diabetes prevention studies often require long term follow-up of patients in order to observe a sufﬁcient number of diabetes diagnoses to precisely estimate treatment effects. In such settings, the availability of a surrogate marker that could be used to estimate the treatment effect and could be observed earlier than the occurrence of a diabetes diagnosis would allow researchers to make conclusions regarding the effectiveness of a given treatment with less required follow-up time. That is, validated surrogate markers could enable shorter randomized clinical trials and require smaller sample sizes, thus accelerating acquisition of clinical information. Identifying such surrogate markers, determining when these markers should be collected, and developing tools to use these markers to test whether a treatment is effective in future studies would contribute signiﬁcantly to research aimed at identifying effective preventative treatments for diabetes. Research on identifying useful surrogate markers has largely focused on estimation of the proportion of treatment effect explained by a surrogate marker since a valid surrogate marker should capture a large proportion of the true treatment effect on the primary outcome. However, current methods to estimate the proportion of treatment effect explained have a number of limitations. In particular, they often require restrictive model assumptions that may not hold in practice and they often only allow for the evaluation of single surrogate marker measured at a single point in time. In addition, current methods do not provide any guidance regarding how to actually use an identiﬁed valid surrogate marker to test for a treatment effect earlier in a future study. In this study, we aim to shift current research practice on surrogate marker evaluation away from restrictive model-based approaches towards robust estimation approaches that can evaluate complex surrogate marker information by proposing novel methods that allow for more ﬂexible model assumptions. Speciﬁcally, we propose to develop novel statistical methods to estimate the proportion of treatment effect explained by surrogate marker measurements over time and by multiple surrogate markers, and identify how such surrogate marker information can be used to test for treatment effectiveness in a future study, thereby allowing for less required follow-up time and shorter trials. We additionally propose to develop methods to identify heterogeneity in the utility of a surrogate marker and a procedure to account for such heterogeneity when using the surrogate marker to test for a treatment effect in a future study. We will apply these methods to data from the Diabetes Prevention Program study to comprehensively evaluate and identify potential surrogate markers of diabetes and to produce tools such that identiﬁed surrogate markers could be used to test for effective treatments in future diabetes studies.

项目总结/摘要糖尿病预防研究通常需要对患者进行长期随访，以观察足够数量的患者以精确评估治疗效果。在这种情况下，代理人的可用性可用于估计治疗效果并可在发生治疗前观察到的标记物。糖尿病的诊断将使研究人员能够对给定治疗的有效性做出结论所需的随访时间更短。也就是说，经验证的替代标志物可以实现更短的随机临床试验。试验和需要更小的样本量，从而加快临床信息的获取。识别此类替代标记，确定何时应收集这些标记，并开发使用这些标记的工具。在未来的研究中，检测治疗是否有效的标志物将对旨在找到有效的糖尿病预防治疗方法识别有用的替代标志物的研究主要集中在估计治疗比例由于有效的替代标志物应该捕获大部分真实的治疗对主要结局的影响。然而，目前估计治疗效果比例的方法解释有一些局限性。特别是，它们通常需要限制性的模型假设，在实践中不成立，并且它们通常仅允许评价在单一时间点测量的单一替代标志物。时间点此外，当前的方法没有提供关于如何实际使用已识别的艾德的任何指导有效的替代标记物，以在未来的研究中更早地测试治疗效果。在这项研究中，我们的目标是转移电流，替代标记评价的研究实践，从基于限制性模型的方法走向稳健的方法通过提出新的方法，可以评估复杂的替代标记信息的估计方法允许更灵活的模型假设。具体而言，我们建议开发新的统计方法估计替代标志物测量值随时间推移解释的治疗效应比例，多个替代标志物，并确定如何使用这些替代标志物信息来测试治疗因此，可以减少所需的随访时间和缩短试验时间。我们另外建议开发方法来鉴定替代标记物效用的异质性，并开发程序，在未来的研究中使用替代标志物测试治疗效果时，考虑到这种异质性。我们将这些方法应用于糖尿病预防项目研究的数据，以全面评估并确定潜在的糖尿病替代标志物，并产生工具，可以用来测试未来糖尿病研究中的有效治疗方法。